1 citations · 1 across the 2 of their papers we have counts for
6 papers
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…
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…
MolMole: Molecule Mining from Scientific Literature
LG AI Research, Sehyun Chun, Jiye Kim +31
The extraction of molecular structures and reaction data from scientific documents is challenging due to their varied, unstructured chemical formats and complex document layouts. T…
Do Not Trust Licenses You See: Dataset Compliance Requires Massive-Scale AI-Powered Lifecycle Tracing
Jaekyeom Kim, Sungryull Sohn, Gerrard Jeongwon Jo +5
This paper argues that a dataset's legal risk cannot be accurately assessed by its license terms alone; instead, tracking dataset redistribution and its full lifecycle is essential…
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…
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…