15 citations · 18 across the 9 of their papers we have counts for
6 papers · 1 filter
CheckRLM: Effective Knowledge-Thought Coherence Checking in Retrieval-Augmented Reasoning
Dingling Xu, Ruobing Wang, Qingfei Zhao +8
Reasoning Language Models (RLMs) have significantly improved performance on complex tasks by extending the reasoning chain. However, these chains are prone to containing factual er…
Ruyi2.5 Technical Report
Huan Song, Shuyu Tian, Qingfei Zhao +5
We present Ruyi2.5, a multimodal familial model built on the AI Flow framework. Extending Ruyi2's "Train Once, Deploy Many" paradigm to the multimodal domain, Ruyi2.5 constructs a…
R-Search: Empowering LLM Reasoning with Search via Multi-Reward Reinforcement Learning
Qingfei Zhao, Ruobing Wang, Dingling Xu +2
Large language models (LLMs) have notably progressed in multi-step and long-chain reasoning. However, extending their reasoning capabilities to encompass deep interactions with sea…
PrefRAG: Preference-Driven Multi-Source Retrieval Augmented Generation
Qingfei Zhao, Ruobing Wang, Yukuo Cen +3
Retrieval-Augmented Generation (RAG) has emerged as a reliable external knowledge augmentation technique to mitigate hallucination issues and parameterized knowledge limitations in…
LongRAG: A Dual-Perspective Retrieval-Augmented Generation Paradigm for Long-Context Question Answering
Qingfei Zhao, Ruobing Wang, Yukuo Cen +4
Long-Context Question Answering (LCQA), a challenging task, aims to reason over long-context documents to yield accurate answers to questions. Existing long-context Large Language…
DeepNote: Note-Centric Deep Retrieval-Augmented Generation
Ruobing Wang, Qingfei Zhao, Yukun Yan +9
Retrieval-Augmented Generation (RAG) mitigates factual errors and hallucinations in Large Language Models (LLMs) for question-answering (QA) by incorporating external knowledge. Ho…