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GeezerVison is showing proceedings.mlr.press — Proceedings of Machine Learning Research [edit] Volume 328: Third Conference on Parsimony and Learning, 23-26 March 2026, Tübingen, Germany[edit] Editors: Rebekka Burkholz, Shiwei Liu, Saiprasad Ravishankar, William Redman, Wei Huang, Weijie Su, Zhihui Zhu Filter Authors: Filter Titles: Semantic Homogeneity As Demonstration: Batch-Structured Semi-Supervised In-Context Learning for Natural Language Understanding Cheng Chen, Yuangang Pan, Ivor Tsang; Conference on Parsimony and Learning, PMLR 328:1-23 Improving Medical Visual Reinforcement Fine-Tuning via Perception and Reasoning Augmentation Guangjing Yang, ZhangYuan Yu, Ziyuan Qin, Xinyuan Song, Huahui Yi, Qingbo Kang, Jun Gao, Yiyue Li, Chenlin Du, Qicheng Lao; Conference on Parsimony and Learning, PMLR 328:24-41 ROSE: Reordered SparseGPT for More Accurate One-Shot Large Language Models Pruning Mingluo Su, Huan Wang; Conference on Parsimony and Learning, PMLR 328:42-60 AlphaFormer: End-to-End Symbolic Regression of Alpha Factors with Transformers Haotong Huang, Jie Peng, Zezhen Ding, Pingzhi Li, Tianlong Chen; Conference on Parsimony and Learning, PMLR 328:61-82 From sparse recovery to plug-and-play priors, understanding trade-offs for stable recovery with generalized projected gradient descent Ali Joundi, Yann Traonmilin, Jean-François Aujol; Conference on Parsimony and Learning, PMLR 328:83-103 Panza: Investigating the Feasibility of Fully-Local Personalized Text Generation Armand Mihai Nicolicioiu, Eugenia Iofinova, Andrej Jovanovic, Eldar Kurtic, Mahdi Nikdan, Andrei Panferov, Ilia Markov, Nir N Shavit, Dan Alistarh; Conference on Parsimony and Learning, PMLR 328:104-130 Enhancing Low-Cost Video Editing with Lightweight Adaptors and Temporal-Aware Inversion Yangfan He, Sida Li, Jianhui Wang, Xinyuan Song, Kun Li, Xinhang Yuan, Kuan Lu, Menghao Huo, Jingqun Tang, Yi Xin, Jiaqi Chen, Keqin Li, Miao Zhang, Xueqian Wang; Conference on Parsimony and Learning, PMLR 328:131-163 SPIKE: Sparse Koopman Regularization for Physics-Informed Neural Networks Jose Marie Antonio Miñoza; Conference on Parsimony and Learning, PMLR 328:164-191 Cannistraci-Hebb Training with N:M Semi-Structured Sparsity for Pre-Training and Re-Training Jiaqing Lyu, Ruijie Wang, Kangyou Bao, Yingtao Zhang, Carlo Vittorio Cannistraci; Conference on Parsimony and Learning, PMLR 328:192-217 Lattice-Based Vector Quantization for Low-Bit Quantization-Aware Training Rishika Kohli, Soma S Dhavala, Shaifu Gupta, Manoj Singh Gaur; Conference on Parsimony and Learning, PMLR 328:218-241 ShapLoRA: Allocation of Low-rank Adaption on Large Language Models via Shapley Value Inspired Importance Estimation Colin Zhao, Qinghua Yao, Xinyuan Song, Wei Zhu; Conference on Parsimony and Learning, PMLR 328:242-264 LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs Erik Schultheis, Dan Alistarh; Conference on Parsimony and Learning, PMLR 328:265-284 Parameter-Efficient Distributional RL via Normalizing Flows and a Geometry-Aware Cramér Surrogate Simo Alami Chehboune, Rim Kaddah, Marie-Paule CANI, Jesse Read; Conference on Parsimony and Learning, PMLR 328:285-313 Analyzing and Mitigating Model Collapse in Reflow Methods Huminhao Zhu, Fangyikang Wang, Tianyu Ding, Qing Qu, Zhihui Zhu; Conference on Parsimony and Learning, PMLR 328:314-340 Stochastic Unrolled Neural Networks Samar Hadou, Navid NaderiAlizadeh, Alejandro Ribeiro; Conference on Parsimony and Learning, PMLR 328:341-359 Prompt Stability Matters: Evaluating and Optimizing Auto-Generated Prompt in General-Purpose Systems Ke Chen, Xucheng Yu, Yufei Zhou, Haohan Wang; Conference on Parsimony and Learning, PMLR 328:360-374 Symbiotic Cooperation for Web Agents: Harnessing Complementary Strengths of Large and Small LLMs Ruichen Zhang, Mufan Qiu, Zhen Tan, Mohan Zhang, Xiaopeng Lu, Jie Peng, Kaidi Xu, Leandro Z. Agudelo, Peter Zhenghao Qian, Tianlong Chen; Conference on Parsimony and Learning, PMLR 328:375-427 Matrix Sensing with Kernel Optimal Loss: Robustness and Optimization Landscape Xinyuan Song, Ziye Ma; Conference on Parsimony and Learning, PMLR 328:428-500 Pruned Adaptation Modules: A Simple yet Strong Baseline for Continual Foundation Models Elif Ceren Gok Yildirim, Murat Onur Yildirim, Joaquin Vanschoren; Conference on Parsimony and Learning, PMLR 328:501-515 Token-Aware Representation Augmentation for Fine-Grained Semi-Supervised Learning Hongyang He, Yan Zhong, Xinyuan Song, Daizong Liu, Victor Sanchez; Conference on Parsimony and Learning, PMLR 328:516-528 MMA:Benchmarking Multi-ModalLarge Language Models in Ambiguity Contexts Ru Wang, Selena Song, Yuquan Wang, Liang Ding, Mingming Gong, Yusuke Iwasawa, Yutaka Matsuo, Jiaxian Guo; Conference on Parsimony and Learning, PMLR 328:529-551 Optimal $k$-Discretization Learning Tong Wang, Zhangyang Wang; Conference on Parsimony and Learning, PMLR 328:552-564 Deep Neural Regression Collapse Akshay Rangamani, Altay Unal; Conference on Parsimony and Learning, PMLR 328:565-581 Beyond In-Distribution Success: Scaling Curves of CoT Granularity for Language Model Generalization Ru Wang, Wei Huang, Selena Song, Haoyu Zhang, Qian Niu, Yusuke Iwasawa, Yutaka Matsuo, Jiaxian Guo; Conference on Parsimony and Learning, PMLR 328:582-611 Learning in the Null Space: Small Singular Values for Continual Learning Cuong Anh Pham, Praneeth Vepakomma, Samuel Horváth; Conference on Parsimony and Learning, PMLR 328:612-628 (PASS) Visual Prompt Locates Good Structure Sparsity through a Recurrent HyperNetwork Tianjin Huang, Yong Tao, Meng Fang, Li Shen, Fan Liu, Yulong Pei, Mykola Pechenizkiy, Tianlong Chen; Conference on Parsimony and Learning, PMLR 328:629-643 Sparsity-Aware Prompt Tuning: A Simple and Effective Way to Fine-tune High-Sparsity LLMs Yuxin Zhang, Weizhong Huang, Yuexiao Ma, Yunshan Zhong, Xiawu Zheng, Rongrong Ji; Conference on Parsimony and Learning, PMLR 328:644-657 Scalable LLM Reasoning Acceleration with Low-rank Distillation Harry Dong, Bilge Acun, Beidi Chen, Yuejie Chi; Conference on Parsimony and Learning, PMLR 328:658-675 FocusDC: Real-World Scene Infusion for Robust Dataset Condensation Youbing Hu, Yun Cheng, Olga Saukh, Firat Ozdemir, Anqi Lu, Zhiqiang Cao, Min Zhang, Zhijun Li; Conference on Parsimony and Learning, PMLR 328:676-697 ERC-SVD: Error-Controlled SVD for Large Language Model Compression Haolei Bai, Siyong Jian, Tuo Liang, Yu Yin, Huan Wang; Conference on Parsimony and Learning, PMLR 328:698-719 Can Less Be More? Benchmarking Lightweight Models Against State-of-the-Art Deep Learning Architectures for Deployable Seizure Detection Isaiah Essien, Donna-lee Ginsberg, Jesse Thornburg; Conference on Parsimony and Learning, PMLR 328:720-734 Beyond Greedy Decoding: Model-Specific Strategy Selection via Multi-faceted Uncertainty Decomposition Kwangje Baeg, Yubin Lim; Conference on Parsimony and Learning, PMLR 328:735-755 Superclass-Guided Representation Disentanglement for Spurious Correlation Mitigation Chenruo Liu, Hongjun Liu, Zeyu Lai, Yiqiu Shen, Chen Zhao, Qi Lei; Conference on Parsimony and Learning, PMLR 328:756-794 Dynamic SFT with Structured Measurements: Fast Queries, Fast Updates, Provable Guarantees Yang Cao, Zhao Song; Conference on Parsimony and Learning, PMLR 328:795-825 Byzantine-Robust Optimization under $(L_0,L_1)$-Smoothness Arman Bolatov, Samuel Horváth, Martin Takáč, Eduard Gorbunov; Conference on Parsimony and Learning, PMLR 328:826-854 Effective Learning for Small Reasoning Models: An Empirical Study on 0.5B Reasoning LLMs Xialie Zhuang, Peixian MA, Zhikai Jia, Zane Cao, Shiwei Liu; Conference on Parsimony and Learning, PMLR 328:855-869 Learning of Discretized LSTMs Nikolaus Kopp, Franz Pernkopf; Conference on Parsimony and Learning, PMLR 328:870-880 GRAIL: Post-hoc Compensation by Linear Reconstruction for Compressed Networks Wenwu Tang, Dong Wang, Lothar Thiele, Olga Saukh; Conference on Parsimony and Learning, PMLR 328:881-895 Trainable Bitwise Soft Quantization for Input Feature Compression Karsten Schrödter, Jan Stenkamp, Nina Herrmann, Fabian Gieseke; Conference on Parsimony and Learning, PMLR 328:896-920 A Stein identity for $q$-Gaussians with bounded support Sophia Sklaviadis, Thomas Möllenhoff, Mario A. T. Figueiredo, Andre Martins, Mohammad Emtiyaz Khan; Conference on Parsimony and Learning, PMLR 328:921-939 Concept based Ambiguity Resolution in LLMs Zhibo Hu, Chen Wang, Yanfeng Shu, Hye-young Paik, Liming Zhu; Conference on Parsimony and Learning, PMLR 328:940-956 Simplex Deep Linear Discriminant Analysis Maxat Tezekbayev, Arman Bolatov, Zhenisbek Assylbekov; Conference on Parsimony and Learning, PMLR 328:957-967 Emergence of Auditory Receptive Fields based on Surprise Yashaswin Yashaswini, Sneha Dash, Sharba Bandyopadhyay; Conference on Parsimony and Learning, PMLR 328:968-988 KNIGHT: Knowledge Graph-Driven Multiple-Choice Question Generation with Adaptive Hardness Calibration Mohammad Amanlou, Erfan Shafiee Moghaddam, Mahdi Nouri, Yasaman Amou Jafary, Farhan Farsi, Behnam Bahrak; Conference on Parsimony and Learning, PMLR 328:989-1024 Teaching LLMs According to Their Aptitude: Adaptive Switching Between CoT and TIR for Mathematical Problem Solving Xin Xu, Yan Xu, Tianhao Chen, Yuchen Yan, Chengwu Liu, Zaoyu Chen, Yufei Wang, Yichun Yin, Yasheng Wang, Qun Liu, Lu Yin; Conference on Parsimony and Learning, PMLR 328:1025-1048 Sparse Mixture-of-Experts for Compositional Generalization: Empirical Evidence and Theoretical Foundations of Optimal Sparsity Jinze Zhao, Peihao Wang, Junjie Yang, Ruisi Cai, Gaowen Liu, Jayanth Srinivasa, Ramana Rao Kompella, Yingbin Liang, Zhangyang Wang; Conference on Parsimony and Learning, PMLR 328:1049-1071 Data-Efficient and Robust Trajectory Generation through Pathlet Dictionary Learning yuanbo tang, Yan Tang, Zihui Zhao, Zixuan Zhang, Yang Li; Conference on Parsimony and Learning, PMLR 328:1072-1089 SonoEdit: Null-Space Constrained Knowledge Editing for Pronunciation Correction in LLM-Based TTS Ayush Pratap Singh, Harshit Singh, Nityanand Mathur, Akshat Mandloi, Sudarshan Kamath; Conference on Parsimony and Learning, PMLR 328:1090-1100 FLIPR: FLexible and Interpretable Prediction Regions for time series Eshant English, Christoph Lippert; Conference on Parsimony and Learning, PMLR 328:1101-1111 Enhancing Long-Context Inference with Context-Position Duo-Mixture Zhenyu Zhang, Sharath Nittur Sridhar, Zhangyang Wang, Souvik Kundu; Conference on Parsimony and Learning, PMLR 328:1112-1124 Generalized Radius and Integrated Codebook Transforms for Differentiable Vector Quantization Haochen You, Heng Zhang, Hongyang He, Yuqi Li, Baojing Liu; Conference on Parsimony and Learning, PMLR 328:1125-1160 Selective Collaboration for Robust Federated Learning Nazarii Tupitsa, Samuel Horváth, Martin Takáč, Eduard Gorbunov; Conference on Parsimony and Learning, PMLR 328:1161-1194 What Scalable Second-Order Information Knows for Pruning at Initialization Ivo Gollini Navarrete, Nicolas Mauricio Cuadrado, Martin Takáč, Samuel Horváth; Conference on Parsimony and Learning, PMLR 328:1195-1227 Efficient Temporal Consistency in Diffusion-Based Video Editing with Adaptor Modules: A Theoretical Framework Xinyuan Song, Yangfan He, Sida Li, Jianhui Wang, Hongyang He, Xinhang Yuan, Ruoyu Wang, Jiaqi Chen, Keqin Li, Kuan Lu, Menghao Huo, Ziqian Bi, Binxu Li, Pei Liu; Conference on Parsimony and Learning, PMLR 328:1228-1250 subscribe via RSS |
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