collaborators

17 papers

cs.CL2026

SafeReview: Defending LLM-based Review Systems Against Adversarial Hidden Prompts

Yuan Xin, Yixuan Weng, Minjun Zhu +5

As Large Language Models (LLMs) are increasingly integrated into academic peer review, their vulnerability to adversarial hidden prompts, i.e., adversarial instructions embedded in…

cs.AI2026

SafeAgent: A Runtime Protection Architecture for Agentic Systems

Hailin Liu, Eugene Ilyushin, Jie Ni +1

Large language model (LLM) agents are vulnerable to prompt-injection attacks that propagate through multi-step workflows, tool interactions, and persistent context, making input-ou…

cs.LG2026

Hard Negative Sample-Augmented DPO Post-Training for Small Language Models

Haocheng Lu, Minjun Zhu, Henry Yu

Large language models (LLMs) continue to struggle with mathematical reasoning, and common post-training pipelines often reduce each generated solution to a binary outcome: correct…

cs.AI2026

DeepReviewer 2.0: A Traceable Agentic System for Auditable Scientific Peer Review

Yixuan Weng, Minjun Zhu, Qiujie Xie +7

Automated peer review is often framed as generating fluent critique, yet reviewers and area chairs need judgments they can \emph{audit}: where a concern applies, what evidence supp…

cs.CV2026

AutoFigure-Edit: Generating Editable Scientific Illustration

Zhen Lin, Qiujie Xie, Minjun Zhu +10

High-quality scientific illustrations are essential for communicating complex scientific and technical concepts, yet existing automated systems remain limited in editability, styli…

cs.AI2026

AutoFigure: Generating and Refining Publication-Ready Scientific Illustrations

Minjun Zhu, Zhen Lin, Yixuan Weng +6

High-quality scientific illustrations are crucial for effectively communicating complex scientific and technical concepts, yet their manual creation remains a well-recognized bottl…