19 papers · 1 filter
User-Aware Active Knowledge Acquisition for Emotional Support Dialogue
Mufan Xu, Kehai Chen, Jiahao Hu +4
Emotional support plays an important role in dialogue systems, and its success depends on adapting to a user's evolving and implicit needs across multi-turn interactions while leve…
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…
Beyond Token-Level Policy Gradients for Complex Reasoning with Large Language Models
Mufan Xu, Kehai Chen, Xuefeng Bai +4
Existing policy-gradient methods for auto-regressive language models typically select subsequent tokens one at a time as actions in the policy. While effective for many generation…
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…
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…