5 papers · 1 filter
Can Large Language Models Generalize Procedures Across Representations?
Fangru Lin, Valentin Hofmann, Xingchen Wan +4
Large language models (LLMs) are trained and tested extensively on symbolic representations such as code and graphs, yet real-world user tasks are often specified in natural langua…
Inverse Reinforcement Learning with Dynamic Reward Scaling for LLM Alignment
Ruoxi Cheng, Haoxuan Ma, Weixin Wang +7
Alignment is vital for safely deploying large language models (LLMs). Existing techniques are either reward-based (training a reward model on preference pairs and optimizing with r…
Improving Neural Argumentative Stance Classification in Controversial Topics with Emotion-Lexicon Features
Mohammad Yeghaneh Abkenar, Weixing Wang, Manfred Stede +3
Argumentation mining comprises several subtasks, among which stance classification focuses on identifying the standpoint expressed in an argumentative text toward a specific target…
TraceDet: Hallucination Detection from the Decoding Trace of Diffusion Large Language Models
Shenxu Chang, Junchi Yu, Weixing Wang +4
Diffusion large language models (D-LLMs) have recently emerged as a promising alternative to auto-regressive LLMs (AR-LLMs). However, the hallucination problem in D-LLMs remains un…
Assessing Open-Source Large Language Models on Argumentation Mining Subtasks
Mohammad Yeghaneh Abkenar, Weixing Wang, Hendrik Graupner +1
We explore the capability of four open-sourcelarge language models (LLMs) in argumentation mining (AM). We conduct experiments on three different corpora; persuasive essays(PE), ar…