15 citations · 15 across the 8 of their papers we have counts for
6 papers · 1 filter
Thinker: Training LLMs in Hierarchical Thinking for Deep Search via Multi-Turn Interaction
Jun Xu, Xinkai Du, Yu Ao +17
Efficient retrieval of external knowledge bases and web pages is crucial for enhancing the reasoning abilities of LLMs. Previous works on training LLMs to leverage external retriev…
RPTS: Tree-Structured Reasoning Process Scoring for Faithful Multimodal Evaluation
Haofeng Wang, Yu Zhang
Large Vision-Language Models (LVLMs) excel in multimodal reasoning and have shown impressive performance on various multimodal benchmarks. However, most of these benchmarks evaluat…
MultiRAG: A Knowledge-guided Framework for Mitigating Hallucination in Multi-source Retrieval Augmented Generation
Wenlong Wu, Haofen Wang, Bohan Li +3
Retrieval Augmented Generation (RAG) has emerged as a promising solution to address hallucination issues in Large Language Models (LLMs). However, the integration of multiple retri…
MemOS: A Memory OS for AI System
Zhiyu Li, Chenyang Xi, Chunyu Li +36
Large Language Models (LLMs) have become an essential infrastructure for Artificial General Intelligence (AGI), yet their lack of well-defined memory management systems hinders the…
KAG-Thinker: Interactive Thinking and Deep Reasoning in LLMs via Knowledge-Augmented Generation
Dalong Zhang, Jun Xu, Jun Zhou +16
In this paper, we introduce KAG-Thinker, which upgrade KAG to a multi-turn interactive thinking and deep reasoning framework powered by a dedicated parameter-light large language m…
ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning
Mingyang Chen, Linzhuang Sun, Tianpeng Li +10
Large Language Models (LLMs) have shown remarkable capabilities in reasoning, exemplified by the success of OpenAI-o1 and DeepSeek-R1. However, integrating reasoning with external…