1 citations · 1 across the 9 of their papers we have counts for
10 papers
GenMem: Generative Symbolic Memory for Self-Evolving Harness
Xinke Jiang, Tao Feng, Weixuan Xu +7
Long-term memory supports the self-evolution of LLM agents by retaining experience and skills across tasks and enabling their retrieval, reuse, and revision in subsequent long-hori…
HPFA: Hypergraph-Based Paired Failure Attribution for LLM Reasoning
Runchuan Zhu, Hongbin Lai, Bowen Jiang +4
Reflection is a powerful mechanism for LLM reasoning, yet its effectiveness hinges on accurately attributing failures to specific reasoning steps, a capability that current models…
Can Induced Emotion Bias LLM Behaviors in Sequential Decision Making?
Minh Khoi Ho, Zihao Zhu, Runchuan Zhu +4
As Large Language Models (LLMs) are increasingly deployed as autonomous agents in high-stakes domains, understanding contextual factors that may modulate their decision-making beco…
An evidence-guided reinforcement learning method to improve psychiatric reasoning in small language models
Xinxin Lin, Guangxin Dai, Yi Zhong +25
Privacy and computational constraints limit the use of large language models in psychiatry, while adapting small language models (SLMs) often requires substantial data and expert a…
EL4NER: Ensemble Learning for Named Entity Recognition via Multiple Small-Parameter Large Language Models
Yuzhen Xiao, Jiahe Song, Yongxin Xu +6
In-Context Learning (ICL) technique based on Large Language Models (LLMs) has gained prominence in Named Entity Recognition (NER) tasks for its lower computing resource consumption…
Evaluating Large Language Model with Knowledge Oriented Language Specific Simple Question Answering
Bowen Jiang, Runchuan Zhu, Jiang Wu +11
We introduce KoLasSimpleQA, the first benchmark evaluating the multilingual factual ability of Large Language Models (LLMs). Inspired by existing research, we created the question…
3DS: Medical Domain Adaptation of LLMs via Decomposed Difficulty-based Data Selection
Hongxin Ding, Yue Fang, Runchuan Zhu +6
Large Language Models(LLMs) excel in general tasks but struggle in specialized domains like healthcare due to limited domain-specific knowledge.Supervised Fine-Tuning(SFT) data con…
Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored Tuning
Yongxin Xu, Ruizhe Zhang, Xinke Jiang +7
Retrieval-Augmented Generation (RAG) offers an effective solution to the issues faced by Large Language Models (LLMs) in hallucination generation and knowledge obsolescence by inco…
KnowPO: Knowledge-aware Preference Optimization for Controllable Knowledge Selection in Retrieval-Augmented Language Models
Ruizhe Zhang, Yongxin Xu, Yuzhen Xiao +5
By integrating external knowledge, Retrieval-Augmented Generation (RAG) has become an effective strategy for mitigating the hallucination problems that large language models (LLMs)…
Few-shots Portrait Generation with Style Enhancement and Identity Preservation
Runchuan Zhu, Naye Ji, Youbing Zhao +1
Nowadays, the wide application of virtual digital human promotes the comprehensive prosperity and development of digital culture supported by digital economy. The personalized port…