ML Anthology

Grover, Aditya

104 publications

NeurIPS 2025 Accelerating Diffusion LLMs via Adaptive Parallel Decoding Daniel Mingyi Israel, Guy Van den Broeck, Aditya Grover
NeurIPS 2025 D1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning Siyan Zhao, Devaansh Gupta, Qinqing Zheng, Aditya Grover
ICLR 2025 LICO: Large Language Models for In-Context Molecular Optimization Tung Nguyen, Aditya Grover
NeurIPS 2025 LaViDa: A Large Diffusion Language Model for Multimodal Understanding Shufan Li, Konstantinos Kallidromitis, Hritik Bansal, Akash Gokul, Yusuke Kato, Kazuki Kozuka, Jason Kuen, Zhe Lin, Kai-Wei Chang, Aditya Grover
NeurIPS 2025 MedMax: Mixed-Modal Instruction Tuning for Training Biomedical Assistants Hritik Bansal, Daniel Mingyi Israel, Siyan Zhao, Shufan Li, Tung Nguyen, Aditya Grover
NeurIPS 2025 OmniCast: A Masked Latent Diffusion Model for Weather Forecasting Across Time Scales Tung Nguyen, Tuan Pham, Troy Arcomano, Rao Kotamarthi, Ian Foster, Sandeep Madireddy, Aditya Grover
CVPR 2025 OmniFlow: Any-to-Any Generation with Multi-Modal Rectified Flows Shufan Li, Konstantinos Kallidromitis, Akash Gokul, Zichun Liao, Yusuke Kato, Kazuki Kozuka, Aditya Grover
AISTATS 2025 Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models Siyan Zhao, Daniel Mingyi Israel, Guy Van Broeck, Aditya Grover
ICCV 2025 Reflect-DiT: Inference-Time Scaling for Text-to-Image Diffusion Transformers via In-Context Reflection Shufan Li, Konstantinos Kallidromitis, Akash Gokul, Arsh Koneru, Yusuke Kato, Kazuki Kozuka, Aditya Grover
ICLR 2025 VideoPhy: Evaluating Physical Commonsense for Video Generation Hritik Bansal, Zongyu Lin, Tianyi Xie, Zeshun Zong, Michal Yarom, Yonatan Bitton, Chenfanfu Jiang, Yizhou Sun, Kai-Wei Chang, Aditya Grover
ICLRW 2025 WaterFlow: Learning Fast & Robust Watermarks Using Stable Diffusion Vinay Shukla, Prachee Sharma, Ryan A. Rossi, Sungchul Kim, Tong Yu, Aditya Grover
NeurIPSW 2024 AtmosArena: Benchmarking Foundation Models for Atmospheric Sciences Tung Nguyen, Prateik Sinha, Advit Deepak, Karen A. McKinnon, Aditya Grover
NeurIPS 2024 ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction Juan Nathaniel, Yongquan Qu, Tung Nguyen, Sungduk Yu, Julius Busecke, Aditya Grover, Pierre Gentine
ICMLW 2024 Comparing Bad Apples to Good Oranges: Aligning Large Language Models via Joint Preference Optimization Hritik Bansal, Ashima Suvarna, Gantavya Bhatt, Nanyun Peng, Kai-Wei Chang, Aditya Grover
NeurIPSW 2024 Comparing Bad Apples to Good Oranges: Aligning Large Language Models via Joint Preference Optimization Hritik Bansal, Ashima Suvarna, Gantavya Bhatt, Nanyun Peng, Kai-Wei Chang, Aditya Grover
ICMLW 2024 Fast and Memory-Efficient Multi-Sequence Generation via Structured Masking Daniel Mingyi Israel, Siyan Zhao, Guy Van den Broeck, Aditya Grover
ICLR 2024 Group Preference Optimization: Few-Shot Alignment of Large Language Models Siyan Zhao, John Dang, Aditya Grover
ICLRW 2024 Group Preference Optimization: Few-Shot Alignment of Large Language Models Siyan Zhao, John Dang, Aditya Grover
ECCV 2024 Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data Shufan Li, Aditya Grover, Harkanwar Singh
ICLR 2024 Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models Hritik Bansal, John Dang, Aditya Grover
ICLRW 2024 Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models Hritik Bansal, John Dang, Aditya Grover
NeurIPSW 2024 PopAlign: Population-Level Alignment for Fair Text-to-Image Generation Shufan Li, Aditya Grover, Harkanwar Singh
NeurIPSW 2024 PopAlign: Population-Level Alignment for Fair Text-to-Image Generation Shufan Li, Harkanwar Singh, Aditya Grover
ICMLW 2024 Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models Siyan Zhao, Daniel Mingyi Israel, Guy Van den Broeck, Aditya Grover
ICMLW 2024 Probing the Decision Boundaries of In-Context Learning in Large Language Models Siyan Zhao, Tung Nguyen, Aditya Grover
NeurIPS 2024 Probing the Decision Boundaries of In-Context Learning in Large Language Models Siyan Zhao, Tung Nguyen, Aditya Grover
ICMLW 2024 Probing the Decision Boundaries of In-Context Learning in Large Language Models Siyan Zhao, Tung Nguyen, Aditya Grover
NeurIPSW 2024 Probing the Decision Boundaries of In-Context Learning in Large Language Models Siyan Zhao, Tung Nguyen, Aditya Grover
NeurIPSW 2024 Probing the Decision Boundaries of In-Context Learning in Large Language Models Download PDF Siyan Zhao, Tung Nguyen, Aditya Grover
NeurIPS 2024 Scaling Transformer Neural Networks for Skillful and Reliable Medium-Range Weather Forecasting Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Romit Maulik, Veerabhadra Kotamarthi, Ian Foster, Sandeep Madireddy, Aditya Grover
ICLRW 2024 Scaling Transformers for Skillful and Reliable Medium-Range Weather Forecasting Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Sandeep Madireddy, Romit Maulik, Veerabhadra Kotamarthi, Ian Foster, Aditya Grover
TMLR 2024 Scaling Vision-and-Language Navigation with Offline RL Valay Bundele, Mahesh Bhupati, Biplab Banerjee, Aditya Grover
NeurIPSW 2024 TALC: Time-Aligned Captions for Multi-Scene Text-to-Video Generation Hritik Bansal, Yonatan Bitton, Michal Yarom, Idan Szpektor, Aditya Grover, Kai-Wei Chang
CVPR 2024 VideoCon: Robust Video-Language Alignment via Contrast Captions Hritik Bansal, Yonatan Bitton, Idan Szpektor, Kai-Wei Chang, Aditya Grover
ICLRW 2024 VideoCon: Robust Video-Language Alignment via Contrast Captions Hritik Bansal, Yonatan Bitton, Idan Szpektor, Kai-Wei Chang, Aditya Grover
NeurIPSW 2024 VideoPhy: Evaluating Physical Commonsense for Video Generation Hritik Bansal, Zongyu Lin, Tianyi Xie, Zeshun Zong, Michal Yarom, Yonatan Bitton, Chenfanfu Jiang, Yizhou Sun, Kai-Wei Chang, Aditya Grover
ICCV 2023 CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning Hritik Bansal, Nishad Singhi, Yu Yang, Fan Yin, Aditya Grover, Kai-Wei Chang
ICLRW 2023 CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning Hritik Bansal, Nishad Singhi, Yu Yang, Fan Yin, Aditya Grover, Kai-Wei Chang
ICML 2023 ClimaX: A Foundation Model for Weather and Climate Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K Gupta, Aditya Grover
ICMLW 2023 ClimaX: A Foundation Model for Weather and Climate Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K Gupta, Aditya Grover
NeurIPS 2023 ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling Tung Nguyen, Jason Jewik, Hritik Bansal, Prakhar Sharma, Aditya Grover
NeurIPS 2023 Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models Siyan Zhao, Aditya Grover
ICMLW 2023 Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models Siyan Zhao, Aditya Grover
ICMLW 2023 Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models Siyan Zhao, Aditya Grover
ICML 2023 Diffusion Models for Black-Box Optimization Siddarth Krishnamoorthy, Satvik Mehul Mashkaria, Aditya Grover
NeurIPSW 2023 ExPT: Scaling Foundation Models for Experimental Design via Synthetic Pretraining Tung Nguyen, Sudhanshu Agrawal, Aditya Grover
NeurIPS 2023 ExPT: Synthetic Pretraining for Few-Shot Experimental Design Tung Nguyen, Sudhanshu Agrawal, Aditya Grover
NeurIPSW 2023 ExPT: Synthetic Pretraining for Few-Shot Experimental Design Tung Nguyen, Sudhanshu Agrawal, Aditya Grover
NeurIPSW 2023 ExPT: Synthetic Pretraining for Few-Shot Experimental Design Tung Nguyen, Sudhanshu Agrawal, Aditya Grover
NeurIPSW 2023 ExPT: Synthetic Pretraining for Few-Shot Experimental Design Tung Nguyen, Sudhanshu Agrawal, Aditya Grover
NeurIPSW 2023 ExPT: Synthetic Pretraining for Few-Shot Experimental Design Tung Nguyen, Sudhanshu Agrawal, Aditya Grover
AAAI 2023 Generative Decision Making Under Uncertainty Aditya Grover
ICML 2023 Generative Pretraining for Black-Box Optimization Satvik Mehul Mashkaria, Siddarth Krishnamoorthy, Aditya Grover
NeurIPSW 2023 Group Preference Optimization: Few-Shot Alignment of Large Language Models Siyan Zhao, John Dang, Aditya Grover
NeurIPSW 2023 Group Preference Optimization: Few-Shot Alignment of Large Language Models Siyan Zhao, John Dang, Aditya Grover
ICLRW 2023 Leaving Reality to Imagination: Robust Classification via Generated Datasets Hritik Bansal, Aditya Grover
ICMLW 2023 Leaving Reality to Imagination: Robust Classification via Generated Datasets Hritik Bansal, Aditya Grover
ICLR 2023 Scaling Pareto-Efficient Decision Making via Offline Multi-Objective RL Baiting Zhu, Meihua Dang, Aditya Grover
ICML 2023 Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories Qinqing Zheng, Mikael Henaff, Brandon Amos, Aditya Grover
ICLRW 2023 Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories Qinqing Zheng, Mikael Henaff, Brandon Amos, Aditya Grover
AISTATS 2022 Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits Wenshuo Guo, Kumar Krishna Agrawal, Aditya Grover, Vidya K. Muthukumar, Ashwin Pananjady
ICMLW 2022 BARACK: Partially Supervised Group Robustness with Guarantees Nimit Sharad Sohoni, Maziar Sanjabi, Nicolas Ballas, Aditya Grover, Shaoliang Nie, Hamed Firooz, Christopher Re
NeurIPSW 2022 Conditioned Spatial Downscaling of Climate Variables Alex Hung, Evan Becker, Ted Zadouri, Aditya Grover
NeurIPSW 2022 ConserWeightive Behavioral Cloning for Reliable Offline Reinforcement Learning Tung Nguyen, Qinqing Zheng, Aditya Grover
TMLR 2022 Controllable Generative Modeling via Causal Reasoning Joey Bose, Ricardo Pio Monti, Aditya Grover
NeurIPS 2022 CyCLIP: Cyclic Contrastive Language-Image Pretraining Shashank Goel, Hritik Bansal, Sumit Bhatia, Ryan Rossi, Vishwa Vinay, Aditya Grover
ICLR 2022 Frame Averaging for Invariant and Equivariant Network Design Omri Puny, Matan Atzmon, Edward J. Smith, Ishan Misra, Aditya Grover, Heli Ben-Hamu, Yaron Lipman
AAAI 2022 Frozen Pretrained Transformers as Universal Computation Engines Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch
NeurIPSW 2022 Generative Pretraining for Black-Box Optimization Siddarth Krishnamoorthy, Satvik Mehul Mashkaria, Aditya Grover
ICLR 2022 It Takes Four to Tango: Multiagent Self Play for Automatic Curriculum Generation Yuqing Du, Pieter Abbeel, Aditya Grover
NeurIPS 2022 Masked Autoencoding for Scalable and Generalizable Decision Making Fangchen Liu, Hao Liu, Aditya Grover, Pieter Abbeel
ICML 2022 Matching Normalizing Flows and Probability Paths on Manifolds Heli Ben-Hamu, Samuel Cohen, Joey Bose, Brandon Amos, Maximillian Nickel, Aditya Grover, Ricky T. Q. Chen, Yaron Lipman
ICML 2022 Online Decision Transformer Qinqing Zheng, Amy Zhang, Aditya Grover
NeurIPSW 2022 Pareto-Efficient Decision Agents for Offline Multi-Objective Reinforcement Learning Baiting Zhu, Meihua Dang, Aditya Grover
NeurIPSW 2022 Pareto-Efficient Decision Agents for Offline Multi-Objective Reinforcement Learning Baiting Zhu, Meihua Dang, Aditya Grover
ICML 2022 Transformer Neural Processes: Uncertainty-Aware Meta Learning via Sequence Modeling Tung Nguyen, Aditya Grover
ICLR 2021 Anytime Sampling for Autoregressive Models via Ordered Autoencoding Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon
NeurIPS 2021 BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery Chris Cundy, Aditya Grover, Stefano Ermon
NeurIPS 2021 Decision Transformer: Reinforcement Learning via Sequence Modeling Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Misha Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch
ICMLW 2021 Decision Transformer: Reinforcement Learning via Sequence Modeling Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch
NeurIPS 2021 Moser Flow: Divergence-Based Generative Modeling on Manifolds Noam Rozen, Aditya Grover, Maximilian Nickel, Yaron Lipman
NeurIPS 2021 PiRank: Scalable Learning to Rank via Differentiable Sorting Robin Swezey, Aditya Grover, Bruno Charron, Stefano Ermon
ICLR 2021 Reset-Free Lifelong Learning with Skill-Space Planning Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch
AAAI 2020 AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows Aditya Grover, Christopher Chute, Rui Shu, Zhangjie Cao, Stefano Ermon
ICML 2020 Fair Generative Modeling via Weak Supervision Kristy Choi, Aditya Grover, Trisha Singh, Rui Shu, Stefano Ermon
AISTATS 2020 Permutation Invariant Graph Generation via Score-Based Generative Modeling Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, Stefano Ermon
ICLRW 2019 AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows Aditya Grover, Christopher Chute, Rui Shu, Zhangjie Cao, Stefano Ermon
NeurIPS 2019 Bias Correction of Learned Generative Models Using Likelihood-Free Importance Weighting Aditya Grover, Jiaming Song, Ashish Kapoor, Kenneth Tran, Alekh Agarwal, Eric J Horvitz, Stefano Ermon
ICLRW 2019 Bias Correction of Learned Generative Models via Likelihood-Free Importance Weighting Aditya Grover, Jiaming Song, Ashish Kapoor, Kenneth Tran, Alekh Agarwal, Eric Horvitz, Stefano Ermon
ICML 2019 Graphite: Iterative Generative Modeling of Graphs Aditya Grover, Aaron Zweig, Stefano Ermon
AISTATS 2019 Learning Controllable Fair Representations Jiaming Song, Pratyusha Kalluri, Aditya Grover, Shengjia Zhao, Stefano Ermon
ICML 2019 Neural Joint Source-Channel Coding Kristy Choi, Kedar Tatwawadi, Aditya Grover, Tsachy Weissman, Stefano Ermon
ICLR 2019 Stochastic Optimization of Sorting Networks via Continuous Relaxations Aditya Grover, Eric Wang, Aaron Zweig, Stefano Ermon
AISTATS 2019 Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization Aditya Grover, Stefano Ermon
AISTATS 2018 Best Arm Identification in Multi-Armed Bandits with Delayed Feedback Aditya Grover, Todor M. Markov, Peter M. Attia, Norman Jin, Nicolas Perkins, Bryan Cheong, Michael H. Chen, Zi Yang, Stephen J. Harris, William C. Chueh, Stefano Ermon
AAAI 2018 Boosted Generative Models Aditya Grover, Stefano Ermon
AAAI 2018 Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models Aditya Grover, Manik Dhar, Stefano Ermon
ICML 2018 Learning Policy Representations in Multiagent Systems Aditya Grover, Maruan Al-Shedivat, Jayesh Gupta, Yuri Burda, Harrison Edwards
ICML 2018 Modeling Sparse Deviations for Compressed Sensing Using Generative Models Manik Dhar, Aditya Grover, Stefano Ermon
NeurIPS 2018 Streamlining Variational Inference for Constraint Satisfaction Problems Aditya Grover, Tudor Achim, Stefano Ermon
AISTATS 2018 Variational Rejection Sampling Aditya Grover, Ramki Gummadi, Miguel Lázaro-Gredilla, Dale Schuurmans, Stefano Ermon
IJCAI 2016 Contextual Symmetries in Probabilistic Graphical Models Ankit Anand, Aditya Grover, Mausam, Parag Singla
NeurIPS 2016 Variational Bayes on Monte Carlo Steroids Aditya Grover, Stefano Ermon
IJCAI 2015 ASAP-UCT: Abstraction of State-Action Pairs in UCT Ankit Anand, Aditya Grover, Mausam, Parag Singla