From the 1 of 5 linked papers with an AI index.
5 papers
MET: Theory-Grounded and Culture-Aware Multilingual Moral Reasoning
Ayoung Lee, Ryan Kwon, Yunxiang Zhang +3
The paper introduces a multilingual, culture-aware benchmark (MCLASH) and a two-step, theory‑grounded prompting method (MET) with a self‑distillation variant (MET‑D) to improve mor…
LiveOIBench: Can Large Language Models Outperform Human Contestants in Informatics Olympiads?
Kaijian Zou, Aaron Xiong, Yunxiang Zhang +6
Competitive programming problems are increasingly used to evaluate the coding capabilities of large language models (LLMs) due to their complexity and ease of verification. Yet, cu…
CLASH: Evaluating Language Models on Judging High-Stakes Dilemmas from Multiple Perspectives
Ayoung Lee, Ryan Sungmo Kwon, Peter Railton +1
Navigating dilemmas involving conflicting values is challenging even for humans in high-stakes domains, let alone for AI, yet prior work has been limited to everyday scenarios. To…
Logit Arithmetic Elicits Long Reasoning Capabilities Without Training
Yunxiang Zhang, Muhammad Khalifa, Lechen Zhang +5
Large reasoning models exhibit long chain-of-thought reasoning with complex strategies such as backtracking and self-verification. Yet, these capabilities typically require resourc…
Logit Arithmetic Elicits Long Reasoning Capabilities Without Training
Yunxiang Zhang, Muhammad Khalifa, Lechen Zhang +5
Large reasoning models (LRMs) can do complex reasoning via long chain-of-thought (CoT) involving cognitive strategies such as backtracking and self-correction. Recent studies sugge…