collaborators

7 papers

cs.CV2026

Forged Peer Judgments Mislead Multimodal LLM Judge Panels: Source-Blind Anchoring and Panel-Consensus Verification

Yang Shu

Multimodal LLM judge panels can cross-reference peers, but a quoted peer judgment may itself be untrusted. We expose source-blind anchoring as a text-level attack surface in vision…

cs.CL2026

Faster but Different: Diagnosing and Controlling Content Drift in Accelerated Multimodal Diffusion Language Models

Yaoxuan Dou, Yang Shu

Training-free acceleration makes diffusion-based multimodal large language models (dMLLMs) more deployable, but it may silently change generated content. We study this serving-time…

cs.AI2026

Agentic Retrieval-Augmented Generation for Financial Document Question Answering

Yang Shu, Yingmin Liu, Zequn Xie

Financial document question answering (QA) demands complex multi-step numerical reasoning over heterogeneous evidence--structured tables, textual narratives, and footnotes--scatter…

cs.AI2026

Numbers Beat Words: A Rigorous On-Premise Benchmark for Coupled MIMO Controller Tuning

Jiaxuan Chen, Haonan Li, Yang Shu

Tuning controllers for strongly coupled multi-input multi-output (MIMO) processes is difficult because decentralized auto-tuning ignores loop interaction and local optimization is…

cs.CL2026

ConflictRAG: Detecting and Resolving Knowledge Conflicts in Retrieval Augmented Generation

Chenyu Wang, Yueyuan Li, Yingmin Liu +1

Retrieval-Augmented Generation (RAG) systems implicitly assume mutual consistency among retrieved documents -- an assumption that frequently fails in practice. We present ConflictR…

cs.AI2026

CyberCorrect: A Cybernetic Framework for Closed-Loop Self-Correction in Large Language Models

Yuning Wu, Yingmin Liu, Yang Shu

Large language model (LLM) self-correction -- the ability to detect and fix errors in generated outputs -- remains largely ad hoc, relying on generic prompts such as "please recons…