Power-Aware Position Vector Routing for Wireless Sensor Networks. - Sangsoo Lee; Daeyoung Kim 001; Sungjin Ahn; Noseong Park (EUC Workshops, 2005)

Proactive Context-Aware Sensor Networks. - Sungjin Ahn; Daeyoung Kim 001 (EWSN, 2006)

Mosaic Localization for Wireless Sensor Networks. - Jihoon Kang; Daeyoung Kim 001; Sungjin Ahn (WCNC, 2007)

Wireless Sensor Networks for Cultural Property Protection. - Jongwoo Sung; Sungjin Ahn; Taesoo Park; Seonghun Jang; Dongheui Yun; Jonggu Kang; Seongeun Yoo; Pohkit Chong; Daeyoung Kim 001 (AINA Workshops, 2008)

Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring. - Sungjin Ahn; Anoop Korattikara Balan; Max Welling (ICML, 2012)

Distributed and Adaptive Darting Monte Carlo through Regenerations. - Sungjin Ahn; Yutian Chen 001; Max Welling (AISTATS, 2013)

Distributed Stochastic Gradient MCMC. - Sungjin Ahn; Babak Shahbaba; Max Welling (ICML, 2014)

Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC. - Sungjin Ahn; Anoop Korattikara; Nathan Liu; Suju Rajan; Max Welling (KDD, 2015)

Pointing the Unknown Words. - Çaglar Gülçehre; Sungjin Ahn; Ramesh Nallapati; Bowen Zhou 002; Yoshua Bengio (ACL (1), 2016)

Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus. - Iulian Vlad Serban; Alberto García-Durán; Çaglar Gülçehre; Sungjin Ahn; Sarath Chandar; Aaron C. Courville; Yoshua Bengio (ACL (1), 2016)

Scalable MCMC for Mixed Membership Stochastic Blockmodels. - Wenzhe Li; Sungjin Ahn; Max Welling (AISTATS, 2016)

Scalable Overlapping Community Detection. - Ismail El-Helw; Rutger F. H. Hofman; Wenzhe Li; Sungjin Ahn; Max Welling; Henri E. Bal (IPDPS Workshops, 2016)

A Neural Knowledge Language Model. - Sungjin Ahn; Heeyoul Choi; Tanel Pärnamaa; Yoshua Bengio (CoRR, 2016)

Hierarchical Memory Networks. - Sarath Chandar; Sungjin Ahn; Hugo Larochelle; Pascal Vincent; Gerald Tesauro; Yoshua Bengio (CoRR, 2016)

Denoising Criterion for Variational Auto-Encoding Framework. - Daniel Jiwoong Im; Sungjin Ahn; Roland Memisevic; Yoshua Bengio (AAAI, 2017)

SENA: Preserving Social Structure for Network Embedding. - Sanghyun Hong 001; Tanmoy Chakraborty 002; Sungjin Ahn; Ghaith Husari; Noseong Park (HT, 2017)

Hierarchical Multiscale Recurrent Neural Networks. - Junyoung Chung; Sungjin Ahn; Yoshua Bengio (ICLR (Poster), 2017)

Bayesian Model-Agnostic Meta-Learning. - Jaesik Yoon; Taesup Kim; Ousmane Dia; Sungwoong Kim; Yoshua Bengio; Sungjin Ahn (NeurIPS, 2018)

Learning Single-View 3D Reconstruction with Adversarial Training. - Pedro O. Pinheiro; Negar Rostamzadeh; Sungjin Ahn (CoRR, 2018)

Domain-Adaptive Single-View 3D Reconstruction. - Pedro O. Pinheiro; Negar Rostamzadeh; Sungjin Ahn (ICCV, 2019)

Variational Temporal Abstraction. - Taesup Kim; Sungjin Ahn; Yoshua Bengio (NeurIPS, 2019)

Neural Multisensory Scene Inference. - Jae Hyun Lim 001; Pedro O. Pinheiro; Negar Rostamzadeh; Chris Pal; Sungjin Ahn (NeurIPS, 2019)

Sequential Neural Processes. - Gautam Singh; Jaesik Yoon; Youngsung Son; Sungjin Ahn (NeurIPS, 2019)

Reinforced Imitation in Heterogeneous Action Space. - Konrad Zolna; Negar Rostamzadeh; Yoshua Bengio; Sungjin Ahn; Pedro O. Pinheiro (CoRR, 2019)

Scalable Object-Oriented Sequential Generative Models. - Jindong Jiang; Sepehr Janghorbani; Gerard de Melo; Sungjin Ahn (CoRR, 2019)

Generative Hierarchical Models for Parts, Objects, and Scenes. - Fei Deng; Zhuo Zhi; Sungjin Ahn (CoRR, 2019)

SCALOR: Generative World Models with Scalable Object Representations. - Jindong Jiang; Sepehr Janghorbani; Gerard de Melo; Sungjin Ahn (ICLR, 2020)

SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition. - Zhixuan Lin; Yi-Fu Wu; Skand Vishwanath Peri; Weihao Sun; Gautam Singh; Fei Deng 001; Jindong Jiang; Sungjin Ahn (ICLR, 2020)

Improving Generative Imagination in Object-Centric World Models. - Zhixuan Lin; Yi-Fu Wu; Skand Vishwanath Peri; Bofeng Fu; Jindong Jiang; Sungjin Ahn (ICML, 2020)

Robustifying Sequential Neural Processes. - Jaesik Yoon; Gautam Singh; Sungjin Ahn (ICML, 2020)

Generative Neurosymbolic Machines. - Jindong Jiang; Sungjin Ahn (NeurIPS, 2020)

Learning to Infer 3D Object Models from Images. - Chang Chen; Fei Deng; Sungjin Ahn (CoRR, 2020)

Generative Scene Graph Networks. - Fei Deng 001; Zhuo Zhi; Donghun Lee; Sungjin Ahn (ICLR, 2021)

Structured World Belief for Reinforcement Learning in POMDP. - Gautam Singh; Skand Vishwanath Peri; Junghyun Kim 007; Hyunseok Kim; Sungjin Ahn (ICML, 2021)

Generative Video Transformer: Can Objects be the Words? - Yi-Fu Wu; Jaesik Yoon; Sungjin Ahn (ICML, 2021)

ROOTS: Object-Centric Representation and Rendering of 3D Scenes. - Chang Chen; Fei Deng 001; Sungjin Ahn (J. Mach. Learn. Res., 2021)

Illiterate DALL-E Learns to Compose. - Gautam Singh; Fei Deng 001; Sungjin Ahn (ICLR, 2022)

DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations. - Fei Deng 001; Ingook Jang; Sungjin Ahn (ICML, 2022)

Simple Unsupervised Object-Centric Learning for Complex and Naturalistic Videos. - Gautam Singh; Yi-Fu Wu; Sungjin Ahn (NeurIPS, 2022)

TransDreamer: Reinforcement Learning with Transformer World Models. - Chang Chen; Yi-Fu Wu; Jaesik Yoon; Sungjin Ahn (CoRR, 2022)

Neural Block-Slot Representations. - Gautam Singh; Yeongbin Kim; Sungjin Ahn (CoRR, 2022)

Neural Systematic Binder. - Gautam Singh; Yeongbin Kim; Sungjin Ahn (ICLR, 2023)

An Investigation into Pre-Training Object-Centric Representations for Reinforcement Learning. - Jaesik Yoon; Yi-Fu Wu; Heechul Bae; Sungjin Ahn (ICML, 2023)

Facing Off World Model Backbones: RNNs, Transformers, and S4. - Fei Deng 001; Junyeong Park; Sungjin Ahn (NeurIPS, 2023)

Object-Centric Slot Diffusion. - Jindong Jiang; Fei Deng 001; Gautam Singh; Sungjin Ahn (NeurIPS, 2023)

Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models. - Yeongbin Kim; Gautam Singh; Junyeong Park; Çaglar Gülçehre; Sungjin Ahn (NeurIPS, 2023)

Object-Centric Semantic Vector Quantization. - Yi-Fu Wu; Minseung Lee; Sungjin Ahn (UniReps, 2023)

Computational Prediction of the Phenotypic Effect of Flavonoids on Adiponectin Biosynthesis. - Seungchan An; Seok Young Hwang; Junpyo Gong; Sungjin Ahn; In Guk Park; Soyeon Oh; Young-Won Chin; Minsoo Noh (J. Chem. Inf. Model., 2023)

Simple Hierarchical Planning with Diffusion. - Chang Chen; Fei Deng 001; Kenji Kawaguchi; Caglar Gulcehre; Sungjin Ahn (ICLR, 2024)

Spatially-Aware Transformers for Embodied Agents. - Junmo Cho; Jaesik Yoon; Sungjin Ahn (ICLR, 2024)

Learning to Compose: Improving Object Centric Learning by Injecting Compositionality. - Whie Jung; Jaehoon Yoo; Sungjin Ahn; Seunghoon Hong (ICLR, 2024)

Neural Language of Thought Models. - Yi-Fu Wu; Minseung Lee; Sungjin Ahn (ICLR, 2024)

PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer. - Chang Chen; Junyeob Baek; Fei Deng 001; Kenji Kawaguchi; Caglar Gulcehre; Sungjin Ahn (ICML, 2024)

Dr. Strategy: Model-Based Generalist Agents with Strategic Dreaming. - Hany Hamed; Subin Kim; Dongyeong Kim; Jaesik Yoon; Sungjin Ahn (ICML, 2024)

Parallelized Spatiotemporal Slot Binding for Videos. - Gautam Singh; Yue Wang 041; Jiawei Yang 002; Boris Ivanovic; Sungjin Ahn; Marco Pavone 001; Tong Che (ICML, 2024)

Slot State Space Models. - Jindong Jiang; Fei Deng 001; Gautam Singh; Minseung Lee; Sungjin Ahn (NeurIPS, 2024)

Structured World Modeling via Semantic Vector Quantization. - Yi-Fu Wu; Minseung Lee; Sungjin Ahn (CoRR, 2024)

Spatially-Aware Transformer for Embodied Agents. - Junmo Cho; Jaesik Yoon; Sungjin Ahn (CoRR, 2024)

Parallelized Spatiotemporal Binding. - Gautam Singh; Yue Wang 041; Jiawei Yang 002; Boris Ivanovic; Sungjin Ahn; Marco Pavone 001; Tong Che (CoRR, 2024)

Mr.Steve: Instruction-Following Agents in Minecraft with What-Where-When Memory. - Junyeong Park; Junmo Cho; Sungjin Ahn (CoRR, 2024)

Dreamweaver: Learning Compositional World Models from Pixels. - Junyeob Baek; Yi-Fu Wu; Gautam Singh; Sungjin Ahn (ICLR, 2025)

MrSteve: Instruction-Following Agents in Minecraft with What-Where-When Memory. - Junyeong Park; Junmo Cho; Sungjin Ahn (ICLR, 2025)

Dreamweaver: Learning Compositional World Representations from Pixels. - Junyeob Baek; Yi-Fu Wu; Gautam Singh; Sungjin Ahn (CoRR, 2025)

Monte Carlo Tree Diffusion for System 2 Planning. - Jaesik Yoon; Hyeonseo Cho; Doojin Baek; Yoshua Bengio; Sungjin Ahn (CoRR, 2025)

Token-Efficient Long Video Understanding for Multimodal LLMs. - Jindong Jiang; Xiuyu Li; Zhijian Liu; Muyang Li; Guo Chen 006; Zhiqi Li; De-An Huang; Guilin Liu; Zhiding Yu; Kurt Keutzer; Sungjin Ahn; Jan Kautz; et al. (CoRR, 2025)

Extendable Long-Horizon Planning via Hierarchical Multiscale Diffusion. - Chang Chen; Hany Hamed; Doojin Baek; Taegu Kang; Yoshua Bengio; Sungjin Ahn (CoRR, 2025)

Search-Based Correction of Reasoning Chains for Language Models. - Minsu Kim 004; Jean-Pierre R. Falet; Oliver E. Richardson; Xiaoyin Chen; Moksh Jain; Sungjin Ahn; Sungsoo Ahn; Yoshua Bengio (CoRR, 2025)

Adaptive Cyclic Diffusion for Inference Scaling. - Gyubin Lee; Truong Nhat Nguyen Bao; Jaesik Yoon; Dongwoo Lee; Minsu Kim 004; Yoshua Bengio; Sungjin Ahn (CoRR, 2025)

Slot-MLLM: Object-Centric Visual Tokenization for Multimodal LLM. - Donghwan Chi; Hyomin Kim; Yoonjin Oh; Yongjin Kim; Donghoon Lee; Daejin Jo; Jongmin Kim 006; Junyeob Baek; Sungjin Ahn; Sungwoong Kim (CoRR, 2025)

Fast Monte Carlo Tree Diffusion: 100x Speedup via Parallel Sparse Planning. - Jaesik Yoon; Hyeonseo Cho; Yoshua Bengio; Sungjin Ahn (CoRR, 2025)

Discrete JEPA: Learning Discrete Token Representations without Reconstruction. - Junyeob Baek; Hosung Lee; Christopher Hoang; Mengye Ren; Sungjin Ahn (CoRR, 2025)

CrafterDojo: A Suite of Foundation Models for Building Open-Ended Embodied Agents in Crafter. - Junyeong Park; Hyeonseo Cho; Sungjin Ahn (CoRR, 2025)