Ming Yin

Affiliations

Princeton ECE

papers

1,934

total citations

papers (10)

MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI

CVPR 2024arXiv

1,715

citations

Towards Instance-Optimal Offline Reinforcement Learning with Pessimism

NEURIPS 2021arXiv

citations

Near-Optimal Offline Reinforcement Learning via Double Variance Reduction

NEURIPS 2021arXiv

citations

Decoding AI’s Nudge: A Unified Framework to Predict Human Behavior in AI-Assisted Decision Making

AAAI 2024arXiv

citations

Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings

NEURIPS 2021arXiv

citations

Keyframe-oriented Vision Token Pruning: Enhancing Efficiency of Large Vision Language Models on Long-Form Video Processing

ICCV 2025arXiv

citations

Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation

NEURIPS 2023arXiv

citations

Ming Yin

Affiliations

papers (10)

MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI

Towards Instance-Optimal Offline Reinforcement Learning with Pessimism

Near-Optimal Offline Reinforcement Learning via Double Variance Reduction

Decoding AI’s Nudge: A Unified Framework to Predict Human Behavior in AI-Assisted Decision Making

Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings

Keyframe-oriented Vision Token Pruning: Enhancing Efficiency of Large Vision Language Models on Long-Form Video Processing

Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation

K-hop Hypergraph Neural Network: A Comprehensive Aggregation Approach

Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games

Learning the Target Network in Function Space

papers (10)

MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI

Towards Instance-Optimal Offline Reinforcement Learning with Pessimism

Near-Optimal Offline Reinforcement Learning via Double Variance Reduction

Decoding AI’s Nudge: A Unified Framework to Predict Human Behavior in AI-Assisted Decision Making

Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings

Keyframe-oriented Vision Token Pruning: Enhancing Efficiency of Large Vision Language Models on Long-Form Video Processing

Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation

K-hop Hypergraph Neural Network: A Comprehensive Aggregation Approach

Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games

Learning the Target Network in Function Space