Meng Fang

Mutual Information Dynamics Learning: A New Paradigm for Unsupervised Reinforcement Learning

SafeDialBench: A Fine-Grained Safety Evaluation Benchmark for Large Language Models in Multi-Turn Dialogues with Diverse Jailbreak Attacks

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages

F1-Reasoner: Synthesizing Verifiable Reasoning Data From Formal Math Statements

Automotive-ENV: Benchmarking Multimodal Agents in Vehicle Interface Systems

Infinity Parser: Layout Aware Reinforcement Learning for Scanned Document Parsing

UniVid: The Open-Source Unified Video Model

ParaRater: Enhancing Cross-Lingual Transfer in Large Langauge Models with Meta-Learning

Think you have Solved Commonsense Reasoning? Try HellaswagUltra

MEAL: A Benchmark for Continual Multi-Agent Reinforcement Learning

Distill Not Only Data but Also Rewards: Can Smaller Language Models Surpass Larger Ones?

Can Large Vision-Language Models Refuse Synthetic Images in Geo-localization?

BagelScore: Visual-Language Evaluation Made Easy

Monte Carlo Planning with Large Language Model for Text-Based Game Agents

MuRating: A High Quality Data Selecting Approach to Multilingual Large Language Model Pretraining

Preference Controllable Reinforcement Learning with Advanced Multi-Objective Optimization

Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling

RuAG: Learned-rule-augmented Generation for Large Language Models

Towards Empowerment Gain through Causal Structure Learning in Model-Based Reinforcement Learning

GasketRAG: Systematic Alignment of Large Language Models with Retrievers

HASARD: A Benchmark for Vision-Based Safe Reinforcement Learning in Embodied Agents

Customizing Reinforcement Learning Agent with Multi-Objective Preference Control

One Model for All: Multi-Objective Controllable Language Models

MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math Data

GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

Assessing Vulnerabilities of Large Language Models to Social Bias Attacks