Long chain-of-thought reasoning improves vision-language models (VLMs), but it also exposes a temporal grounding failure: as generation unfolds, models may drift from image evidence while reinforcement learning still provides only a final-answer reward. We study this gap through visual revisit, a temporally localized r...
Zhaolu Kang, Tai-Long Luo, Chen-Xin Li et al.· 0 citations
Prospective Multimodal Memory Compilation is proposed, a framework that shifts part of the memory reasoning process from query time to memory consolidation time and improves answer quality and visual evidence recall while reducing query-time token and latency costs.
Jing-Yu Sun, Yang Lin, Yuyang Xue et al.· 1 citation
TrajWiki is proposed, a trajectory-based memory framework for long-horizon conversational agents that improves long-horizon dialogue performance across both open-source and closed-source LLM backbones, while providing greater interpretability and diagnostic visibility into memory evolution, retrieval failures, and answ...
Jingyu Sun, Yuyang Xue, Ming-Yang Li et al.· 0 citations
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