6 papers
Progress-SQL: Improving Reinforcement Learning for Text-to-SQL via Progressive Rewards
Shihao Zhang, Xiaoman Wang, Yuan Liu +2
Reinforcement learning has recently shown promise in improving large language models for Text-to-SQL generation, yet existing methods typically optimize one-shot rewards defined ov…
AutoVQA-G: Self-Improving Agentic Framework for Automated Visual Question Answering and Grounding Annotation
Rongsheng Hu, Runwei Guan, Yicheng Di +2
Manual annotation of high-quality visual question answering with grounding (VQA-G) datasets, which pair visual questions with evidential grounding, is crucial for advancing vision-…
RefereeBench: Are Video MLLMs Ready to be Multi-Sport Referees
Yichen Xu, Yuanhang Liu, Chuhan Wang +5
While Multimodal Large Language Models (MLLMs) excel at generic video understanding, their ability to support specialized, rule-grounded decision-making remains insufficiently expl…
Beyond Transcription: Unified Audio Schema for Perception-Aware AudioLLMs
Linhao Zhang, Yuhan Song, Aiwei Liu +6
Recent Audio Large Language Models (AudioLLMs) exhibit a striking performance inversion: while excelling at complex reasoning tasks, they consistently underperform on fine-grained…
POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs
Haicheng Wang, Yuan Liu, Yikun Liu +9
Multimodal Large Language Models (MLLMs) have recently demonstrated remarkable capabilities in cross-modal understanding and generation. However, the rapid growth of visual token s…
RRM: Robust Reward Model Training Mitigates Reward Hacking
Tianqi Liu, Wei Xiong, Jie Ren +15
Reward models (RMs) play a pivotal role in aligning large language models (LLMs) with human preferences. However, traditional RM training, which relies on response pairs tied to sp…