Aditya Grover
58 papers · 2015–2026 · 12 conferences · across top CS/AI conferences
Achievements
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πΊοΈ Taxonomy Completionist (18) π§ Keyword Pioneer π Renaissance Researcher (5) π Interdisciplinary Bridge π£ Hot Topic Early Bird
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Cross-Pollinator
(14)
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Interdisciplinary Bridge
πΊοΈ
Taxonomy Completionist
(18)
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Deep Specialist
(13)
π§¬
Topic Evolution
π€
Dynamic Duo
(17)
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Triple Crown
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Grand Slam
ποΈ
Keyword Collector
(215)
β‘
Prolific Year
(6)
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Century Club
(56)
π₯
Unstoppable
(8)
Conferences
NIPS (15)
ICML (12)
ICLR (10)
AISTATS (7)
AAAI (3)
ACL (2)
CVPR (2)
ICCV (2)
IJCAI (2)
EACL (1)
ECCV (1)
NAACL (1)
Top co-authors
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
The Pitfalls of KV Cache Compression
ACL 2026
Comparing Bad Apples to Good Oranges Aligning Large Language Models via Joint Preference Optimization
ACL 2025
Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models
AISTATS 2025
LICO: Large Language Models for In-Context Molecular Optimization
ICLR 2025
OmniFlow: Any-to-Any Generation with Multi-Modal Rectified Flows
CVPR 2025
VideoPhy: Evaluating Physical Commonsense for Video Generation
ICLR 2025
Reflect-DiT: Inference-Time Scaling for Text-to-Image Diffusion Transformers via In-Context Reflection
ICCV 2025
InstructAny2Pix: Image Editing with Multi-Modal Prompts
NAACL 2025
Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models
ICLR 2024
VideoCon: Robust Video-Language Alignment via Contrast Captions
CVPR 2024
Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data
ECCV 2024
ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction
NIPS 2024
Scaling transformer neural networks for skillful and reliable medium-range weather forecasting
NIPS 2024
Group Preference Optimization: Few-Shot Alignment of Large Language Models
ICLR 2024
Probing the Decision Boundaries of In-context Learning in Large Language Models
NIPS 2024
Generative Pretraining for Black-Box Optimization
ICML 2023
ExPT: Synthetic Pretraining for Few-Shot Experimental Design
NIPS 2023
ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling
NIPS 2023
Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models
NIPS 2023
Generative Decision Making Under Uncertainty
AAAI 2023
CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning
ICCV 2023
Scaling Pareto-Efficient Decision Making via Offline Multi-Objective RL
ICLR 2023
Diffusion Models for Black-Box Optimization
ICML 2023
ClimaX: A foundation model for weather and climate
ICML 2023
Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories
ICML 2023
Frame Averaging for Invariant and Equivariant Network Design
ICLR 2022
Frozen Pretrained Transformers as Universal Computation Engines
AAAI 2022
CyCLIP: Cyclic Contrastive Language-Image Pretraining
NIPS 2022
Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling
ICML 2022
Masked Autoencoding for Scalable and Generalizable Decision Making
NIPS 2022
Matching Normalizing Flows and Probability Paths on Manifolds
ICML 2022
Online Decision Transformer
ICML 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
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery
NIPS 2021
Reset-Free Lifelong Learning with Skill-Space Planning
ICLR 2021
Anytime Sampling for Autoregressive Models via Ordered Autoencoding
ICLR 2021
PiRank: Scalable Learning To Rank via Differentiable Sorting
NIPS 2021
Moser Flow: Divergence-based Generative Modeling on Manifolds
NIPS 2021
Decision Transformer: Reinforcement Learning via Sequence Modeling
NIPS 2021
Permutation Invariant Graph Generation via Score-Based Generative Modeling
AISTATS 2020
AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows
AAAI 2020
Fair Generative Modeling via Weak Supervision
ICML 2020
Graphite: Iterative Generative Modeling of Graphs
ICML 2019
Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization
AISTATS 2019
Stochastic Optimization of Sorting Networks via Continuous Relaxations
ICLR 2019
Learning Controllable Fair Representations
AISTATS 2019
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting
NIPS 2019
Neural Joint Source-Channel Coding
ICML 2019
Best arm identification in multi-armed bandits with delayed feedback
AISTATS 2018
Modeling Sparse Deviations for Compressed Sensing using Generative Models
ICML 2018
Learning Policy Representations in Multiagent Systems
ICML 2018
Streamlining Variational Inference for Constraint Satisfaction Problems
NIPS 2018
Variational Rejection Sampling
AISTATS 2018
Contextual Symmetries in Probabilistic Graphical Models
IJCAI 2016
Variational Bayes on Monte Carlo Steroids
NIPS 2016
ASAP-UCT: Abstraction of State-Action Pairs in UCT
IJCAI 2015