40 citations · 49 across the 17 of their papers we have counts for
18 papers
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…
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…
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…
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…
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…
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…
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…
KL Penalty Control via Perturbation for Direct Preference Optimization
Sangkyu Lee, Janghoon Han, Hosung Song +3
Direct Preference Optimization (DPO) demonstrates the advantage of aligning a large language model with human preference using only an offline dataset. However, DPO has the limitat…
HFI: A unified framework for training-free detection and implicit watermarking of latent diffusion model generated images
Sungik Choi, Hankook Lee, Jaehoon Lee +3
Dramatic advances in the quality of the latent diffusion models (LDMs) also led to the malicious use of AI-generated images. While current AI-generated image detection methods assu…
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…
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…
Deep Exploration of Cross-Lingual Zero-Shot Generalization in Instruction Tuning
Janghoon Han, Changho Lee, Joongbo Shin +3
Instruction tuning has emerged as a powerful technique, significantly boosting zero-shot performance on unseen tasks. While recent work has explored cross-lingual generalization by…
Instruction Matters: A Simple yet Effective Task Selection for Optimized Instruction Tuning of Specific Tasks
Changho Lee, Janghoon Han, Seonghyeon Ye +3
Instruction tuning has been proven effective in enhancing zero-shot generalization across various tasks and in improving the performance of specific tasks. For task-specific improv…
Mitigating Biases for Instruction-following Language Models via Bias Neurons Elimination
Nakyeong Yang, Taegwan Kang, Jungkyu Choi +2
Instruction-following language models often show undesirable biases. These undesirable biases may be accelerated in the real-world usage of language models, where a wide range of i…
Lightweight feature encoder for wake-up word detection based on self-supervised speech representation
Hyungjun Lim, Younggwan Kim, Kiho Yeom +4
Self-supervised learning method that provides generalized speech representations has recently received increasing attention. Wav2vec 2.0 is the most famous example, showing remarka…
External Knowledge Selection with Weighted Negative Sampling in Knowledge-grounded Task-oriented Dialogue Systems
Janghoon Han, Joongbo Shin, Hosung Song +4
Constructing a robust dialogue system on spoken conversations bring more challenge than written conversation. In this respect, DSTC10-Track2-Task2 is proposed, which aims to build…
Towards Continual Knowledge Learning of Language Models
Joel Jang, Seonghyeon Ye, Sohee Yang +5
Large Language Models (LMs) are known to encode world knowledge in their parameters as they pretrain on a vast amount of web corpus, which is often utilized for performing knowledg…
Extrofitting: Enriching Word Representation and its Vector Space with Semantic Lexicons
Hwiyeol Jo, Stanley Jungkyu Choi
We propose post-processing method for enriching not only word representation but also its vector space using semantic lexicons, which we call extrofitting. The method consists of 3…