activity
20242026
most citedDEER: A Benchmark for Evaluating Deep Research Agents on Expert Report Generation

1 citations · 1 across the 3 of their papers we have counts for

collaborators

10 papers

cs.CL2026

K-EXAONE 2.0 Technical Report

Eunbi Choi, Kibong Choi, Sehyun Chun +74

This technical report presents K-EXAONE 2.0, an open-weight multilingual foundation model developed by LG AI Research as a step in our effort toward global frontier-scale foundatio…

cs.CL20261 cited

DEER: A Benchmark for Evaluating Deep Research Agents on Expert Report Generation

Janghoon Han, Heegyu Kim, Changho Lee +6

Recent advances in large language models have enabled deep research systems that generate expert-level reports through multi-step reasoning and evidence-based synthesis. However, e…

cs.CV2026

Spanning Tree Autoregressive Visual Generation

Sangkyu Lee, Changho Lee, Janghoon Han +6

We present Spanning Tree Autoregressive (STAR) modeling, which can incorporate prior knowledge of images, such as center bias and locality, to maintain sampling performance while a…

cs.CL2026

K-EXAONE Technical Report

Eunbi Choi, Kibong Choi, Seokhee Hong +62

This technical report presents K-EXAONE, a large-scale multilingual language model developed by LG AI Research. K-EXAONE is built on a Mixture-of-Experts architecture with 236B tot…

cs.CL2026

EXAONE 4.0: Unified Large Language Models Integrating Non-reasoning and Reasoning Modes

Kyunghoon Bae, Eunbi Choi, Kibong Choi +37

This technical report introduces EXAONE 4.0, which integrates a Non-reasoning mode and a Reasoning mode to achieve both the excellent usability of EXAONE 3.5 and the advanced reaso…

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…