← Authors

Aditya Grover

57 papers · 2015–2026 · 12 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (5) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (11) πŸƒ Academic Marathon (10) 🐝 Cross-Pollinator (14) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (18) πŸ”¬ Deep Specialist (13) 🧬 Topic Evolution 🀝 Dynamic Duo (17) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (215) ⚑ Prolific Year (6) πŸ’Ž Century Club (56) πŸ”₯ Unstoppable (8)

Conferences

NIPS (15) ICML (12) ICLR (10) AISTATS (7) AAAI (3) CVPR (2) ICCV (2) IJCAI (2) ACL (1) EACL (1) ECCV (1) NAACL (1)

Top co-authors

Stefano Ermon (17) Hritik Bansal (8) Tung Nguyen (8) Pieter Abbeel (5) Shufan Li (4) Kai-Wei Chang (4) Siyan Zhao (4) Igor Mordatch (3) Jiaming Song (3) Rui Shu (3)

Keywords

representation learning (6) generative model (6) variational inference (5) offline reinforcement learning (5) autoregressive model (4) reinforcement learning (4) large language model (4) transformer architecture (4) variational autoencoder (3) weather forecasting (3) sequence modeling (3) black-box optimization (3) multi-armed bandit (2) in-context learning (2) density estimation (2) multimodal learning (2) contrastive learning (2) transfer learning (2) approximate inference (2) compressed sensing (2)

Papers

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