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20222026
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cs.CL2026

The Hallucination Signal Is a Mean Shift: Why Simple Probes Suffice

Jungseob Lee, Jaehyung Seo, Heuiseok Lim

Hidden-state probes effectively detect LLM hallucinations, but the geometry of the signal remains poorly characterized, driving increasingly complex probe architectures. Across thr…

cs.CL2026

Language Chain in Alignment: Cross-lingual Ranking Preference Optimization

Seungyoon Lee, Minhyuk Kim, Jungseob Lee +1

The alignment of Large Language Models heavily relies on English-centric high-quality preference data, which often leads to suboptimal performance in other languages. In this paper…

cs.CL2026

Answer-Conditioned Chains of Thought Degrade Verifiable-Reasoning Distillation in Large Language Models

Jungseob Lee, Seungyoon Lee, Suhyune Son +4

A standard recipe for distilling the reasoning ability of large language models (LLMs) is to sample chains of thought from the model, keep those that reach the correct final answer…

cs.CL2025

Cross-Lingual Optimization for Language Transfer in Large Language Models

Jungseob Lee, Seongtae Hong, Hyeonseok Moon +1

Adapting large language models to other languages typically employs supervised fine-tuning (SFT) as a standard approach. However, it often suffers from an overemphasis on English p…

cs.CL2022

Language Chameleon: Transformation analysis between languages using Cross-lingual Post-training based on Pre-trained language models

Suhyune Son, Chanjun Park, Jungseob Lee +5

As pre-trained language models become more resource-demanding, the inequality between resource-rich languages such as English and resource-scarce languages is worsening. This can b…