2 papers
cs.AI2026
SAGE: Multi-Agent Self-Evolution for LLM Reasoning
Yulin Peng, Xinxin Zhu, Chenxing Wei +4
Reinforcement learning with verifiable rewards improves reasoning in large language models (LLMs), but many methods still rely on large human-labeled datasets. While self-play redu…
cs.CV2025
SceneRAG: Scene-level Retrieval-Augmented Generation for Video Understanding
Nianbo Zeng, Haowen Hou, Fei Richard Yu +2
Despite recent advances in retrieval-augmented generation (RAG) for video understanding, effectively understanding long-form video content remains underexplored due to the vast sca…