activity
20192026
most citedText Compression-aided Transformer Encoding

51 citations · 84 across the 12 of their papers we have counts for

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16 papers · 1 filter

cs.CL2026

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…

cs.CL2026

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…

cs.CL2025

From Perception to Reasoning: Deep Thinking Empowers Multimodal Large Language Models

Wenxin Zhu, Andong Chen, Yuchen Song +4

With the remarkable success of Multimodal Large Language Models (MLLMs) in perception tasks, enhancing their complex reasoning capabilities has emerged as a critical research focus…

cs.CL2025

Lost in Benchmarks? Rethinking Large Language Model Benchmarking with Item Response Theory

Hongli Zhou, Hui Huang, Ziqing Zhao +10

The evaluation of large language models (LLMs) via benchmarks is widespread, yet inconsistencies between different leaderboards and poor separability among top models raise concern…

cs.CL20221 cited

Document-Level Relation Extraction with Sentences Importance Estimation and Focusing

Wang Xu, Kehai Chen, Lili Mou +1

Document-level relation extraction (DocRE) aims to determine the relation between two entities from a document of multiple sentences. Recent studies typically represent the entire…

cs.CL202151 cited

Text Compression-aided Transformer Encoding

Zuchao Li, Zhuosheng Zhang, Hai Zhao +4

Text encoding is one of the most important steps in Natural Language Processing (NLP). It has been done well by the self-attention mechanism in the current state-of-the-art Transfo…