1 citations · 2 across the 4 of their papers we have counts for
9 papers · 1 filter
CE-RM: A Pointwise Generative Reward Model Optimized via Two-Stage Rollout and Unified Criteria
Xinyu Hu, Yancheng He, Weixun Wang +6
Automatic evaluation is crucial yet challenging for open-ended natural language generation, especially when rule-based metrics are infeasible. Compared with traditional methods, th…
SCOPE: Intrinsic Semantic Space Control for Mitigating Copyright Infringement in LLMs
Zhenliang Zhang, Xinyu Hu, Xiaojun Wan
Large language models sometimes inadvertently reproduce passages that are copyrighted, exposing downstream applications to legal risk. Most existing studies for inference-time defe…
CFunModel: A "Funny" Language Model Capable of Chinese Humor Generation and Processing
Zhenghan Yu, Xinyu Hu, Xiaojun Wan
Humor plays a significant role in daily language communication. With the rapid development of large language models (LLMs), natural language processing has made significant strides…
Exploring the Multilingual NLG Evaluation Abilities of LLM-Based Evaluators
Jiayi Chang, Mingqi Gao, Xinyu Hu +1
Previous research has shown that LLMs have potential in multilingual NLG evaluation tasks. However, existing research has not fully explored the differences in the evaluation capab…
Aspect-Guided Multi-Level Perturbation Analysis of Large Language Models in Automated Peer Review
Jiatao Li, Yanheng Li, Xinyu Hu +2
We propose an aspect-guided, multi-level perturbation framework to evaluate the robustness of Large Language Models (LLMs) in automated peer review. Our framework explores perturba…
Re-evaluating Automatic LLM System Ranking for Alignment with Human Preference
Mingqi Gao, Yixin Liu, Xinyu Hu +3
Evaluating and ranking the capabilities of different LLMs is crucial for understanding their performance and alignment with human preferences. Due to the high cost and time-consumi…