activity
20222026
most citedHuaTuo: Tuning LLaMA Model with Chinese Medical Knowledge

97 citations · 146 across the 33 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.CL2025

Uncovering the Role of Initial Saliency in U-Shaped Attention Bias: Scaling Initial Token Weight for Enhanced Long-Text Processing

Zewen Qiang, Sendong Zhao, Haochun Wang +2

Large language models (LLMs) have demonstrated strong performance on a variety of natural language processing (NLP) tasks. However, they often struggle with long-text sequences due…

cs.CL2025

MoGU V2: Toward a Higher Pareto Frontier Between Model Usability and Security

Yanrui Du, Fenglei Fan, Sendong Zhao +3

As Large Language Models (LLMs) increasingly permeate human life, their security has emerged as a critical concern, particularly their ability to maintain harmless responses to mal…

cs.CL2025★ 1 cited

Anchoring Refusal Direction: Mitigating Safety Risks in Tuning via Projection Constraint

Yanrui Du, Fenglei Fan, Sendong Zhao +6

Instruction Fine-Tuning (IFT) has been widely adopted as an effective post-training strategy to enhance various abilities of Large Language Models (LLMs). However, prior studies ha…

cs.CL2025

CoCoA: Collaborative Chain-of-Agents for Parametric-Retrieved Knowledge Synergy

Yi Jiang, Sendong Zhao, Jianbo Li +4

Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs), especially for knowledge-intensive tasks. Despite its advantages, current RAG methods often struggle to…

cs.IR2025

GainRAG: Preference Alignment in Retrieval-Augmented Generation through Gain Signal Synthesis

Yi Jiang, Sendong Zhao, Jianbo Li +2

The Retrieval-Augmented Generation (RAG) framework introduces a retrieval module to dynamically inject retrieved information into the input context of large language models (LLMs),…

cs.MA2025

Beyond Frameworks: Unpacking Collaboration Strategies in Multi-Agent Systems

Haochun Wang, Sendong Zhao, Jingbo Wang +3

Multi-agent collaboration has emerged as a pivotal paradigm for addressing complex, distributed tasks in large language model (LLM)-driven applications. While prior research has fo…