16 citations · 17 across the 18 of their papers we have counts for
20 papers
EMIR: Evolution-Aware Memory with Intent-Guided Multi-Round Retrieval
Jinlan Liu, Hongliang Sun, Yong Wang +4
Long-term memory enables large language model (LLM) agents to leverage historical interactions for future tasks. However, existing memory systems struggle to utilize continuously e…
Scientific Image Quality Assessment via Multi-modal Retrieval-Augmented Generation
Yinuo Zhang, Bingshuo Liu, Zhiying Tu +6
This paper proposes a Retrieval-Augmented Generation (RAG) framework for scientific image quality assessment, designed to simultaneously address both the understanding track (SIQA-…
History-Conditioned Joint-Prefix Alignment for Generative Recommendation
Lianjie Li, Zhiying Tu, Bolin Zhang +3
Generative recommendation retrieves items by autoregressively generating semantic identifiers, but beam search may discard a target before its complete identifier is generated. Our…
MADE: Belief-Driven Dual-Agent Coordination for Autonomous Model Deployment
Yicheng Liu, Bolin Zhang, Weiran Liu +4
LLM-based agents now have strong general capabilities. However, they still struggle with domain-specific tasks, motivating the integration of external tools to broaden their capabi…
GARDRec: Decision-Level Graph Grounding for Large Language Model Recommendation
Yong Wang, Hongliang Sun, Jinlan Liu +4
Large language models (LLMs) offer new opportunities for recommendation by interpreting item descriptions, user instructions, and external knowledge through natural-language prompt…
Dual-Path LLM Reasoning for Multimodal Few-Shot Knowledge Graph Completion
Jinlan Liu, Zhiying Tu, Yongchao Xing +5
Knowledge graph completion (KGC) aims to infer missing facts in knowledge graphs (KGs), thereby improving their completeness and supporting downstream intelligent applications. How…
SkillWiki: A Living Knowledge Infrastructure for Agent Skills
Dingcheng Huang, Yuda Ding, Bingshuo Liu +8
While knowledge is managed through Wikipedia and software through GitHub, agent skills still lack an infrastructure for large-scale production, governance, and evolution. SkillWiki…
An Effective Router for Vision-Language Model Selection
Can Wang, Shengwei Wang, Bolin Zhang +2
Vision-language models (VLMs) with varying performance and resource requirements are widely deployed, making it difficult for users to select the most appropriate one among numerou…
Evidence-Based Intelligent Diagnostic and Therapeutic Visualization System with Large Language Models: Multi-Turn Interaction and Multimodal Treatment Plan Generation
Yunhan Wang, Yuda Wang, Zhiying Tu +5
Aim: Existing AI-assisted traditional Chinese medicine diagnostic tools suffer from opaque reasoning processes, passive interaction, and limited treatment plan presentation. This s…
Gradients Must Earn Their Influence: Unifying SFT with Generalized Entropic Objectives
Zecheng Wang, Deyuan Liu, Chunshan Li +5
Standard negative log-likelihood (NLL) for Supervised Fine-Tuning (SFT) applies uniform token-level weighting. This rigidity creates a two-fold failure mode: (i) overemphasizing lo…
Beyond Confidence: The Rhythms of Reasoning in Generative Models
Deyuan Liu, Zecheng Wang, Zhanyue Qin +3
Large Language Models (LLMs) exhibit impressive capabilities yet suffer from sensitivity to slight input context variations, hampering reliability. Conventional metrics like accura…
EchoReview: Learning Peer Review from the Echoes of Scientific Citations
Yinuo Zhang, Dingcheng Huang, Haifeng Suo +9
As the volume of scientific submissions continues to grow rapidly, traditional peer review systems are facing unprecedented scalability pressures, highlighting the urgent need for…
ScEdit: Script-based Assessment of Knowledge Editing
Xinye Li, Zunwen Zheng, Qian Zhang +8
Knowledge Editing (KE) has gained increasing attention, yet current KE tasks remain relatively simple. Under current evaluation frameworks, many editing methods achieve exceptional…
LFTF: Locating First and Then Fine-Tuning for Mitigating Gender Bias in Large Language Models
Zhanyue Qin, Yue Ding, Deyuan Liu +7
Nowadays, Large Language Models (LLMs) have attracted widespread attention due to their powerful performance. However, due to the unavoidable exposure to socially biased data durin…
Mitigating Gender Bias in Code Large Language Models via Model Editing
Zhanyue Qin, Haochuan Wang, Zecheng Wang +6
In recent years, with the maturation of large language model (LLM) technology and the emergence of high-quality programming code datasets, researchers have become increasingly conf…
HBot: A Chatbot for Healthcare Applications in Traditional Chinese Medicine Based on Human Body 3D Visualization
Bolin Zhang, Zhiwei Yi, Jiahao Wang +3
The unique diagnosis and treatment techniques and remarkable clinical efficacy of traditional Chinese medicine (TCM) make it play an important role in the field of elderly care and…
UNO Arena for Evaluating Sequential Decision-Making Capability of Large Language Models
Zhanyue Qin, Haochuan Wang, Deyuan Liu +9
Sequential decision-making refers to algorithms that take into account the dynamics of the environment, where early decisions affect subsequent decisions. With large language model…
Pruning via Merging: Compressing LLMs via Manifold Alignment Based Layer Merging
Deyuan Liu, Zhanyue Qin, Hairu Wang +12
While large language models (LLMs) excel in many domains, their complexity and scale challenge deployment in resource-limited environments. Current compression techniques, such as…
Checkpoint Merging via Bayesian Optimization in LLM Pretraining
Deyuan Liu, Zecheng Wang, Bingning Wang +6
The rapid proliferation of large language models (LLMs) such as GPT-4 and Gemini underscores the intense demand for resources during their training processes, posing significant ch…
A Survey on Data Selection for LLM Instruction Tuning
Bolin Zhang, Jiahao Wang, Qianlong Du +3
Instruction tuning is a vital step of training large language models (LLMs), so how to enhance the effect of instruction tuning has received increased attention. Existing works ind…