2 citations · 3 across the 7 of their papers we have counts for
4 papers · 1 filter
Context-measure: Contextualizing Metric for Camouflage
Chen-Yang Wang, Ge-Peng Ji, Song Shao +2
Camouflage relies heavily on context, but current metrics used in camouflaged object segmentation ignore contextual cues. We identify two major drawbacks of these metrics: first, t…
GlobalRAG: Enhancing Global Reasoning in Multi-hop Question Answering via Reinforcement Learning
Jinchang Luo, Mingquan Cheng, Fan Wan +7
Reinforcement learning has recently shown promise in improving retrieval-augmented generation (RAG). Despite these advances, its effectiveness in multi-hop question answering (QA)…
Select to Know: An Internal-External Knowledge Self-Selection Framework for Domain-Specific Question Answering
Bolei He, Xinran He, Run Shao +5
Large Language Models (LLMs) perform well in general QA but often struggle in domain-specific scenarios. Retrieval-Augmented Generation (RAG) introduces external knowledge but suff…
Attention Debiasing for Token Pruning in Vision Language Models
Kai Zhao, Wubang Yuan, Yuchen Lin +5
Vision-language models (VLMs) typically encode substantially more visual tokens than text tokens, resulting in significant token redundancy. Pruning uninformative visual tokens is…