1 citations · 1 across the 6 of their papers we have counts for
7 papers
ESCRAG-R1: Retrieval-Augmented Reinforcement Learning for Emotional Support Conversation
Weichu Liu, Yuxuan Hu, Yirong Sun +6
Emotional Support Conversation (ESC) systems aim to provide holistic support by balancing professional therapeutic competence with natural empathy. However, existing methods strugg…
MM-THEBench: Do Reasoning MLLMs Think Reasonably?
Zhidian Huang, Zijun Yao, Ji Qi +7
Recent advances in multimodal large language models (MLLMs) mark a shift from non-thinking models to post-trained reasoning models capable of solving complex problems through think…
LongEmotion: Measuring Emotional Intelligence of Large Language Models in Long-Context Interaction
Weichu Liu, Jing Xiong, Yuxuan Hu +10
Large language models (LLMs) have made significant progress in Emotional Intelligence (EI) and long-context modeling. However, existing benchmarks often overlook the fact that emot…
Cross-Task Experiential Learning on LLM-based Multi-Agent Collaboration
Yilong Li, Chen Qian, Yu Xia +12
Large Language Model-based multi-agent systems (MAS) have shown remarkable progress in solving complex tasks through collaborative reasoning and inter-agent critique. However, exis…
How do Transformers Learn Implicit Reasoning?
Jiaran Ye, Zijun Yao, Zhidian Huang +8
Recent work suggests that large language models (LLMs) can perform multi-hop reasoning implicitly -- producing correct answers without explicitly verbalizing intermediate steps --…
ReaRAG: Knowledge-guided Reasoning Enhances Factuality of Large Reasoning Models with Iterative Retrieval Augmented Generation
Zhicheng Lee, Shulin Cao, Jinxin Liu +5
Large Reasoning Models (LRMs) exhibit remarkable reasoning abilities but rely primarily on parametric knowledge, limiting factual accuracy. While recent works equip reinforcement l…
SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation
Zijun Yao, Weijian Qi, Liangming Pan +5
This paper introduces Self-aware Knowledge Retrieval (SeaKR), a novel adaptive RAG model that extracts self-aware uncertainty of LLMs from their internal states. SeaKR activates re…