6 papers
Reasoning Model Is Superior LLM-Judge, Yet Suffers from Biases
Hui Huang, Xuanxin Wu, Muyun Yang +1
This paper presents the first systematic comparison investigating whether Large Reasoning Models (LRMs) are superior judges to non-reasoning LLMs. Our empirical analysis yields fou…
Long-form RewardBench: Evaluating Reward Models for Long-form Generation
Hui Huang, Yancheng He, Wei Liu +7
The widespread adoption of reinforcement learning-based alignment highlights the growing importance of reward models. Various benchmarks have been built to evaluate reward models i…
Toward Robust LLM-Based Judges: Taxonomic Bias Evaluation and Debiasing Optimization
Hongli Zhou, Hui Huang, Rui Zhang +5
Large language model (LLM)-based judges are widely adopted for automated evaluation and reward modeling, yet their judgments are often affected by judgment biases. Accurately evalu…
RM-Distiller: Exploiting Generative LLM for Reward Model Distillation
Hongli Zhou, Hui Huang, Wei Liu +8
Reward models (RMs) play a pivotal role in aligning large language models (LLMs) with human preferences. Due to the difficulty of obtaining high-quality human preference annotation…
DiVA: Fine-grained Factuality Verification with Agentic-Discriminative Verifier
Hui Huang, Muyun Yang, Yuki Arase
Despite the significant advancements of Large Language Models (LLMs), their factuality remains a critical challenge, fueling growing interest in factuality verification. Existing r…
Legal Fact Prediction: The Missing Piece in Legal Judgment Prediction
Junkai Liu, Yujie Tong, Hui Huang +7
Legal judgment prediction (LJP), which enables litigants and their lawyers to forecast judgment outcomes and refine litigation strategies, has emerged as a crucial legal NLP task.…