activity
20242026
most citedSafeDPO: A Simple Approach to Direct Preference Optimization with Enhanced Safety

1 citations · 1 across the 1 of their papers we have counts for

collaborators

10 papers

cs.LG20261 cited

SafeDPO: A Simple Approach to Direct Preference Optimization with Enhanced Safety

Geon-Hyeong Kim, Yu Jin Kim, Byoungjip Kim +4

As Large Language Models (LLMs) are increasingly deployed in real-world applications, balancing helpfulness and safety has become a central challenge. A natural approach is to inco…

cs.CL2026

EXAONE Deep: Reasoning Enhanced Language Models

Kyunghoon Bae, Eunbi Choi, Kibong Choi +28

We present EXAONE Deep series, which exhibits superior capabilities in various reasoning tasks, including math and coding benchmarks. We train our models mainly on the reasoning-sp…

cs.CL2026

EXAONE 3.5: Series of Large Language Models for Real-world Use Cases

Soyoung An, Kyunghoon Bae, Eunbi Choi +29

This technical report introduces the EXAONE 3.5 instruction-tuned language models, developed and released by LG AI Research. The EXAONE 3.5 language models are offered in three con…

cs.CL2026

EXAONE 3.0 7.8B Instruction Tuned Language Model

Soyoung An, Kyunghoon Bae, Eunbi Choi +34

We introduce EXAONE 3.0 instruction-tuned language model, the first open model in the family of Large Language Models (LLMs) developed by LG AI Research. Among different model size…

cs.CL2025

LGAI-EMBEDDING-Preview Technical Report

Jooyoung Choi, Hyun Kim, Hansol Jang +6

This report presents a unified instruction-based framework for learning generalized text embeddings optimized for both information retrieval (IR) and non-IR tasks. Built upon a dec…

cs.CV2025

Scalable Video-to-Dataset Generation for Cross-Platform Mobile Agents

Yunseok Jang, Yeda Song, Sungryull Sohn +5

Recent advancements in Large Language Models (LLMs) and Vision-Language Models (VLMs) have sparked significant interest in developing GUI visual agents. We introduce MONDAY (Mobile…