most citedAssessing Judging Bias in Large Reasoning Models: An Empirical Study

1 citations · 1 across the 3 of their papers we have counts for

collaborators

8 papers

cs.PL2026

MHRC-Bench: A Multilingual Hardware Repository-Level Code Completion benchmark

Qingyun Zou, Jiahao Cui, Nuo Chen +2

Large language models (LLMs) have achieved strong performance on code completion tasks in general-purpose programming languages. However, existing repository-level code completion…

cs.AI2026

PaperDebugger: A Plugin-Based Multi-Agent System for In-Editor Academic Writing, Review, and Editing

Junyi Hou, Andre Lin Huikai, Nuo Chen +2

Large language models are increasingly embedded into academic writing workflows, yet existing assistants remain external to the editor, preventing deep interaction with document st…

cs.CL2025

Beyond Brainstorming: What Drives High-Quality Scientific Ideas? Lessons from Multi-Agent Collaboration

Nuo Chen, Yicheng Tong, Jiaying Wu +5

While AI agents show potential in scientific ideation, most existing frameworks rely on single-agent refinement, limiting creativity due to bounded knowledge and perspective. Inspi…

cs.CY2025

Position: The Current AI Conference Model is Unsustainable! Diagnosing the Crisis of Centralized AI Conference

Nuo Chen, Moming Duan, Andre Huikai Lin +3

Artificial Intelligence (AI) conferences are essential for advancing research, sharing knowledge, and fostering academic community. However, their rapid expansion has rendered the…

cs.CY2025

Towards Evaluting Fake Reasoning Bias in Language Models

Qian Wang, Zhenheng Tang, Zhanzhi Lou +3

Large Reasoning Models (LRMs), evolved from standard Large Language Models (LLMs), are increasingly utilized as automated judges because of their explicit reasoning processes. Yet…

cs.AR2025

HLStrans: Dataset for C-to-HLS Hardware Code Synthesis

Qingyun Zou, Nuo Chen, Yao Chen +2

High-Level Synthesis (HLS) enables hardware design from C/C++ kernels but requires extensive transformations, such as restructuring code, inserting pragmas, adapting data types, an…