8 papers
TimeChat-Captioner: Scripting Multi-Scene Videos with Time-Aware and Structural Audio-Visual Captions
Linli Yao, Yuancheng Wei, Yaojie Zhang +12
This paper proposes Omni Dense Captioning, a novel task designed to generate continuous, fine-grained, and structured audio-visual narratives with explicit timestamps. To ensure de…
Thinking Without Images: Internalizing Visual Manipulation with On-Policy Self-Distillation
Yishuo Cai, Jiahui Liu, Yuanxin Liu +9
''Thinking with Images'' has emerged as an effective paradigm for fine-grained visual reasoning: by explicitly zooming into relevant regions and reasoning over crops, models can ac…
From Player to Master: Enhancing Test-Time Learning of LLM Agents via Reinforcement Learning over Memory
Yishuo Cai, Xingyu Guo, Xuancheng Huang +8
Large language model (LLM) agents are increasingly deployed in long-running settings where improving through experience at test time becomes important. A common approach is to upda…
VideoReasonBench: Can MLLMs Perform Vision-Centric Complex Video Reasoning?
Yuanxin Liu, Kun Ouyang, Haoning Wu +7
Recent studies have shown that long chain-of-thought (CoT) reasoning can significantly enhance the performance of large language models (LLMs) on complex tasks. However, this benef…
Scaling DPPs for RAG: Density Meets Diversity
Xun Sun, Baiheng Xie, Li Huang +1
Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by grounding generation in external knowledge, yielding relevance responses that are aligned with factual…
M-RAG: Semantic Key-Value Indexing for Retrieval-Augmented Generation
Xu Sun, Sun Xu, Tongkai Xu +4
Retrieval-augmented generation (RAG) turns external documents into evidence for large language models. In practice, this is also a data access problem: a system must decide what to…