Jungtaek Kim - RankMe

48 papers A* 12A 3Misc 2Journal 30Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	TAPE: Tool-Guided Adaptive Planning and Constrained Execution in Language Model Agents. CoRR Jongwon Jeong, Jungtaek Kim, Kangwook Lee
2026	J	`jnl`	Transformers in the Dark: Navigating Unknown Search Spaces via Bandit Feedback. CoRR Jungtaek Kim, Thomas Zeng, Ziqian Lin, Minjae Lee, Chungpa Lee, Jy-yong Sohn, Hyung Il Koo, Kangwook Lee
2026	J	`jnl`	Transformers in the Dark: Navigating Unknown Search Spaces via Bandit Feedback. Trans. Mach. Learn. Res. Jungtaek Kim, Thomas Zeng, Ziqian Lin, Minjae Lee, Chungpa Lee, Jy-yong Sohn, Hyung Il Koo, Kangwook Lee
2025	J	`jnl`	ReJump: A Tree-Jump Representation for Analyzing and Improving LLM Reasoning. CoRR Yuchen Zeng, Shuibai Zhang, Wonjun Kang, Shutong Wu, Lynnix Zou, Ying Fan, Heeju Kim, Ziqian Lin, Jungtaek Kim, Hyung Il Koo, Dimitris Papailiopoulos, Kangwook Lee
2025	A*	`conf`	VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data. ICML Thomas Zeng, Shuibai Zhang, Shutong Wu, Christian Classen, Daewon Chae, Ethan Ewer, Minjae Lee, Heeju Kim, Wonjun Kang, Jackson Kunde, Ying Fan, Jungtaek Kim, Hyung Il Koo, Kannan Ramchandran, Dimitris Papailiopoulos, Kangwook Lee
2025	J	`jnl`	VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data. CoRR Thomas Zeng, Shuibai Zhang, Shutong Wu, Christian Classen, Daewon Chae, Ethan Ewer, Minjae Lee, Heeju Kim, Wonjun Kang, Jackson Kunde, Ying Fan, Jungtaek Kim, Hyung Il Koo, Kannan Ramchandran, Dimitris Papailiopoulos, Kangwook Lee
2024	J	`jnl`	Beyond Regrets: Geometric Metrics for Bayesian Optimization. CoRR Jungtaek Kim
2024	J	`jnl`	Budget-Aware Sequential Brick Assembly with Efficient Constraint Satisfaction. Trans. Mach. Learn. Res. Seokjun Ahn, Jungtaek Kim, Minsu Cho, Jaesik Park
2024	A	`conf`	Exploiting Preferences in Loss Functions for Sequential Recommendation via Weak Transitivity. CIKM Hyunsoo Chung, Jungtaek Kim, Hyungeun Jo, Hyungwon Choi
2024	J	`jnl`	Exploiting Preferences in Loss Functions for Sequential Recommendation via Weak Transitivity. CoRR Hyunsoo Chung, Jungtaek Kim, Hyungeun Jo, Hyungwon Choi
2024	A*	`conf`	Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions. ICLR Jungtaek Kim, Jeongbeen Yoon, Minsu Cho
2024	A*	`conf`	Model Fusion through Bayesian Optimization in Language Model Fine-Tuning. NeurIPS Chaeyun Jang, Hyungi Lee, Jungtaek Kim, Juho Lee
2024	J	`jnl`	Model Fusion through Bayesian Optimization in Language Model Fine-Tuning. CoRR Chaeyun Jang, Hyungi Lee, Jungtaek Kim, Juho Lee
2024	A*	`conf`	Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization. ICML Kwang-Sung Jun, Jungtaek Kim
2024	J	`jnl`	Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization. CoRR Kwang-Sung Jun, Jungtaek Kim
2023	J	`jnl`	BayesO: A Bayesian optimization framework in Python. J. Open Source Softw. Jungtaek Kim, Seungjin Choi
2023	A*	`conf`	Datasets and Benchmarks for Nanophotonic Structure and Parametric Design Simulations. NeurIPS Jungtaek Kim, Mingxuan Li, Oliver Hinder, Paul W. Leu
2023	J	`jnl`	Datasets and Benchmarks for Nanophotonic Structure and Parametric Design Simulations. CoRR Jungtaek Kim, Mingxuan Li, Oliver Hinder, Paul W. Leu
2023	J	`jnl`	Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning. CoRR Jungtaek Kim
2023	J	`jnl`	Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions. CoRR Jungtaek Kim, Jeongbeen Yoon, Minsu Cho
2023	A*	`conf`	Generative Neural Fields by Mixtures of Neural Implicit Functions. NeurIPS Tackgeun You, Mijeong Kim, Jungtaek Kim, Bohyung Han
2023	J	`jnl`	Generative Neural Fields by Mixtures of Neural Implicit Functions. CoRR Tackgeun You, Mijeong Kim, Jungtaek Kim, Bohyung Han
2022	A	`conf`	Combinatorial Bayesian optimization with random mapping functions to convex polytopes. UAI Jungtaek Kim, Seungjin Choi, Minsu Cho
2022	A*	`conf`	Learning to Assemble Geometric Shapes. IJCAI Jinhwi Lee, Jungtaek Kim, Hyunsoo Chung, Jaesik Park, Minsu Cho
2022	J	`jnl`	Learning to Assemble Geometric Shapes. CoRR Jinhwi Lee, Jungtaek Kim, Hyunsoo Chung, Jaesik Park, Minsu Cho
2022	A*	`conf`	On Evaluation Metrics for Graph Generative Models. ICLR Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham W. Taylor
2022	J	`jnl`	On Evaluation Metrics for Graph Generative Models. CoRR Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham W. Taylor
2022	A	`conf`	On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization. AISTATS Jungtaek Kim, Seungjin Choi
2022	J	`jnl`	On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization. CoRR Jungtaek Kim, Seungjin Choi
2022	J	`jnl`	Sequential Brick Assembly with Efficient Constraint Satisfaction. CoRR Seokjun Ahn, Jungtaek Kim, Minsu Cho, Jaesik Park
2021	J	`jnl`	Bayesian optimization with approximate set kernels. Mach. Learn. Jungtaek Kim, Michael McCourt, Tackgeun You, Saehoon Kim, Seungjin Choi
2021	A*	`conf`	Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning. NeurIPS Hyunsoo Chung, Jungtaek Kim, Boris Knyazev, Jinhwi Lee, Graham W. Taylor, Jaesik Park, Minsu Cho
2021	J	`jnl`	Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning. CoRR Hyunsoo Chung, Jungtaek Kim, Boris Knyazev, Jinhwi Lee, Graham W. Taylor, Jaesik Park, Minsu Cho
2020	J	`jnl`	Bootstrapping Neural Processes. CoRR Juho Lee, Yoonho Lee, Jungtaek Kim, Eunho Yang, Sung Ju Hwang, Yee Whye Teh
2020	A*	`conf`	Bootstrapping neural processes. NeurIPS Juho Lee, Yoonho Lee, Jungtaek Kim, Eunho Yang, Sung Ju Hwang, Yee Whye Teh
2020	J	`jnl`	Combinatorial 3D Shape Generation via Sequential Assembly. CoRR Jungtaek Kim, Hyunsoo Chung, Minsu Cho, Jaesik Park
2020	J	`jnl`	Combinatorial Bayesian Optimization with Random Mapping Functions to Convex Polytope. CoRR Jungtaek Kim, Minsu Cho, Seungjin Choi
2020	—	`conf`	On Local Optimizers of Acquisition Functions in Bayesian Optimization. ECML/PKDD (2) Jungtaek Kim, Seungjin Choi
2019	J	`jnl`	Bayesian Optimization over Sets. CoRR Jungtaek Kim, Michael McCourt, Tackgeun You, Saehoon Kim, Seungjin Choi
2019	J	`jnl`	MxML: Mixture of Meta-Learners for Few-Shot Classification. CoRR Minseop Park, Jungtaek Kim, Saehoon Kim, Yanbin Liu, Seungjin Choi
2019	J	`jnl`	On Local Optimizers of Acquisition Functions in Bayesian Optimization. CoRR Jungtaek Kim, Seungjin Choi
2019	J	`jnl`	Practical Bayesian Optimization with Threshold-Guided Marginal Likelihood Maximization. CoRR Jungtaek Kim, Seungjin Choi
2019	A*	`conf`	Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks. ICML Juho Lee, Yoonho Lee, Jungtaek Kim, Adam R. Kosiorek, Seungjin Choi, Yee Whye Teh
2018	Misc	`conf`	Clustering-Guided Gp-Ucb for Bayesian Optimization. ICASSP Jungtaek Kim, Seungjin Choi
2018	A*	`conf`	On the Optimal Bit Complexity of Circulant Binary Embedding. AAAI Saehoon Kim, Jungtaek Kim, Seungjin Choi
2018	Misc	`conf`	Open Set Recognition by Regularising Classifier with Fake Data Generated by Generative Adversarial Networks. ICASSP Inhyuk Jo, Jungtaek Kim, Hyohyeong Kang, Yong-Deok Kim, Seungjin Choi
2018	J	`jnl`	Set Transformer. CoRR Juho Lee, Yoonho Lee, Jungtaek Kim, Adam R. Kosiorek, Seungjin Choi, Yee Whye Teh
2017	J	`jnl`	Learning to Transfer Initializations for Bayesian Hyperparameter Optimization. CoRR Jungtaek Kim, Saehoon Kim, Seungjin Choi