2 citations · 2 across the 6 of their papers we have counts for
6 papers
SrDetection: A Self-Referential Framework for Data Leakage Detection in Code Large Language Models
Shuaimin Li, Liyang Fan, Zeyang Li +9
Evaluating code large language models (Code LLMs) requires reliable detection of data leakage, where benchmark performance is artificially inflated by exposure to benchmark data du…
AdaReP:Adaptive Re-Planning under Model Mismatch for Neural World-Model Predictive Control
Yutian Cheng, Xiaojian Ma, Xianhao Wang +6
Neural world models coupled with model predictive control (MPC) replan at every environment step to bound accumulated prediction error, but this incurs substantial computational ov…
CoTJudger: A Graph-Driven Framework for Automatic Evaluation of Chain-of-Thought Efficiency and Redundancy in LRMs
Siyi Li, Jiajun Shi, Shiwen Ni +9
Large Reasoning Models (LRMs) have demonstrated strong performance by producing extended Chain-of-Thought (CoT) traces before answering. However, this paradigm often induces over-r…
Automatic Paper Reviewing with Heterogeneous Graph Reasoning over LLM-Simulated Reviewer-Author Debates
Shuaimin Li, Liyang Fan, Yufang Lin +5
Existing paper review methods often rely on superficial manuscript features or directly on large language models (LLMs), which are prone to hallucinations, biased scoring, and limi…
A Survey on Large Language Model Benchmarks
Shiwen Ni, Guhong Chen, Shuaimin Li +11
In recent years, with the rapid development of the depth and breadth of large language models' capabilities, various corresponding evaluation benchmarks have been emerging in incre…
xJailbreak: Representation Space Guided Reinforcement Learning for Interpretable LLM Jailbreaking
Sunbowen Lee, Shiwen Ni, Chi Wei +7
Safety alignment mechanism are essential for preventing large language models (LLMs) from generating harmful information or unethical content. However, cleverly crafted prompts can…