Aditya Grover
Assistant Professor
Leads the MINT group on probabilistic and generative models for representation learning and sequential decision making, with uses in climate and science.
Aditya Grover's lab at UCLA works on reinforcement learning and generative & foundation models. 39 papers since 2023, 36 at top venues, mostly NeurIPS and ICLR. 6 PhD students. 13 alumni. Applications close .
At a glance
- papers, 2023–2026
- 10/ year
- at T1 venues
- 92%
- PhD students
- 6
- MS students
- 0
- alumni listed
- 13
Papers by yearfrom the lab homepage, 2023–2026
- 10 papers2026 · T1 10 · collecting
- 13 papers2025 · T1 10
- 7 papers2024 · T1 7
- 9 papers2023 · T1 9
T1 venuesOtherVenues: NeurIPS, ICLR, ICML, CVPR, ICCV
Research focuspaper titles that use each topic's words
- Generative & foundation models18 papers
- Reinforcement learning8 papers
- climate3 papers
- sequential decision0 papers
- sequential0 papers
Paper list
From the lab homepage.
202610 papers
- CVPR (T1)Honeybee: Data recipes for vision-language reasoners
- ICLR (T1)Inpainting-Guided Policy Optimization for Diffusion Large Language Models
- ICLR (T1)Lavida-O: Elastic Large Masked Diffusion Models for Unified Multimodal Understanding and Generation
- ICML (T1)LaViDa-R1: Advancing Reasoning for Unified Multimodal Diffusion Language Models
- ICLR (T1)OpenThoughts: Data Recipes for Reasoning Models
- ICLR (T1)Planned Diffusion
- ICML (T1)Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models
- CVPR (T1)Sparse-LaViDa: Sparse Multimodal Discrete Diffusion Language Models
- ACL (T1)The Pitfalls of KV Cache Compression
- ICLR (T1)Videophy-2: A challenging action-centric physical commonsense evaluation in video generation
202513 papers
- NeurIPS (T1)Accelerating Diffusion LLMs via Adaptive Parallel Decoding
- NeurIPS (T1)d1: Scaling reasoning in diffusion large language models via reinforcement learning
- NeurIPS (T1)Lavida: A large diffusion language model for multimodal understanding
- ICLR (T1)LICO: Large language models for in-context molecular optimization
- NeurIPS (T1)MedMax: Mixed-Modal Instruction Tuning for Training Biomedical Assistants
- NeurIPS (T1)OmniCast: A Masked Latent Diffusion Model for Weather Forecasting Across Time Scales
- CVPR (T1)OmniFlow: Any-to-Any Generation with Multi-Modal Rectified Flows
- RLCOnline intrinsic rewards for decision making agents from large language model feedback
- COLMPredGen: Accelerated Inference of Large Language Models through Input-Time Speculation for Real-Time Speech Interaction
- AISTATS (T1)Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models
- ICCV (T1)Reflect-DiT: Inference-Time Scaling for Text-to-Image Diffusion Transformers via In-Context Reflection
- ICLR (T1)VideoPhy: Evaluating Physical Commonsense for Video Generation
20247 papers
- NeurIPS (T1)ChaosBench: A multi-channel, physics-based benchmark for subseasonal-to-seasonal climate prediction
- ICLR (T1)Group Preference Optimization: Few-Shot Alignment of Large Language Models
- ECCV (T1)Mamba-nd: Selective state space modeling for multi-dimensional data
- ICLR (T1)Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models
- NeurIPS (T1)Probing the Decision Boundaries of In-context Learning in Large Language Models
- NeurIPS (T1)Scaling transformer neural networks for skillful and reliable medium-range weather forecasting
- CVPR (T1)VideoCon: Robust Video-Language Alignment via Contrast Captions
20239 papers
- ICCV (T1)CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning
- NeurIPS (T1)ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling
- ICML (T1)ClimaX: A foundation model for weather and climate
- NeurIPS (T1)Decision Stacks: Flexible Reinforcment Learning Via Modular Generative Models
- ICML (T1)Diffusion Models for Offline Black-Box Optimization
- NeurIPS (T1)ExPT: Synthetic Pretraining for Few-Shot Experimental Design
- ICML (T1)Generative Pretraining for Black-box Optimization
- ICLR (T1)Scaling Pareto-Efficient Decision Making via Offline Multi-Objective RL
- ICML (T1)Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories
Where alumni went13 listed
Apply to UCLAFall 2027
Computer Science PhD
- Round
- Single round (Dec 15)
- Opens
- —
- GRE
- optional
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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