most citedMulti-Scale Feature Fusion and Graph Neural Network Integration for Text Classification with Large Language Models

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Circuit-Diff: Factual Edit-based Intervention Method for Localizing Knowledge in Attribution Graphs

Edward G. Friedman, Xiangchen Song

Mechanistic interpretability defines features as the fundamental units of a neural network and circuits as the weighted subgraphs that carry out its computation. Because individual…

cs.CL2025

Parameter-Efficient Fine-Tuning with Differential Privacy for Robust Instruction Adaptation in Large Language Models

Yulin Huang, Yaxuan Luan, Jinxu Guo +2

This study addresses the issues of privacy protection and efficiency in instruction fine-tuning of large-scale language models by proposing a parameter-efficient method that integr…

cs.CL2025★ 1 cited

Multi-Scale Feature Fusion and Graph Neural Network Integration for Text Classification with Large Language Models

Xiangchen Song, Yulin Huang, Jinxu Guo +2

This study investigates a hybrid method for text classification that integrates deep feature extraction from large language models, multi-scale fusion through feature pyramids, and…

cs.CL2025

LLM-Centric RAG with Multi-Granular Indexing and Confidence Constraints

Xiaofan Guo, Yaxuan Luan, Yue Kang +2

This paper addresses the issues of insufficient coverage, unstable results, and limited reliability in retrieval-augmented generation under complex knowledge environments, and prop…

cs.CL2025

Controllable Abstraction in Summary Generation for Large Language Models via Prompt Engineering

Xiangchen Song, Yuchen Liu, Yaxuan Luan +2

This study presents a controllable abstract summary generation method for large language models based on prompt engineering. To address the issues of summary quality and controllab…