Jaekyeom Kim

29 papers A* 7Journal 16Unranked 6
YearRankTypeTitle / Venue / Authors
2026 — conf
Beyond Blind Following: Evaluating Robustness of LLM Agents under Imperfect Guidance.
EACL (Volume 1: Long Papers)
Yao Fu, Ran Qiu, Xinhe Wang, Jacob Sansom, Sathvika Ayyappa Prabhu, Huijie Tang, Jaekyeom Kim, Sungryull Sohn, Honglak Lee
2026 J jnl
Gaming the Judge: Unfaithful Chain-of-Thought Can Undermine Agent Evaluation.
CoRR
Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim, Sungryull Sohn, Yunxiang Zhang, Moontae Lee, Hao Peng, Lu Wang, Honglak Lee
2026 J jnl
Process Reward Models That Think.
Trans. Mach. Learn. Res.
Muhammad Khalifa, Rishabh Agarwal, Lajanugen Logeswaran, Jaekyeom Kim, Hao Peng, Moontae Lee, Honglak Lee, Lu Wang
2026 J jnl
Scaling Web Agent Training through Automatic Data Generation and Fine-grained Evaluation.
CoRR
Lajanugen Logeswaran, Jaekyeom Kim, Sungryull Sohn, Creighton Glasscock, Honglak Lee
2025 J jnl
Do Not Trust Licenses You See: Dataset Compliance Requires Massive-Scale AI-Powered Lifecycle Tracing.
CoRR
Jaekyeom Kim, Sungryull Sohn, Gerrard Jeongwon Jo, Jihoon Choi, Kyunghoon Bae, Hwayoung Lee, Yongmin Park, Honglak Lee
2025 — conf
Interactive and Expressive Code-Augmented Planning with Large Language Models.
ACL (1)
Anthony Zhe Liu, Xinhe Wang, Jacob Sansom, Yao Fu, Jongwook Choi, Sungryull Sohn, Jaekyeom Kim, Honglak Lee
2025 J jnl
MLRC-Bench: Can Language Agents Solve Machine Learning Research Challenges?
CoRR
Yunxiang Zhang, Muhammad Khalifa, Shitanshu Bhushan, Grant D. Murphy, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, Lu Wang
2025 J jnl
Process Reward Models That Think.
CoRR
Muhammad Khalifa, Rishabh Agarwal, Lajanugen Logeswaran, Jaekyeom Kim, Hao Peng, Moontae Lee, Honglak Lee, Lu Wang
2025 J jnl
Towards Minimal Fine-Tuning of VLMs.
CoRR
Tiange Luo, Lajanugen Logeswaran, Jaekyeom Kim, Justin Johnson, Honglak Lee
2024 — conf
Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agents.
EMNLP (Findings)
Jaekyeom Kim, Dong-Ki Kim, Lajanugen Logeswaran, Sungryull Sohn, Honglak Lee
2024 J jnl
Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agents.
CoRR
Jaekyeom Kim, Dong-Ki Kim, Lajanugen Logeswaran, Sungryull Sohn, Honglak Lee
2024 A* conf
AutoGuide: Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents.
NeurIPS
Yao Fu, Dong-Ki Kim, Jaekyeom Kim, Sungryull Sohn, Lajanugen Logeswaran, Kyunghoon Bae, Honglak Lee
2024 J jnl
AutoGuide: Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents.
CoRR
Yao Fu, Dong-Ki Kim, Jaekyeom Kim, Sungryull Sohn, Lajanugen Logeswaran, Kyunghoon Bae, Honglak Lee
2024 J jnl
Interactive and Expressive Code-Augmented Planning with Large Language Models.
CoRR
Anthony Z. Liu, Xinhe Wang, Jacob Sansom, Yao Fu, Jongwook Choi, Sungryull Sohn, Jaekyeom Kim, Honglak Lee
2024 — conf
Small Language Models Need Strong Verifiers to Self-Correct Reasoning.
ACL (Findings)
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, Lu Wang
2024 J jnl
Small Language Models Need Strong Verifiers to Self-Correct Reasoning.
CoRR
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, Lu Wang
2022 A* conf
Constrained GPI for Zero-Shot Transfer in Reinforcement Learning.
NeurIPS
Jaekyeom Kim, Seohong Park, Gunhee Kim
2022 A* conf
Lipschitz-constrained Unsupervised Skill Discovery.
ICLR
Seohong Park, Jongwook Choi, Jaekyeom Kim, Honglak Lee, Gunhee Kim
2022 J jnl
Lipschitz-constrained Unsupervised Skill Discovery.
CoRR
Seohong Park, Jongwook Choi, Jaekyeom Kim, Honglak Lee, Gunhee Kim
2021 A* conf
Drop-Bottleneck: Learning Discrete Compressed Representation for Noise-Robust Exploration.
ICLR
Jaekyeom Kim, Minjung Kim, Dongyeon Woo, Gunhee Kim
2021 J jnl
Drop-Bottleneck: Learning Discrete Compressed Representation for Noise-Robust Exploration.
CoRR
Jaekyeom Kim, Minjung Kim, Dongyeon Woo, Gunhee Kim
2021 A* conf
Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods.
NeurIPS
Seohong Park, Jaekyeom Kim, Gunhee Kim
2021 J jnl
Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods.
CoRR
Seohong Park, Jaekyeom Kim, Gunhee Kim
2021 A* conf
Unsupervised Skill Discovery with Bottleneck Option Learning.
ICML
Jaekyeom Kim, Seohong Park, Gunhee Kim
2021 J jnl
Unsupervised Skill Discovery with Bottleneck Option Learning.
CoRR
Jaekyeom Kim, Seohong Park, Gunhee Kim
2020 — conf
Model-Agnostic Boundary-Adversarial Sampling for Test-Time Generalization in Few-Shot Learning.
ECCV (1)
Jaekyeom Kim, HyoungSeok Kim, Gunhee Kim
2019 A* conf
EMI: Exploration with Mutual Information.
ICML
HyoungSeok Kim, Jaekyeom Kim, Yeonwoo Jeong, Sergey Levine, Hyun Oh Song
2018 J jnl
EMI: Exploration with Mutual Information Maximizing State and Action Embeddings.
CoRR
HyoungSeok Kim, Jaekyeom Kim, Yeonwoo Jeong, Sergey Levine, Hyun Oh Song
2015 — conf
Image quality evaluation of LCDs based on novel RGBW sub-pixel structure.
IQSP
Sungjin Kim, Dongwoo Kang, Jinsang Lee, Jaekyeom Kim, Yongmin Park, Taeseong Han, Sooyeon Jung, Jang Jin Yoo, Moojong Lim, JongSang Baek