ICML Papers
5,975 papers found • Page 38 of 120
Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing
Tianci Liu, Ruirui Li, Zihan Dong et al.
Mitigating Local Cohesion and Global Sparseness in Graph Contrastive Learning with Fuzzy Boundaries
Yuena Lin, Haichun Cai, Jun-Yi Hang et al.
Mitigating Object Hallucination in Large Vision-Language Models via Image-Grounded Guidance
Linxi Zhao, Yihe Deng, Weitong Zhang et al.
MITIGATING OVER-EXPLORATION IN LATENT SPACE OPTIMIZATION USING LES
Omer Ronen, Ahmed Imtiaz Humayun, Richard Baraniuk et al.
Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification
Langzhang Liang, Fanchen Bu, Zixing Song et al.
Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn
Hongyao Tang, Johan Obando-Ceron, Pablo Samuel Castro et al.
MixBridge: Heterogeneous Image-to-Image Backdoor Attack through Mixture of Schrödinger Bridges
Shixi Qin, Zhiyong Yang, Shilong Bao et al.
Mixed-curvature decision trees and random forests
Philippe Chlenski, Quentin Chu, Raiyan Khan et al.
MixMin: Finding Data Mixtures via Convex Minimization
Anvith Thudi, Evianne Rovers, Yangjun Ruan et al.
Mixture of Experts Made Intrinsically Interpretable
Xingyi Yang, Constantin Venhoff, Ashkan Khakzar et al.
Mixture of Experts Provably Detect and Learn the Latent Cluster Structure in Gradient-Based Learning
Ryotaro Kawata, Kohsei Matsutani, Yuri Kinoshita et al.
Mixture of Hidden-Dimensions: Not All Hidden-States’ Dimensions are Needed in Transformer
Yilong Chen, Junyuan Shang, Zhenyu Zhang et al.
Mixture of Lookup Experts
Shibo Jie, Yehui Tang, Kai Han et al.
ML$^2$-GCL: Manifold Learning Inspired Lightweight Graph Contrastive Learning
Jianqing Liang, Zhiqiang Li, Xinkai Wei et al.
MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency
Dongzhi Jiang, Renrui Zhang, Ziyu Guo et al.
MMedPO: Aligning Medical Vision-Language Models with Clinical-Aware Multimodal Preference Optimization
Kangyu Zhu, Peng Xia, Yun Li et al.
MMInference: Accelerating Pre-filling for Long-Context Visual Language Models via Modality-Aware Permutation Sparse Attention
Yucheng Li, Huiqiang Jiang, Chengruidong Zhang et al.
MM-RLHF: The Next Step Forward in Multimodal LLM Alignment
Yi-Fan Zhang, Tao Yu, Haochen Tian et al.
Modalities Contribute Unequally: Enhancing Medical Multi-modal Learning through Adaptive Modality Token Re-balancing
Jie Peng, Jenna Ballard, Mohan Zhang et al.
MODA: MOdular Duplex Attention for Multimodal Perception, Cognition, and Emotion Understanding
Zhicheng Zhang, Wuyou Xia, Chenxi Zhao et al.
Model-Based Exploration in Monitored Markov Decision Processes
Alireza Kazemipour, Matthew Taylor, Michael Bowling
Model Immunization from a Condition Number Perspective
Amber Yijia Zheng, Cedar Site Bai, Brian Bullins et al.
Modeling All-Atom Glycan Structures via Hierarchical Message Passing and Multi-Scale Pre-training
Minghao Xu, Jiaze Song, Keming Wu et al.
Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent
Yongxian Wei, Anke Tang, Li Shen et al.
Models of Heavy-Tailed Mechanistic Universality
Liam Hodgkinson, Zhichao Wang, Michael Mahoney
Model Steering: Learning with a Reference Model Improves Generalization Bounds and Scaling Laws
Xiyuan Wei, Ming Lin, Fanjiang Ye et al.
Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence
Shangbin Feng, Zifeng Wang, Yike Wang et al.
Model Uncertainty Quantification by Conformal Prediction in Continual Learning
Rui Gao, Weiwei Liu
Modified K-means Algorithm with Local Optimality Guarantees
Mingyi Li, Michael R. Metel, Akiko Takeda
Modular Duality in Deep Learning
Jeremy Bernstein, Laker Newhouse
Modularized Self-Reflected Video Reasoner for Multimodal LLM with Application to Video Question Answering
Zihan Song, Xin Wang, Zi Qian et al.
Modulated Diffusion: Accelerating Generative Modeling with Modulated Quantization
Weizhi Gao, Zhichao Hou, Junqi Yin et al.
MODULI: Unlocking Preference Generalization via Diffusion Models for Offline Multi-Objective Reinforcement Learning
Yifu Yuan, Zhenrui Zheng, Zibin Dong et al.
MoEQuant: Enhancing Quantization for Mixture-of-Experts Large Language Models via Expert-Balanced Sampling and Affinity Guidance
Zhixuan Chen, Xing Hu, Dawei Yang et al.
MoE-SVD: Structured Mixture-of-Experts LLMs Compression via Singular Value Decomposition
Wei Li, Lujun Li, Hao Gu et al.
MOGIC: Metadata-infused Oracle Guidance for Improved Extreme Classification
Suchith Chidananda Prabhu, Bhavyajeet Singh, Anshul Mittal et al.
MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition
Sungnyun Kim, Kangwook Jang, Sangmin Bae et al.
MoH: Multi-Head Attention as Mixture-of-Head Attention
Peng Jin, Bo Zhu, Li Yuan et al.
Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts
Xu Liu, Juncheng Liu, Gerald Woo et al.
MoMa: Modulating Mamba for Adapting Image Foundation Models to Video Recognition
Yuhuan Yang, Chaofan Ma, Zhenjie Mao et al.
Momentum-Driven Adaptivity: Towards Tuning-Free Asynchronous Federated Learning
Wenjing Yan, Xiangyu Zhong, Xiaolu Wang et al.
MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking
Sebastian Farquhar, Vikrant Varma, David Lindner et al.
Monte Carlo Tree Diffusion for System 2 Planning
Jaesik Yoon, Hyeonseo Cho, Doojin Baek et al.
Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design
Zhi Zheng, Zhuoliang Xie, Zhenkun Wang et al.
Monte-Carlo Tree Search with Uncertainty Propagation via Optimal Transport
Tuan Dam, Pascal Stenger, Lukas Schneider et al.
MoRAgent: Parameter Efficient Agent Tuning with Mixture-of-Roles
Jing Han, Binwei Yan, Tianyu Guo et al.
More Than Meets the Eye: Enhancing Multi-Object Tracking Even with Prolonged Occlusions
Bishoy Galoaa, Somaieh Amraee, Sarah Ostadabbas
Morse: Dual-Sampling for Lossless Acceleration of Diffusion Models
Chao Li, Jiawei Fan, Anbang Yao
MP-Nav: Enhancing Data Poisoning Attacks against Multimodal Learning
Jingfeng Zhang, Prashanth Krishnamurthy, Naman Patel et al.
MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment
Tianze Wang, Dongnan Gui, Yifan Hu et al.