5 papers
Agentic-R: Learning to Retrieve for Agentic Search
Wenhan Liu, Xinyu Ma, Yutao Zhu +4
Agentic search has recently emerged as a powerful paradigm, where an agent interleaves multi-step reasoning with on-demand retrieval to solve complex questions. Despite its success…
Adversarial Yet Cooperative: Multi-Perspective Reasoning in Retrieved-Augmented Language Models
Can Xu, Lingyong Yan, Jiayi Wu +6
Recent advances in synergizing large reasoning models (LRMs) with retrieval-augmented generation (RAG) have shown promising results, yet two critical challenges remain: (1) reasoni…
Efficient Thought Space Exploration Through Strategic Intervention
Ziheng Li, Hengyi Cai, Xiaochi Wei +4
While large language models (LLMs) demonstrate emerging reasoning capabilities, current inference-time expansion methods incur prohibitive computational costs by exhaustive samplin…
Grounding Long-Context Reasoning with Contextual Normalization for Retrieval-Augmented Generation
Jiamin Chen, Yuchen Li, Xinyu Ma +5
Retrieval-Augmented Generation (RAG) has become an essential approach for extending the reasoning and knowledge capacity of large language models (LLMs). While prior research has p…
VPN: Visual Prompt Navigation
Shuo Feng, Zihan Wang, Yuchen Li +6
While natural language is commonly used to guide embodied agents, the inherent ambiguity and verbosity of language often hinder the effectiveness of language-guided navigation in c…