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cs.CL2026

Ready2Blend: From Natural-Language Instructions to Composable Alignment Prompts

Jeesu Jung, Hwan Chang, Juseon Do +5

Continual alignment requires LLMs to adapt to new requirements without forgetting previously acquired behaviors. Natural-language instructions are flexible and composable but offer…

cs.CL2026

Leveraging Fine-grained Error Correction in Korean Speech Recognition for Consultation Services

Yonghyun Jun, Jimin Lee, Hwan Chang +3

Automatic Speech Recognition (ASR) technology is fundamental to customer service automation and large-scale transcription. However, even advanced ASR models exhibit inevitable erro…

cs.CL2026

Scaling Creative Writing Beyond Story-Centric Data with Attribute-Guided Genre Expansion

Hwan Chang, Yongil Kim, Heuiyeen Yeen +3

High-quality creative writing data for large language models (LLMs) remains dominated by story-centric data, limiting models' ability to follow the structural and functional conven…

cs.CL2026

EXAONE 4.5 Technical Report

Eunbi Choi, Kibong Choi, Sehyun Chun +55

This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integrating a dedicated visual enc…

cs.CL2026

Doc-PP: Document Policy Preservation Benchmark for Large Vision-Language Models

Haeun Jang, Hwan Chang, Hwanhee Lee

The deployment of Large Vision-Language Models (LVLMs) for real-world document question answering is often constrained by dynamic, user-defined policies that dictate information di…