6 papers
Neuron-Aware Data Selection In Instruction Tuning For Large Language Models
Xin Chen, Junchao Wu, Shu Yang +6
Instruction Tuning (IT) has been proven to be an effective approach to unlock the powerful capabilities of large language models (LLMs). Recent studies indicate that excessive IT d…
ToolRM: Towards Agentic Tool-Use Reward Modeling
Renhao Li, Jianhong Tu, Yang Su +6
Reward models (RMs) play a critical role in aligning large language models (LLMs) with human preferences. Yet in the domain of tool learning, the lack of RMs specifically designed…
Are Large Reasoning Models Good Translation Evaluators? Analysis and Performance Boost
Runzhe Zhan, Zhihong Huang, Xinyi Yang +3
Recent advancements in large reasoning models (LRMs) have introduced an intermediate "thinking" process prior to generating final answers, improving their reasoning capabilities on…
Exploring the Impact of Personality Traits on LLM Bias and Toxicity
Shuo Wang, Renhao Li, Xi Chen +3
With the different roles that AI is expected to play in human life, imbuing large language models (LLMs) with different personalities has attracted increasing research interests. W…
HiMATE: A Hierarchical Multi-Agent Framework for Machine Translation Evaluation
Shijie Zhang, Renhao Li, Songsheng Wang +3
The advancement of Large Language Models (LLMs) enables flexible and interpretable automatic evaluations. In the field of machine translation evaluation, utilizing LLMs with transl…
RepreGuard: Detecting LLM-Generated Text by Revealing Hidden Representation Patterns
Xin Chen, Junchao Wu, Shu Yang +7
Detecting content generated by large language models (LLMs) is crucial for preventing misuse and building trustworthy AI systems. Although existing detection methods perform well,…