Jaewoong Cho

According to our database, Jaewoong Cho authored at least 38 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Pruning and Distilling Mixture-of-Experts into Dense Language Models.

Junhyuck Kim, Jihun Yun, Haechan Kim, Gyeongman Kim, Joonghyun Bae, Jaewoong Cho

CoRR, May, 2026

Towards Faithful Agentic XAI: A Verification Method and an Open-World Benchmark for Better Model Faithfulness.

Jaechang Kim, Sunung Mun, Seungjoon Lee, Jaewoong Cho, Jungseul Ok

CoRR, May, 2026

Raon-Speech Technical Report.

Beomsoo Kim, Changho Choi, Dohyun Kim, Dongki Lee, Ethan Ewer, Eunchong Kim, Gyeongman Kim, Haechan Kim, Hyeonghwan Kim, Inkyu Park, Jihun Yun, Jihwan Moon, Jiyun Kim, Joonghyun Bae, Junhyuck Kim, Minkyu Kim, Sehun Lee, Seungjun Chung, Sungwoo Cho, Dongmin Park, Dongwon Kim, Hara Kang, Jonghyun Lee, Keon Lee, Kangwook Lee, Jaewoong Cho

CoRR, May, 2026

2025

Clip-Low Increases Entropy and Clip-High Decreases Entropy in Reinforcement Learning of Large Language Models.

Jaesung R. Park, Junsu Kim, Gyeongman Kim, Jinyoung Jo, Sean Choi, Jaewoong Cho, Ernest K. Ryu

CoRR, September, 2025

Orak: A Foundational Benchmark for Training and Evaluating LLM Agents on Diverse Video Games.

Dongmin Park, Minkyu Kim, Beongjun Choi, Junhyuck Kim, Keon Lee, Jonghyun Lee, Inkyu Park, Byeong-Uk Lee, Jaeyoung Hwang, Jaewoo Ahn, Ameya Sunil Mahabaleshwarkar, Bilal Kartal, Pritam Biswas, Yoshi Suhara, Kangwook Lee, Jaewoong Cho

CoRR, June, 2025

Alignment as Distribution Learning: Your Preference Model is Explicitly a Language Model.

Jihun Yun, Juno Kim, Jongho Park, Junhyuck Kim, Jongha Jon Ryu, Jaewoong Cho, Kwang-Sung Jun

CoRR, June, 2025

T1: Tool-integrated Self-verification for Test-time Compute Scaling in Small Language Models.

Minki Kang, Jongwon Jeong, Jaewoong Cho

CoRR, April, 2025

Task Diversity Shortens the In-Context Learning Plateau.

Jaeyeon Kim, Sehyun Kwon, Joo Young Choi, Jongho Park, Jaewoong Cho, Jason D. Lee, Ernest K. Ryu

Trans. Mach. Learn. Res., 2025

Delving into Large Language Models for Effective Time-Series Anomaly Detection.

Junwoo Park, Kyudan Jung, Dohyun Lee, Hyuck Lee, Daehoon Gwak, ChaeHun Park, Jaegul Choo, Jaewoong Cho

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Distilling LLM Agent into Small Models with Retrieval and Code Tools.

Minki Kang, Jongwon Jeong, Seanie Lee, Jaewoong Cho, Sung Ju Hwang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Bridging the Gap between Expert and Language Models: Concept-guided Chess Commentary Generation and Evaluation.

Jaechang Kim, Jinmin Goh, Inseok Hwang, Jaewoong Cho, Jungseul Ok

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Lexico: Extreme KV Cache Compression via Sparse Coding over Universal Dictionaries.

Junhyuck Kim, Jongho Park, Jaewoong Cho, Dimitris Papailiopoulos

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Efficient Generative Modeling with Residual Vector Quantization-Based Tokens.

Jaehyeon Kim, Taehong Moon, Keon Lee, Jaewoong Cho

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Rare-to-Frequent: Unlocking Compositional Generation Power of Diffusion Models on Rare Concepts with LLM Guidance.

Dongmin Park, Sebin Kim, Taehong Moon, Minkyu Kim, Kangwook Lee, Jaewoong Cho

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

DiTTo-TTS: Diffusion Transformers for Scalable Text-to-Speech without Domain-Specific Factors.

Keon Lee, Dong Won Kim, Jaehyeon Kim, Seungjun Chung, Jaewoong Cho

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

FlashAdventure: A Benchmark for GUI Agents Solving Full Story Arcs in Diverse Adventure Games.

Jaewoo Ahn, Junseo Kim, Heeseung Yun, Jaehyeon Son, Dongmin Park, Jaewoong Cho, Gunhee Kim

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

2024

Predictive Pipelined Decoding: A Compute-Latency Trade-off for Exact LLM Decoding.

Seongjun Yang, Gibbeum Lee, Jaewoong Cho, Dimitris Papailiopoulos, Kangwook Lee

Trans. Mach. Learn. Res., 2024

Simple Drop-in LoRA Conditioning on Attention Layers Will Improve Your Diffusion Model.

Joo Young Choi, Jaesung R. Park, Inkyu Park, Jaewoong Cho, Albert No, Ernest K. Ryu

Trans. Mach. Learn. Res., 2024

Mini-Batch Optimization of Contrastive Loss.

Jaewoong Cho, Kartik Sreenivasan, Keon Lee, Kyunghoo Mun, Soheun Yi, Jeong-Gwan Lee, Anna Lee, Jy-yong Sohn, Dimitris Papailiopoulos, Kangwook Lee

Trans. Mach. Learn. Res., 2024

Fast and Accurate Neural Rendering Using Semi-Gradients.

In-Young Cho, Jaewoong Cho

CoRR, 2024

Task Diversity Shortens the ICL Plateau.

Jaeyeon Kim, Sehyun Kwon, Joo Young Choi, Jongho Park, Jaewoong Cho, Jason D. Lee, Ernest K. Ryu

CoRR, 2024

DiTTo-TTS: Efficient and Scalable Zero-Shot Text-to-Speech with Diffusion Transformer.

Keon Lee, Dong Won Kim, Jaehyeon Kim, Jaewoong Cho

CoRR, 2024

A Simple Framework to Accelerate Multilingual Language Model for Monolingual Text Generation.

Jimin Hong, Gibbeum Lee, Jaewoong Cho

CoRR, 2024

SAiD: Speech-driven Blendshape Facial Animation with Diffusion.

Inkyu Park, Jaewoong Cho

CoRR, 2024

Latent Paraphrasing: Perturbation on Layers Improves Knowledge Injection in Language Models.

Minki Kang, Sung Ju Hwang, Gibbeum Lee, Jaewoong Cho

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Can Mamba Learn How To Learn? A Comparative Study on In-Context Learning Tasks.

Jongho Park, Jaeseung Park, Zheyang Xiong, Nayoung Lee, Jaewoong Cho, Samet Oymak, Kangwook Lee, Dimitris Papailiopoulos

Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Simple Early Exiting Framework for Accelerated Sampling in Diffusion Models.

Tae Hong Moon, Moonseok Choi, EungGu Yun, Jongmin Yoon, Gayoung Lee, Jaewoong Cho, Juho Lee

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Image Clustering Conditioned on Text Criteria.

Sehyun Kwon, Jaeseung Park, Minkyu Kim, Jaewoong Cho, Ernest K. Ryu, Kangwook Lee

Proceedings of the Twelfth International Conference on Learning Representations, 2024

CLaM-TTS: Improving Neural Codec Language Model for Zero-Shot Text-to-Speech.

Jaehyeon Kim, Keon Lee, Seungjun Chung, Jaewoong Cho

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Accelerating Multilingual Language Model for Excessively Tokenized Languages.

Jimin Hong, Gibbeum Lee, Jaewoong Cho

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Addressing Feature Imbalance in Sound Source Separation.

Jaechang Kim, Jeongyeon Hwang, Soheun Yi, Jaewoong Cho, Jungseul Ok

CoRR, 2023

Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback.

Taeho Yoon, Kibeom Myoung, Keon Lee, Jaewoong Cho, Albert No, Ernest K. Ryu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Equal Experience in Recommender Systems.

Jaewoong Cho, Moonseok Choi, Changho Suh

CoRR, 2022

2020

A Fair Classifier Using Kernel Density Estimation.

Jaewoong Cho, Gyeongjo Hwang, Changho Suh

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Fair Classifier Using Mutual Information.

Jaewoong Cho, Gyeongjo Hwang, Changho Suh

Proceedings of the IEEE International Symposium on Information Theory, 2020

2019

Wasserstein GAN Can Perform PCA.

Jaewoong Cho, Changho Suh

Proceedings of the 57th Annual Allerton Conference on Communication, 2019

2017

Two-way interference channel capacity: How to have the cake and eat it too.

Changho Suh, Jaewoong Cho, David Tse

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

2016

To feedback or not to feedback.

Changho Suh, David Tse, Jaewoong Cho

Proceedings of the IEEE International Symposium on Information Theory, 2016