most citedSWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution

2 citations · 4 across the 10 of their papers we have counts for

collaborators

13 papers

cs.CL20261 cited

Reasoning in Trees: Improving Retrieval-Augmented Generation for Multi-Hop Question Answering

Yuling Shi, Maolin Sun, Zijun Liu +4

Retrieval-Augmented Generation (RAG) has demonstrated significant effectiveness in enhancing large language models (LLMs) for complex multi-hop question answering (QA). For multi-h…

cs.LG2026

Fed-SE: Federated Self-Evolution for Privacy-Constrained Multi-Environment LLM Agents

Xiang Chen, Yuling Shi, Qizhen Lan +4

LLM agents are widely deployed in complex interactive tasks, yet privacy constraints often preclude centralized optimization and co-evolution across dynamic environments. Despite t…

cs.CV2025

Analyzing the Mechanism of Attention Collapse in VGGT from a Dynamics Perspective

Huan Li, Longjun Luo, Yuling Shi +1

Visual Geometry Grounded Transformer (VGGT) delivers state-of-the-art feed-forward 3D reconstruction, yet its global self-attention layer suffers from a drastic collapse phenomenon…

cs.CV2025

GraphGeo: Multi-Agent Debate Framework for Visual Geo-localization with Heterogeneous Graph Neural Networks

Heng Zheng, Yuling Shi, Xiaodong Gu +6

Visual geo-localization requires extensive geographic knowledge and sophisticated reasoning to determine image locations without GPS metadata. Traditional retrieval methods are con…

cs.GR2025

Empowering LLMs with Structural Role Inference for Zero-Shot Graph Learning

Heng Zhang, Jing Liu, Jiajun Wu +8

Large Language Models have emerged as a promising approach for graph learning due to their powerful reasoning capabilities. However, existing methods exhibit systematic performance…

cs.CV2025

Progressive Supernet Training for Efficient Visual Autoregressive Modeling

Xiaoyue Chen, Yuling Shi, Kaiyuan Li +5

Visual Auto-Regressive (VAR) models significantly reduce inference steps through the "next-scale" prediction paradigm. However, progressive multi-scale generation incurs substantia…