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Tatsunori HashimotoAssistant Professor, Stanford thashim [AT] stanford.edu
BioI am currently an assistant professor at the computer science department in Stanford university. My research uses tools from statistics to make machine learning systems more robust and trustworthy — especially in complex systems such as large language models. The goal of my research is to use robustness and worst-case performance as a lens to understand and make progress on several fundamental challenges in machine learning and natural language processing. A few topics of recent interest are,
Previously, I was a post-doc at Stanford working for John C. Duchi and Percy Liang on tradeoffs between the average and worst-case performance of machine learning models. Before my post-doc, I was a graduate student at MIT co-advised by Tommi Jaakkola and David Gifford and a undergraduate student at Harvard in statistics and math advised by Edoardo Airoldi. AdviseesYu Sun (2023-) Postdoc (w/ Sanmi Koyejo and Carlos Guestrin) Ian Covert (2023-) Postdoc (w/ James Zou) Lisa Li (2021-) Graduate Student (w/ Percy Liang) Tianyi Zhang (2021-) Graduate Student Yann Dubois (2022-) Graduate Student (w/ Percy Liang) Neil Band (2023-) Graduate Student (w/ Tengyu Ma) Nicole Meister (2023-) Graduate Student (w/ Carlos Guestrin) Zitong Yang (2024-) Graduate Student (w/ Emmanuel Candes) Chenglei Si (2024-) Graduate Student (w/ Diyi Yang) Christopher Mohri (2024-) Graduate Student (w/ John Duchi) Tristan Thrush (2024-) Graduate Student (w/ Chris Potts) PublicationsMost recent publications on Google Scholar.
Observational Scaling Laws and the Predictability of Language Model Performance PDF Yangjun Ruan, Chris J Maddison, Tatsunori Hashimoto ArXiv preprint Length-controlled AlpacaEval: A simple way to debias automatic evaluators PDF Yann Dubois, Balázs Galambosi, Percy Liang, Tatsunori B Hashimoto ArXiv preprint Linguistic Calibration of Language Models PDF Neil Band, Xuechen Li, Tengyu Ma, Tatsunori Hashimoto International Conference on Machine Learning (ICML 2024) Language Models with Conformal Factuality Guarantees PDF Christopher Mohri, Tatsunori Hashimoto International Conference on Machine Learning (ICML 2024) Proving test set contamination in black box language models PDF Yonatan Oren, Nicole Meister, Niladri Chatterji, Faisal Ladhak, Tatsunori B Hashimoto International Conference on Learning Representations (ICLR 2024) Benchmarking and improving generator-validator consistency of language models PDF Xiang Lisa Li, Vaishnavi Shrivastava, Siyan Li, Tatsunori Hashimoto, Percy Liang International Conference on Learning Representations (ICLR 2024) Identifying the risks of lm agents with an lm-emulated sandbox PDF Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J Maddison, Tatsunori Hashimoto International Conference on Learning Representations (ICLR 2024) Robust Distortion-free Watermarks for Language Models PDF Rohith Kuditipudi, John Thickstun, Tatsunori Hashimoto, Percy Liang Transactions on Machine Learning Research (TMLR 2024) Likelihood-Based Diffusion Language Models PDF Ishaan Gulrajani, Tatsunori B. Hashimoto Advances in Neural Information Processing Systems (NeurIPS 2023) AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback PDF Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B Hashimoto Advances in Neural Information Processing Systems (NeurIPS 2023) Whose Opinions Do Language Models Reflect? PDF Shibani Santurkar, Esin Durmus, Faisal Ladhak, Cinoo Lee, Percy Liang, Tatsunori Hashimoto International Conference on Machine Learning (ICML 2023, oral) Data Feedback Loops: Model-driven Amplification of Dataset Biases PDF Rohan Taori, Tatsunori B Hashimoto International Conference on Machine Learning (ICML 2023, oral)" Foundation Models and Fair Use PDF Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A Lemley, Percy Liang Journal of Machine Learning Research (JMLR 2024) Navigating the Grey Area: Expressions of Overconfidence and Uncertainty in Language Models PDF Kaitlyn Zhou, Dan Jurafsky, Tatsunori Hashimoto Conference on Empirical Methods in Natural Language Processing (EMNLP 2023) Benchmarking Large Language Models for News Summarization PDF Tianyi Zhang, Faisal Ladhak, Esin Durmus, Percy Liang, Kathleen McKeown, Tatsunori B Hashimoto Transactions of the Association of Computational Linguistics (TACL, presented at EMNLP 2023) Tracing and Removing Data Errors in Natural Language Generation Datasets PDF Faisal Ladhak, Esin Durmus, Tatsunori Hashimoto Annual Meeting of the Association of Computational Linguistics (ACL 2023) Diffusion-LM Improves Controllable Text Generation PDF Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B Hashimoto Advances in Neural Information Processing Systems 31 (NeurIPS 2022) Identifiability Conditions for Domain Adaptation PDF Ishaan Gulrajani, Tatsunori B Hashimoto International Conference on Machine Learning (ICML 2022) Emergent abilities of large language models PDF Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus Transactions on Machine Learning Research (2022) Jury learning: Integrating dissenting voices into machine learning models PDF Mitchell Gordon, Michelle Lam, Joon Park, Kayur Patel, Jeff Hancock, Tatsunori B Hashimoto, Michael Bernstein Conference on Human Factors in Computing Systems (CHI 2022, Best paper) Spurious Correlations in Reference-Free Evaluation of Text Generation PDF Esin Durmus, Faisal Ladhak, Tatsunori B Hashimoto Annual Meeting of the Association of Computational Linguistics (ACL 2022) Large Language Models Can Be Strong Differentially Private Learners PDF Xuechen Li, Florian Tramer, Percy Liang, Tatsunori B Hashimoto International Conference on Learning Representations (ICLR 2022 Oral) Is Importance Weighting Incompatible with Interpolating Classifiers? PDF Ke A Wang, Niladri S Chatterji, Saminul Haque, Tatsunori B Hashimoto International Conference on Learning Representations (ICLR 2022) Model Performance Scaling with Multiple Data Sources PDF Tatsunori B Hashimoto International Conference on Machine Learning (ICML 2021) Improved Natural Language Generation via Loss Truncation PDF Daniel Kang, Tatsunori B Hashimoto Annual Meeting of the Association of Computational Linguistics (ACL 2020) Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-case Generalization PDF Shiori Sagawa*, Pang Wei Koh*, Tatsunori B Hashimoto, Percy Liang International Conference on Learning Representations (ICLR 2020) Distributionally Robust Language Modeling PDF Yonatan Oren*, Shiori Sagawa *, Tatsunori B Hashimoto *, Percy Liang Empirical Methods in Natural Language Processing (EMNLP 2019) Distributionally Robust Losses For Latent Covariate Mixtures PDF John C Duchi, Tatsunori B Hashimoto, Hongseok Namkoong Operations Research (2022) Unifying Human and Statistical Evaluation for Natural Language Generation PDF Tatsunori B Hashimoto*, Hugh Zhang*, Percy Liang Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2019) Generating Sentences by Editing Prototypes PDF Kelvin Guu*, Tatsunori B Hashimoto*, Yonatan Oren, Percy Liang Transactions of the Association of Computational Linguistics (TACL, presented at ACL 2018) Fairness Without Demographics in Repeated Loss Minimization PDF Tatsunori B Hashimoto, Megha Srivastava, Hongseok Namkoong, Percy Liang Proceedings of the 35th International Conference on Machine Learning (ICML 2018, Best paper runner up) Word embeddings as metric recovery in semantic spaces PDF Tatsunori B Hashimoto, David Alvarez-Melis, Tommi S Jaakkola Transactions of the Association for Computational Linguistics 4 (TACL, presented at ACL 2016) Metric recovery from directed unweighted graphs PDF Tatsunori B Hashimoto, Yi Sun, Tommi S Jaakkola Artificial Intelligence and Statistics (AISTATS 2015), (best poster at NeurIPS 2014 workshop on networks) Observational Scaling Laws and the Predictability of Language Model Performance PDF Yangjun Ruan, Chris J Maddison, Tatsunori Hashimoto ArXiv preprint Length-controlled AlpacaEval: A simple way to debias automatic evaluators PDF Yann Dubois, Balázs Galambosi, Percy Liang, Tatsunori B Hashimoto ArXiv preprint Trustless Audits without Revealing Data or Models PDF Suppakit Waiwitlikhit, Ion Stoica, Yi Sun, Tatsunori Hashimoto, Daniel Kang International Conference on Machine Learning (ICML 2024) Linguistic Calibration of Language Models PDF Neil Band, Xuechen Li, Tengyu Ma, Tatsunori Hashimoto International Conference on Machine Learning (ICML 2024) A Survey on Data Selection for Language Models PDF Alon Albalak, Yanai Elazar, Sang Michael Xie, Shayne Longpre, Nathan Lambert, Xinyi Wang, Niklas Muennighoff, Bairu Hou, Liangming Pan, Haewon Jeong, Colin Raffel, Shiyu Chang, Tatsunori Hashimoto, William Yang Wang ArXiv preprint Language Models with Conformal Factuality Guarantees PDF Christopher Mohri, Tatsunori Hashimoto International Conference on Machine Learning (ICML 2024) Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution PDF Ian Covert, Chanwoo Kim, Su-In Lee, James Zou, Tatsunori Hashimoto ArXiv preprint On the learnability of watermarks for language models PDF Chenchen Gu, Xiang Lisa Li, Percy Liang, Tatsunori Hashimoto International Conference on Learning Representations (ICLR 2024) Removing rlhf protections in gpt-4 via fine-tuning PDF Qiusi Zhan, Richard Fang, Rohan Bindu, Akul Gupta, Tatsunori Hashimoto, Daniel Kang ArXiv preprint Proving test set contamination in black box language models PDF Yonatan Oren, Nicole Meister, Niladri Chatterji, Faisal Ladhak, Tatsunori B Hashimoto International Conference on Learning Representations (ICLR 2024) Benchmarking and improving generator-validator consistency of language models PDF Xiang Lisa Li, Vaishnavi Shrivastava, Siyan Li, Tatsunori Hashimoto, Percy Liang International Conference on Learning Representations (ICLR 2024) Identifying the risks of lm agents with an lm-emulated sandbox PDF Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J Maddison, Tatsunori Hashimoto International Conference on Learning Representations (ICLR 2024) Safety-tuned llamas: Lessons from improving the safety of large language models that follow instructions PDF Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Röttger, Dan Jurafsky, Tatsunori Hashimoto, James Zou International Conference on Learning Representations (ICLR 2024) Robust Distortion-free Watermarks for Language Models PDF Rohith Kuditipudi, John Thickstun, Tatsunori Hashimoto, Percy Liang Transactions on Machine Learning Research (TMLR 2024) One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention PDF Arvind Mahankali, Tatsunori B. Hashimoto, Tengyu Ma International Conference on Learning Representations (ICLR 2024) Likelihood-Based Diffusion Language Models PDF Ishaan Gulrajani, Tatsunori B. Hashimoto Advances in Neural Information Processing Systems (NeurIPS 2023) AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback PDF Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B Hashimoto Advances in Neural Information Processing Systems (NeurIPS 2023) When Do Pre-Training Biases Propagate to Downstream Tasks? A Case Study in Text Summarization PDF Faisal Ladhak, Esin Durmus, Mirac Suzgun, Tianyi Zhang, Dan Jurafsky, Kathleen Mckeown, Tatsunori B Hashimoto Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023) Whose Opinions Do Language Models Reflect? PDF Shibani Santurkar, Esin Durmus, Faisal Ladhak, Cinoo Lee, Percy Liang, Tatsunori Hashimoto International Conference on Machine Learning (ICML 2023, oral) Data Feedback Loops: Model-driven Amplification of Dataset Biases PDF Rohan Taori, Tatsunori B Hashimoto International Conference on Machine Learning (ICML 2023, oral)" Foundation Models and Fair Use PDF Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A Lemley, Percy Liang Journal of Machine Learning Research (JMLR 2024) Navigating the Grey Area: Expressions of Overconfidence and Uncertainty in Language Models PDF Kaitlyn Zhou, Dan Jurafsky, Tatsunori Hashimoto Conference on Empirical Methods in Natural Language Processing (EMNLP 2023) Out-of-Domain Robustness via Targeted Augmentations PDF Irena Gao, Shiori Sagawa, Pang Wei Koh, Tatsunori Hashimoto, Percy Liang International Conference on Machine Learning (ICML 2023) Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks PDF Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto ArXiv preprint Evaluating Self-Supervised Learning via Risk Decomposition PDF Yann Dubois, Tatsunori Hashimoto, Percy Liang International Conference on Machine Learning (ICML 2023, oral) Benchmarking Large Language Models for News Summarization PDF Tianyi Zhang, Faisal Ladhak, Esin Durmus, Percy Liang, Kathleen McKeown, Tatsunori B Hashimoto Transactions of the Association of Computational Linguistics (TACL, presented at EMNLP 2023) Tracing and Removing Data Errors in Natural Language Generation Datasets PDF Faisal Ladhak, Esin Durmus, Tatsunori Hashimoto Annual Meeting of the Association of Computational Linguistics (ACL 2023) Privacy-Preserving Domain Adaptation of Semantic Parsers PDF Fatemehsadat Mireshghallah, Richard Shin, Yu Su, Tatsunori Hashimoto, Jason Eisner ArXiv preprint Coder Reviewer Reranking for Code Generation PDF Tianyi Zhang, Tao Yu, Tatsunori B Hashimoto, Mike Lewis, Wen-tau Yih, Daniel Fried, Sida I Wang International Conference on Machine Learning (ICML 2023) ZK-IMG: Attested Images via Zero-Knowledge Proofs to Fight Disinformation PDF Daniel Kang, Tatsunori Hashimoto, Ion Stoica, Yi Sun ArXiv preprint Easily accessible text-to-image generation amplifies demographic stereotypes at large scale PDF Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, Aylin Caliskan FAccT 2023 Contrastive decoding: Open-ended text generation as optimization PDF Xiang Lisa Li, Ari Holtzman, Daniel Fried, Percy Liang, Jason Eisner, Tatsunori Hashimoto, Luke Zettlemoyer, Mike Lewis ArXiv preprint Scaling up Trustless DNN Inference with Zero-Knowledge Proofs PDF Daniel Kang, Tatsunori Hashimoto, Ion Stoica, Yi Sun ArXiv preprint Is a caption worth a thousand images? a controlled study for representation learning PDF Shibani Santurkar, Yann Dubois, Rohan Taori, Percy Liang, Tatsunori Hashimoto International Conference on Learning Representations (ICLR 2023) A Closer Look at the Calibration of Differentially Private Learners PDF Hanlin Zhang, Xuechen Li, Prithviraj Sen, Salim Roukos, Tatsunori Hashimoto ArXiv preprint Improving self-supervised learning by characterizing idealized representations PDF Yann Dubois, Tatsunori Hashimoto, Stefano Ermon, Percy Liang Advances in Neural Information Processing Systems 31 (NeurIPS 2022) When Does Differentially Private Learning Not Suffer in High Dimensions? PDF Xuechen Li, Daogao Liu, Tatsunori Hashimoto, Huseyin A. Inan, Janardhan Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta Advances in Neural Information Processing Systems 31 (NeurIPS 2022) Diffusion-LM Improves Controllable Text Generation PDF Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B Hashimoto Advances in Neural Information Processing Systems 31 (NeurIPS 2022) Identifiability Conditions for Domain Adaptation PDF Ishaan Gulrajani, Tatsunori B Hashimoto International Conference on Machine Learning (ICML 2022) Undersampling is a Minimax Optimal Robustness Intervention in Nonparametric Classification PDF Niladri Chatterji, Saminul Haque, Tatsunori B Hashimoto ArXiv preprint TempLM: Distilling Language Models into Template-Based Generators PDF Tianyi Zhang, Mina Lee, Lisa Li, Ende Shen, Tatsunori B Hashimoto ArXiv preprint Emergent abilities of large language models PDF Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus Transactions on Machine Learning Research (2022) Jury learning: Integrating dissenting voices into machine learning models PDF Mitchell Gordon, Michelle Lam, Joon Park, Kayur Patel, Jeff Hancock, Tatsunori B Hashimoto, Michael Bernstein Conference on Human Factors in Computing Systems (CHI 2022, Best paper) Spurious Correlations in Reference-Free Evaluation of Text Generation PDF Esin Durmus, Faisal Ladhak, Tatsunori B Hashimoto Annual Meeting of the Association of Computational Linguistics (ACL 2022) Large Language Models Can Be Strong Differentially Private Learners PDF Xuechen Li, Florian Tramer, Percy Liang, Tatsunori B Hashimoto International Conference on Learning Representations (ICLR 2022 Oral) Language Modeling via Stochastic Processes PDF Rose E Wang, Esin Durmus, Noah Goodman, Tatsunori B Hashimoto International Conference on Learning Representations (ICLR 2022 Oral) Is Importance Weighting Incompatible with Interpolating Classifiers? PDF Ke A Wang, Niladri S Chatterji, Saminul Haque, Tatsunori B Hashimoto International Conference on Learning Representations (ICLR 2022) Distributionally Robust Models with Parametric Likelihood Ratios PDF Paul Michel, Tatsunori B Hashimoto, Graham Neubig International Conference on Learning Representations (ICLR 2022) Extending the WILDS Benchmark for Unsupervised Adaptation PDF Shiori Sagawa, Pang Wei Koh [...] Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang International Conference on Learning Representations (ICLR 2022 Oral) On the opportunities and risks of foundation models PDF Rishi Bommasani [.. alphabetical authors ..] Tatsunori Hashimoto [...] ArXiv preprint Accelerating approximate aggregation queries with expensive predicates PDF Daniel Kang, John Guibas, Peter Bailis, Tatsunori B Hashimoto, Yi Sun, Matei Zaharia ACM Conference on Management of Data (SIGMOD 2022) Model Performance Scaling with Multiple Data Sources PDF Tatsunori B Hashimoto International Conference on Machine Learning (ICML 2021) Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions PDF Dorottya Demszky, Jing Liu, Zid Mancenido, Julie Cohen, Heather Hill, Dan Jurafsky, Tatsunori B Hashimoto Annual Meeting of the Association of Computational Linguistics (ACL 2020) DReCa: A general task augmentation strategy for few-shot natural language inference PDF Shikhar Murty, Tatsunori B Hashimoto, Christopher D Manning Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2021) On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies PDF Tianyi Zhang, Tatsunori B Hashimoto Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2021) Modeling the Second Player in Distributionally Robust Optimization PDF Paul Michel, Tatsunori B. Hashimoto, Graham Neubig International Conference on Learning Representations (ICLR 2021) Task-agnostic Indexes for Deep Learning-based Queries over Unstructured Data PDF Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Matei Zaharia Preprint The Disagreement Deconvolution: Bringing Machine Learning Performance Metrics In Line With Reality PDF Mitchell L Gordon, Kaitlyn Zhou, Kayur Patel, Tatsunori B Hashimoto, Michael S Bernstein Conference on Human Factors in Computing Systems (CHI 2021) Approximate Selection with Guarantees using Proxies PDF Daniel Kang*, Edward Gan*, Peter Bailis, Tatsunori B Hashimoto, Matei Zaharia International Conference on Very Large Data Bases (VLDB 2020) Improved Natural Language Generation via Loss Truncation PDF Daniel Kang, Tatsunori B Hashimoto Annual Meeting of the Association of Computational Linguistics (ACL 2020) Robustness to Spurious Correlations via Human Annotations PDF Megha Srivastava, Tatsunori B Hashimoto, Percy Liang International Conference on Machine Learning (ICML 2020) Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-case Generalization PDF Shiori Sagawa*, Pang Wei Koh*, Tatsunori B Hashimoto, Percy Liang International Conference on Learning Representations (ICLR 2020) Learning Autocomplete Systems as a Communication Game PDF Mina Lee, Tatsunori B Hashimoto, Percy Liang Emergent Communication Workshop at Neural Information Processing Systems (NeurIPS 2019) Distributionally Robust Language Modeling PDF Yonatan Oren*, Shiori Sagawa *, Tatsunori B Hashimoto *, Percy Liang Empirical Methods in Natural Language Processing (EMNLP 2019) Distributionally Robust Losses For Latent Covariate Mixtures PDF John C Duchi, Tatsunori B Hashimoto, Hongseok Namkoong Operations Research (2022) Inferring Multidimensional Rates of Aging from Cross-Sectional Data PDF Emma Pierson*, Pang Wei Koh *, Tatsunori B Hashimoto *, Daphne Koller, Jure Lesokevic, Nicholas Eriksson, Percy Liang 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019) Unifying Human and Statistical Evaluation for Natural Language Generation PDF Tatsunori B Hashimoto*, Hugh Zhang*, Percy Liang Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2019) A Retrieve-and-Edit Framework for Predicting Structured Outputs PDF Tatsunori B Hashimoto, Kelvin Guu, Yonatan Oren, Percy Liang Advances in Neural Information Processing Systems 31 (NeurIPS 2018, Oral) Generating Sentences by Editing Prototypes PDF Kelvin Guu*, Tatsunori B Hashimoto*, Yonatan Oren, Percy Liang Transactions of the Association of Computational Linguistics (TACL, presented at ACL 2018) Fairness Without Demographics in Repeated Loss Minimization PDF Tatsunori B Hashimoto, Megha Srivastava, Hongseok Namkoong, Percy Liang Proceedings of the 35th International Conference on Machine Learning (ICML 2018, Best paper runner up) Derivative free optimization via repeated classification PDF Tatsunori B Hashimoto, Steve Yadlowsky, John C Duchi 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018) Unsupervised Transformation Learning via Convex Relaxations PDF Tatsunori B Hashimoto, Percy S Liang, John C Duchi Advances in Neural Information Processing Systems 30 (NeurIPS 2017) Continuous representations and models from random walk diffusion limits PDF Tatsunori B Hashimoto PhD Thesis, MIT CSAIL, 2016 Word embeddings as metric recovery in semantic spaces PDF Tatsunori B Hashimoto, David Alvarez-Melis, Tommi S Jaakkola Transactions of the Association for Computational Linguistics 4 (TACL, presented at ACL 2016) Learning Population-Level Diffusions with Generative RNNs PDF Tatsunori B Hashimoto, David Gifford, Tommi S Jaakkola Proceedings of the 33rd International Conference on Machine Learning (ICML 2016) From random walks to distances on unweighted graphs PDF Tatsunori B Hashimoto, Yi Sun, Tommi S Jaakkola Advances in Neural Information Processing Systems (NeurIPS 2015) Metric recovery from directed unweighted graphs PDF Tatsunori B Hashimoto, Yi Sun, Tommi S Jaakkola Artificial Intelligence and Statistics (AISTATS 2015), (best poster at NeurIPS 2014 workshop on networks) A synergistic DNA logic predicts genome-wide chromatin accessibility PDF Tatsunori B Hashimoto*, Richard I Sherwood*, Daniel D Kang*, Nisha Rajagopal, Amira A Barkal, Haoyang Zeng, Bart JM Emons, Sharanya Srinivasan, Tommi S Jaakkola, David K Gifford Genome research (2016) Cas9 Functionally Opens Chromatin PDF Amira A Barkal, Sharanya Srinivasan, Tatsunori B Hashimoto, David K Gifford, Richard I Sherwood PloS One (2016) Cloning-free CRISPR PDF Mandana Arbab, Sharanya Srinivasan, Tatsunori B Hashimoto, Niels Geijsen, Richard I Sherwood Stem cell reports (2015) GERV: a statistical method for generative evaluation of regulatory variants for transcription factor binding PDF Haoyang Zeng, Tatsunori B Hashimoto, Daniel D Kang, David K Gifford Bioinformatics (2015) Long-term persistence and development of induced pancreatic beta cells generated by lineage conversion of acinar cells PDF Weida Li, Claudia Cavelti-Weder, Yinying Zhang, Kendell Clement, Scott Donovan, Gabriel Gonzalez, Jiang Zhu, Marianne Stemann, Ke Xu, Tatsunori B Hashimoto, Takatsugu Yamada, Mio Nakanishi, Yuemei Zhang, Samuel Zeng, David Gifford, Alexander Meissner, Gordon Weir, Qiao Zhou Nature Biotechnology (2014) Universal count correction for high-throughput sequencing PDF Tatsunori B Hashimoto, Matthew D Edwards, David K Gifford PLoS computational biology (2014) Discovery of directional and nondirectional pioneer transcription factors by modeling DNase profile magnitude and shape PDF Richard I Sherwood *, Tatsunori B Hashimoto *, Charles W O'donnell *, Sophia Lewis, Amira A Barkal, John Peter Van Hoff, Vivek Karun, Tommi S Jaakkola, David K Gifford Nature Biotechnology (2014) Quantifying condition-dependent intracellular protein levels enables high-precision fitness estimates PDF Kerry A Geiler-Samerotte, Tatsunori B Hashimoto, Michael F Dion, Bogdan A Budnik, Edoardo M Airoldi, D Allan Drummond PloS one (2013) Lineage-based identification of cellular states and expression programs PDF Tatsunori B Hashimoto, Tommi S Jaakkola, Richard Sherwood, Esteban O. Mazzoni, Hynek Wichterle, David Gifford Bioinformatics (2012) Finding drug discovery rules of thumb with bump hunting PDF Tatsunori B Hashimoto, Matthew Segall Proceedings of the ACS (2010) BFL: a node and edge betweenness based fast layout algorithm for large scale networks. PDF Tatsunori B Hashimoto, Masao Nagasaki, Kaname Kojima, Satoru Miyano BMC bioinformatics (2009) Observational Scaling Laws and the Predictability of Language Model Performance PDF Yangjun Ruan, Chris J Maddison, Tatsunori Hashimoto ArXiv preprint Linguistic Calibration of Language Models PDF Neil Band, Xuechen Li, Tengyu Ma, Tatsunori Hashimoto International Conference on Machine Learning (ICML 2024) Language Models with Conformal Factuality Guarantees PDF Christopher Mohri, Tatsunori Hashimoto International Conference on Machine Learning (ICML 2024) Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution PDF Ian Covert, Chanwoo Kim, Su-In Lee, James Zou, Tatsunori Hashimoto ArXiv preprint Proving test set contamination in black box language models PDF Yonatan Oren, Nicole Meister, Niladri Chatterji, Faisal Ladhak, Tatsunori B Hashimoto International Conference on Learning Representations (ICLR 2024) Robust Distortion-free Watermarks for Language Models PDF Rohith Kuditipudi, John Thickstun, Tatsunori Hashimoto, Percy Liang Transactions on Machine Learning Research (TMLR 2024) One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention PDF Arvind Mahankali, Tatsunori B. Hashimoto, Tengyu Ma International Conference on Learning Representations (ICLR 2024) Likelihood-Based Diffusion Language Models PDF Ishaan Gulrajani, Tatsunori B. Hashimoto Advances in Neural Information Processing Systems (NeurIPS 2023) Data Feedback Loops: Model-driven Amplification of Dataset Biases PDF Rohan Taori, Tatsunori B Hashimoto International Conference on Machine Learning (ICML 2023, oral)" Out-of-Domain Robustness via Targeted Augmentations PDF Irena Gao, Shiori Sagawa, Pang Wei Koh, Tatsunori Hashimoto, Percy Liang International Conference on Machine Learning (ICML 2023) Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks PDF Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto ArXiv preprint Evaluating Self-Supervised Learning via Risk Decomposition PDF Yann Dubois, Tatsunori Hashimoto, Percy Liang International Conference on Machine Learning (ICML 2023, oral) Scaling up Trustless DNN Inference with Zero-Knowledge Proofs PDF Daniel Kang, Tatsunori Hashimoto, Ion Stoica, Yi Sun ArXiv preprint Is a caption worth a thousand images? a controlled study for representation learning PDF Shibani Santurkar, Yann Dubois, Rohan Taori, Percy Liang, Tatsunori Hashimoto International Conference on Learning Representations (ICLR 2023) A Closer Look at the Calibration of Differentially Private Learners PDF Hanlin Zhang, Xuechen Li, Prithviraj Sen, Salim Roukos, Tatsunori Hashimoto ArXiv preprint Improving self-supervised learning by characterizing idealized representations PDF Yann Dubois, Tatsunori Hashimoto, Stefano Ermon, Percy Liang Advances in Neural Information Processing Systems 31 (NeurIPS 2022) When Does Differentially Private Learning Not Suffer in High Dimensions? PDF Xuechen Li, Daogao Liu, Tatsunori Hashimoto, Huseyin A. Inan, Janardhan Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta Advances in Neural Information Processing Systems 31 (NeurIPS 2022) Identifiability Conditions for Domain Adaptation PDF Ishaan Gulrajani, Tatsunori B Hashimoto International Conference on Machine Learning (ICML 2022) Undersampling is a Minimax Optimal Robustness Intervention in Nonparametric Classification PDF Niladri Chatterji, Saminul Haque, Tatsunori B Hashimoto ArXiv preprint Emergent abilities of large language models PDF Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus Transactions on Machine Learning Research (2022) Large Language Models Can Be Strong Differentially Private Learners PDF Xuechen Li, Florian Tramer, Percy Liang, Tatsunori B Hashimoto International Conference on Learning Representations (ICLR 2022 Oral) Is Importance Weighting Incompatible with Interpolating Classifiers? PDF Ke A Wang, Niladri S Chatterji, Saminul Haque, Tatsunori B Hashimoto International Conference on Learning Representations (ICLR 2022) Distributionally Robust Models with Parametric Likelihood Ratios PDF Paul Michel, Tatsunori B Hashimoto, Graham Neubig International Conference on Learning Representations (ICLR 2022) Extending the WILDS Benchmark for Unsupervised Adaptation PDF Shiori Sagawa, Pang Wei Koh [...] Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang International Conference on Learning Representations (ICLR 2022 Oral) Model Performance Scaling with Multiple Data Sources PDF Tatsunori B Hashimoto International Conference on Machine Learning (ICML 2021) Modeling the Second Player in Distributionally Robust Optimization PDF Paul Michel, Tatsunori B. Hashimoto, Graham Neubig International Conference on Learning Representations (ICLR 2021) Task-agnostic Indexes for Deep Learning-based Queries over Unstructured Data PDF Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Matei Zaharia Preprint Approximate Selection with Guarantees using Proxies PDF Daniel Kang*, Edward Gan*, Peter Bailis, Tatsunori B Hashimoto, Matei Zaharia International Conference on Very Large Data Bases (VLDB 2020) Robustness to Spurious Correlations via Human Annotations PDF Megha Srivastava, Tatsunori B Hashimoto, Percy Liang International Conference on Machine Learning (ICML 2020) Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-case Generalization PDF Shiori Sagawa*, Pang Wei Koh*, Tatsunori B Hashimoto, Percy Liang International Conference on Learning Representations (ICLR 2020) Distributionally Robust Losses For Latent Covariate Mixtures PDF John C Duchi, Tatsunori B Hashimoto, Hongseok Namkoong Operations Research (2022) A Retrieve-and-Edit Framework for Predicting Structured Outputs PDF Tatsunori B Hashimoto, Kelvin Guu, Yonatan Oren, Percy Liang Advances in Neural Information Processing Systems 31 (NeurIPS 2018, Oral) Fairness Without Demographics in Repeated Loss Minimization PDF Tatsunori B Hashimoto, Megha Srivastava, Hongseok Namkoong, Percy Liang Proceedings of the 35th International Conference on Machine Learning (ICML 2018, Best paper runner up) Derivative free optimization via repeated classification PDF Tatsunori B Hashimoto, Steve Yadlowsky, John C Duchi 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018) Unsupervised Transformation Learning via Convex Relaxations PDF Tatsunori B Hashimoto, Percy S Liang, John C Duchi Advances in Neural Information Processing Systems 30 (NeurIPS 2017) Continuous representations and models from random walk diffusion limits PDF Tatsunori B Hashimoto PhD Thesis, MIT CSAIL, 2016 Word embeddings as metric recovery in semantic spaces PDF Tatsunori B Hashimoto, David Alvarez-Melis, Tommi S Jaakkola Transactions of the Association for Computational Linguistics 4 (TACL, presented at ACL 2016) Learning Population-Level Diffusions with Generative RNNs PDF Tatsunori B Hashimoto, David Gifford, Tommi S Jaakkola Proceedings of the 33rd International Conference on Machine Learning (ICML 2016) From random walks to distances on unweighted graphs PDF Tatsunori B Hashimoto, Yi Sun, Tommi S Jaakkola Advances in Neural Information Processing Systems (NeurIPS 2015) Metric recovery from directed unweighted graphs PDF Tatsunori B Hashimoto, Yi Sun, Tommi S Jaakkola Artificial Intelligence and Statistics (AISTATS 2015), (best poster at NeurIPS 2014 workshop on networks) Observational Scaling Laws and the Predictability of Language Model Performance PDF Yangjun Ruan, Chris J Maddison, Tatsunori Hashimoto ArXiv preprint Length-controlled AlpacaEval: A simple way to debias automatic evaluators PDF Yann Dubois, Balázs Galambosi, Percy Liang, Tatsunori B Hashimoto ArXiv preprint A Survey on Data Selection for Language Models PDF Alon Albalak, Yanai Elazar, Sang Michael Xie, Shayne Longpre, Nathan Lambert, Xinyi Wang, Niklas Muennighoff, Bairu Hou, Liangming Pan, Haewon Jeong, Colin Raffel, Shiyu Chang, Tatsunori Hashimoto, William Yang Wang ArXiv preprint Language Models with Conformal Factuality Guarantees PDF Christopher Mohri, Tatsunori Hashimoto International Conference on Machine Learning (ICML 2024) On the learnability of watermarks for language models PDF Chenchen Gu, Xiang Lisa Li, Percy Liang, Tatsunori Hashimoto International Conference on Learning Representations (ICLR 2024) Removing rlhf protections in gpt-4 via fine-tuning PDF Qiusi Zhan, Richard Fang, Rohan Bindu, Akul Gupta, Tatsunori Hashimoto, Daniel Kang ArXiv preprint Proving test set contamination in black box language models PDF Yonatan Oren, Nicole Meister, Niladri Chatterji, Faisal Ladhak, Tatsunori B Hashimoto International Conference on Learning Representations (ICLR 2024) Benchmarking and improving generator-validator consistency of language models PDF Xiang Lisa Li, Vaishnavi Shrivastava, Siyan Li, Tatsunori Hashimoto, Percy Liang International Conference on Learning Representations (ICLR 2024) Identifying the risks of lm agents with an lm-emulated sandbox PDF Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J Maddison, Tatsunori Hashimoto International Conference on Learning Representations (ICLR 2024) Safety-tuned llamas: Lessons from improving the safety of large language models that follow instructions PDF Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Röttger, Dan Jurafsky, Tatsunori Hashimoto, James Zou International Conference on Learning Representations (ICLR 2024) Likelihood-Based Diffusion Language Models PDF Ishaan Gulrajani, Tatsunori B. Hashimoto Advances in Neural Information Processing Systems (NeurIPS 2023) AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback PDF Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B Hashimoto Advances in Neural Information Processing Systems (NeurIPS 2023) When Do Pre-Training Biases Propagate to Downstream Tasks? A Case Study in Text Summarization PDF Faisal Ladhak, Esin Durmus, Mirac Suzgun, Tianyi Zhang, Dan Jurafsky, Kathleen Mckeown, Tatsunori B Hashimoto Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023) Whose Opinions Do Language Models Reflect? PDF Shibani Santurkar, Esin Durmus, Faisal Ladhak, Cinoo Lee, Percy Liang, Tatsunori Hashimoto International Conference on Machine Learning (ICML 2023, oral) Foundation Models and Fair Use PDF Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A Lemley, Percy Liang Journal of Machine Learning Research (JMLR 2024) Navigating the Grey Area: Expressions of Overconfidence and Uncertainty in Language Models PDF Kaitlyn Zhou, Dan Jurafsky, Tatsunori Hashimoto Conference on Empirical Methods in Natural Language Processing (EMNLP 2023) Benchmarking Large Language Models for News Summarization PDF Tianyi Zhang, Faisal Ladhak, Esin Durmus, Percy Liang, Kathleen McKeown, Tatsunori B Hashimoto Transactions of the Association of Computational Linguistics (TACL, presented at EMNLP 2023) Tracing and Removing Data Errors in Natural Language Generation Datasets PDF Faisal Ladhak, Esin Durmus, Tatsunori Hashimoto Annual Meeting of the Association of Computational Linguistics (ACL 2023) Privacy-Preserving Domain Adaptation of Semantic Parsers PDF Fatemehsadat Mireshghallah, Richard Shin, Yu Su, Tatsunori Hashimoto, Jason Eisner ArXiv preprint Contrastive decoding: Open-ended text generation as optimization PDF Xiang Lisa Li, Ari Holtzman, Daniel Fried, Percy Liang, Jason Eisner, Tatsunori Hashimoto, Luke Zettlemoyer, Mike Lewis ArXiv preprint Diffusion-LM Improves Controllable Text Generation PDF Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B Hashimoto Advances in Neural Information Processing Systems 31 (NeurIPS 2022) TempLM: Distilling Language Models into Template-Based Generators PDF Tianyi Zhang, Mina Lee, Lisa Li, Ende Shen, Tatsunori B Hashimoto ArXiv preprint Emergent abilities of large language models PDF Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus Transactions on Machine Learning Research (2022) Jury learning: Integrating dissenting voices into machine learning models PDF Mitchell Gordon, Michelle Lam, Joon Park, Kayur Patel, Jeff Hancock, Tatsunori B Hashimoto, Michael Bernstein Conference on Human Factors in Computing Systems (CHI 2022, Best paper) Spurious Correlations in Reference-Free Evaluation of Text Generation PDF Esin Durmus, Faisal Ladhak, Tatsunori B Hashimoto Annual Meeting of the Association of Computational Linguistics (ACL 2022) Large Language Models Can Be Strong Differentially Private Learners PDF Xuechen Li, Florian Tramer, Percy Liang, Tatsunori B Hashimoto International Conference on Learning Representations (ICLR 2022 Oral) Language Modeling via Stochastic Processes PDF Rose E Wang, Esin Durmus, Noah Goodman, Tatsunori B Hashimoto International Conference on Learning Representations (ICLR 2022 Oral) On the opportunities and risks of foundation models PDF Rishi Bommasani [.. alphabetical authors ..] Tatsunori Hashimoto [...] ArXiv preprint Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions PDF Dorottya Demszky, Jing Liu, Zid Mancenido, Julie Cohen, Heather Hill, Dan Jurafsky, Tatsunori B Hashimoto Annual Meeting of the Association of Computational Linguistics (ACL 2020) DReCa: A general task augmentation strategy for few-shot natural language inference PDF Shikhar Murty, Tatsunori B Hashimoto, Christopher D Manning Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2021) On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies PDF Tianyi Zhang, Tatsunori B Hashimoto Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2021) The Disagreement Deconvolution: Bringing Machine Learning Performance Metrics In Line With Reality PDF Mitchell L Gordon, Kaitlyn Zhou, Kayur Patel, Tatsunori B Hashimoto, Michael S Bernstein Conference on Human Factors in Computing Systems (CHI 2021) Improved Natural Language Generation via Loss Truncation PDF Daniel Kang, Tatsunori B Hashimoto Annual Meeting of the Association of Computational Linguistics (ACL 2020) Learning Autocomplete Systems as a Communication Game PDF Mina Lee, Tatsunori B Hashimoto, Percy Liang Emergent Communication Workshop at Neural Information Processing Systems (NeurIPS 2019) Distributionally Robust Language Modeling PDF Yonatan Oren*, Shiori Sagawa *, Tatsunori B Hashimoto *, Percy Liang Empirical Methods in Natural Language Processing (EMNLP 2019) Unifying Human and Statistical Evaluation for Natural Language Generation PDF Tatsunori B Hashimoto*, Hugh Zhang*, Percy Liang Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2019) A Retrieve-and-Edit Framework for Predicting Structured Outputs PDF Tatsunori B Hashimoto, Kelvin Guu, Yonatan Oren, Percy Liang Advances in Neural Information Processing Systems 31 (NeurIPS 2018, Oral) Generating Sentences by Editing Prototypes PDF Kelvin Guu*, Tatsunori B Hashimoto*, Yonatan Oren, Percy Liang Transactions of the Association of Computational Linguistics (TACL, presented at ACL 2018) Continuous representations and models from random walk diffusion limits PDF Tatsunori B Hashimoto PhD Thesis, MIT CSAIL, 2016 Word embeddings as metric recovery in semantic spaces PDF Tatsunori B Hashimoto, David Alvarez-Melis, Tommi S Jaakkola Transactions of the Association for Computational Linguistics 4 (TACL, presented at ACL 2016) Inferring Multidimensional Rates of Aging from Cross-Sectional Data PDF Emma Pierson*, Pang Wei Koh *, Tatsunori B Hashimoto *, Daphne Koller, Jure Lesokevic, Nicholas Eriksson, Percy Liang 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019) Continuous representations and models from random walk diffusion limits PDF Tatsunori B Hashimoto PhD Thesis, MIT CSAIL, 2016 Learning Population-Level Diffusions with Generative RNNs PDF Tatsunori B Hashimoto, David Gifford, Tommi S Jaakkola Proceedings of the 33rd International Conference on Machine Learning (ICML 2016) A synergistic DNA logic predicts genome-wide chromatin accessibility PDF Tatsunori B Hashimoto*, Richard I Sherwood*, Daniel D Kang*, Nisha Rajagopal, Amira A Barkal, Haoyang Zeng, Bart JM Emons, Sharanya Srinivasan, Tommi S Jaakkola, David K Gifford Genome research (2016) Cas9 Functionally Opens Chromatin PDF Amira A Barkal, Sharanya Srinivasan, Tatsunori B Hashimoto, David K Gifford, Richard I Sherwood PloS One (2016) Cloning-free CRISPR PDF Mandana Arbab, Sharanya Srinivasan, Tatsunori B Hashimoto, Niels Geijsen, Richard I Sherwood Stem cell reports (2015) GERV: a statistical method for generative evaluation of regulatory variants for transcription factor binding PDF Haoyang Zeng, Tatsunori B Hashimoto, Daniel D Kang, David K Gifford Bioinformatics (2015) Long-term persistence and development of induced pancreatic beta cells generated by lineage conversion of acinar cells PDF Weida Li, Claudia Cavelti-Weder, Yinying Zhang, Kendell Clement, Scott Donovan, Gabriel Gonzalez, Jiang Zhu, Marianne Stemann, Ke Xu, Tatsunori B Hashimoto, Takatsugu Yamada, Mio Nakanishi, Yuemei Zhang, Samuel Zeng, David Gifford, Alexander Meissner, Gordon Weir, Qiao Zhou Nature Biotechnology (2014) Universal count correction for high-throughput sequencing PDF Tatsunori B Hashimoto, Matthew D Edwards, David K Gifford PLoS computational biology (2014) Discovery of directional and nondirectional pioneer transcription factors by modeling DNase profile magnitude and shape PDF Richard I Sherwood *, Tatsunori B Hashimoto *, Charles W O'donnell *, Sophia Lewis, Amira A Barkal, John Peter Van Hoff, Vivek Karun, Tommi S Jaakkola, David K Gifford Nature Biotechnology (2014) Quantifying condition-dependent intracellular protein levels enables high-precision fitness estimates PDF Kerry A Geiler-Samerotte, Tatsunori B Hashimoto, Michael F Dion, Bogdan A Budnik, Edoardo M Airoldi, D Allan Drummond PloS one (2013) Lineage-based identification of cellular states and expression programs PDF Tatsunori B Hashimoto, Tommi S Jaakkola, Richard Sherwood, Esteban O. Mazzoni, Hynek Wichterle, David Gifford Bioinformatics (2012) Finding drug discovery rules of thumb with bump hunting PDF Tatsunori B Hashimoto, Matthew Segall Proceedings of the ACS (2010) BFL: a node and edge betweenness based fast layout algorithm for large scale networks. PDF Tatsunori B Hashimoto, Masao Nagasaki, Kaname Kojima, Satoru Miyano BMC bioinformatics (2009) TeachingCS336 (Spring 2024): Language Modeling from Scratch CS224n (Winter 2024): Natural Language Processing with Deep Learning CS324 (Winter 2023): Advances in Foundation Models CS324 (Winter 2022): Large Language Models CS329D (Fall 2021, Spring 2021): Machine Learning Under Distribution Shifts CS221 (Winter 2021): Artificial Intelligence: Principles and Techniques Former AdviseesEsin Durmus (2021-2023) SAIL Postdoc (w/ Dan Jurafsky), now at Anthropic. Niladri Chatterji (2021-2023) SAIL Postdoc (w/ Percy Liang), now at Meta Shibani Santurkar (2021-2023) Postdoc (w/ Percy Liang and Tengyu Ma), now at OpenAI. Daniel Kang (2021-2022) Graduate Student (w/ Matei Zaharia and Peter Bailis), now assistant prof at UIUC. Ishaan Gulrajani (2021-2022) Graduate Student (on leave), at OpenAI Xuechen Li (2021-2024) Graduate Student (w/ Carlos Guestrin), now at X.ai Rohan Taori (2021-2024) Graduate Student, now at Anthropic Resume
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Tatsunori Hashimoto
thashim [AT] stanford.edu
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