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cs.CL2026

MET: Theory-Grounded and Culture-Aware Multilingual Moral Reasoning

Ayoung Lee, Ryan Kwon, Yunxiang Zhang +3

Language models are increasingly used for moral decision-making across diverse linguistic and cultural contexts, yet existing work overlooks multilinguality on three aspects: 1) mu…

cs.CL2026

Learning to Ideate for Machine Learning Engineering Agents

Yunxiang Zhang, Kang Zhou, Zhichao Xu +5

Existing machine learning engineering (MLE) agents struggle to iteratively optimize their implemented algorithms for effectiveness. To address this, we introduce MLE-Ideator, a dua…

cs.CL2026

Skill-Aware Data Selection and Fine-Tuning for Data-Efficient Reasoning Distillation

Lechen Zhang, Yunxiang Zhang, Wei Hu +1

Large reasoning models such as DeepSeek-R1 and their distilled variants achieve strong performance on complex reasoning tasks. Yet, distilling these models often demands large-scal…

cs.CL2025

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…

cs.CL2025

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…