Aditya Grover

Enabling Autoregressive Models to Fill In Masked Tokens EACL 2026 HoneyBee: Data Recipes for Vision-Language Reasoners CVPR 2026 Sparse-LaViDa: Sparse Multimodal Discrete Diffusion Language Models CVPR 2026 The Pitfalls of KV Cache Compression ACL 2026 Comparing Bad Apples to Good Oranges Aligning Large Language Models via Joint Preference Optimization ACL 2025 InstructAny2Pix: Image Editing with Multi-Modal Prompts NAACL 2025 LICO: Large Language Models for In-Context Molecular Optimization ICLR 2025 OmniFlow: Any-to-Any Generation with Multi-Modal Rectified Flows CVPR 2025 Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models AISTATS 2025 Reflect-DiT: Inference-Time Scaling for Text-to-Image Diffusion Transformers via In-Context Reflection ICCV 2025 VideoPhy: Evaluating Physical Commonsense for Video Generation ICLR 2025 ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction NeurIPS 2024 Group Preference Optimization: Few-Shot Alignment of Large Language Models ICLR 2024 Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data ECCV 2024 Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models ICLR 2024 Probing the Decision Boundaries of In-context Learning in Large Language Models NeurIPS 2024 Scaling transformer neural networks for skillful and reliable medium-range weather forecasting NeurIPS 2024 VideoCon: Robust Video-Language Alignment via Contrast Captions CVPR 2024 CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning ICCV 2023 ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling NeurIPS 2023 ClimaX: A foundation model for weather and climate ICML 2023 Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models NeurIPS 2023 Diffusion Models for Black-Box Optimization ICML 2023 ExPT: Synthetic Pretraining for Few-Shot Experimental Design NeurIPS 2023 Generative Decision Making Under Uncertainty AAAI 2023 Generative Pretraining for Black-Box Optimization ICML 2023 Scaling Pareto-Efficient Decision Making via Offline Multi-Objective RL ICLR 2023 Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories ICML 2023 CyCLIP: Cyclic Contrastive Language-Image Pretraining NeurIPS 2022 Frame Averaging for Invariant and Equivariant Network Design ICLR 2022 Frozen Pretrained Transformers as Universal Computation Engines AAAI 2022 It Takes Four to Tango: Multiagent Self Play for Automatic Curriculum Generation ICLR 2022 Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits AISTATS 2022 Masked Autoencoding for Scalable and Generalizable Decision Making NeurIPS 2022 Matching Normalizing Flows and Probability Paths on Manifolds ICML 2022 Online Decision Transformer ICML 2022 Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling ICML 2022 Anytime Sampling for Autoregressive Models via Ordered Autoencoding ICLR 2021 BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery NeurIPS 2021 Decision Transformer: Reinforcement Learning via Sequence Modeling NeurIPS 2021 Moser Flow: Divergence-based Generative Modeling on Manifolds NeurIPS 2021 PiRank: Scalable Learning To Rank via Differentiable Sorting NeurIPS 2021 Reset-Free Lifelong Learning with Skill-Space Planning ICLR 2021 AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows AAAI 2020 Fair Generative Modeling via Weak Supervision ICML 2020 Permutation Invariant Graph Generation via Score-Based Generative Modeling AISTATS 2020 Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting NeurIPS 2019 Graphite: Iterative Generative Modeling of Graphs ICML 2019 Learning Controllable Fair Representations AISTATS 2019 Neural Joint Source-Channel Coding ICML 2019 Stochastic Optimization of Sorting Networks via Continuous Relaxations ICLR 2019 Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization AISTATS 2019 Best arm identification in multi-armed bandits with delayed feedback AISTATS 2018 Learning Policy Representations in Multiagent Systems ICML 2018 Modeling Sparse Deviations for Compressed Sensing using Generative Models ICML 2018 Streamlining Variational Inference for Constraint Satisfaction Problems NeurIPS 2018 Variational Rejection Sampling AISTATS 2018 Contextual Symmetries in Probabilistic Graphical Models IJCAI 2016 Variational Bayes on Monte Carlo Steroids NeurIPS 2016 ASAP-UCT: Abstraction of State-Action Pairs in UCT IJCAI 2015