Chelsea Finn
190 papers · 2016–2025 · 13 conferences · across top CS/AI conferences
Achievements
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πΊοΈ Taxonomy Completionist (24) π§ Keyword Pioneer π Renaissance Researcher (5) π Interdisciplinary Bridge π£ Hot Topic Early Bird
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Academic Marathon
(9)
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Renaissance Researcher
(5)
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Interdisciplinary Bridge
π
Conference Loyalist
(40)
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Keyword Trendsetter Combo
(9)
π€
Dynamic Duo
(90)
π
Triple Crown
π±
Topic Pioneer
π
Keyword Champion
(2)
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Grand Slam
π₯
Mega-Team
(98)
π¬
Deep Specialist
(44)
π
Trend Setter
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Conference Pioneer
π₯
Unstoppable
(10)
β
The Questioner
(2)
π
Century Club
(190)
ποΈ
Keyword Collector
(75)
β‘
Prolific Year
(31)
Conferences
NIPS (42)
CORL (40)
ICLR (39)
ICML (31)
RSS (21)
CVPR (4)
EMNLP (4)
L4DC (3)
JMLR (2)
AAAI (1)
ACL (1)
COLING (1)
ECCV (1)
Top co-authors
Research topics
Keywords
reinforcement learning
(21)
imitation learning
(20)
offline reinforcement learning
(19)
representation learning
(15)
robotic manipulation
(14)
robot manipulation
(14)
multi-task learning
(13)
few-shot learning
(11)
model-based reinforcement learning
(9)
domain generalization
(7)
large language model
(7)
distribution shift
(7)
continual learning
(6)
reward function
(6)
meta-reinforcement learning
(6)
contrastive learning
(5)
latent variable model
(5)
self-supervised learning
(5)
domain adaptation
(5)
sample efficiency
(5)
Papers
Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval
ICLR 2025
CoT-VLA: Visual Chain-of-Thought Reasoning for Vision-Language-Action Models
CVPR 2025
Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
RSS 2025
FAST: Efficient Action Tokenization for Vision-Language-Action Models
RSS 2025
PERSONA: A Reproducible Testbed for Pluralistic Alignment
COLING 2025
Bidirectional Decoding: Improving Action Chunking via Guided Test-Time Sampling
ICLR 2025
Range, not Independence, Drives Modularity in Biologically Inspired Representations
ICLR 2025
$\pi_0.5$: a Vision-Language-Action Model with Open-World Generalization
CORL 2025
Learning Long-Context Diffusion Policies via Past-Token Prediction
CORL 2025
Curating Demonstrations using Online Experience
RSS 2025
Οβ: A Vision-Language-Action Flow Model for General Robot Control
RSS 2025
RoboArena: Distributed Real-World Evaluation of Generalist Robot Policies
CORL 2025
Latent Diffusion Planning for Imitation Learning
ICML 2025
Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models
ICML 2025
Calibrating Language Models with Adaptive Temperature Scaling
EMNLP 2024
Surgical Robot Transformer (SRT): Imitation Learning for Surgical Tasks
CORL 2024
ALOHA Unleashed: A Simple Recipe for Robot Dexterity
CORL 2024
OpenVLA: An Open-Source Vision-Language-Action Model
CORL 2024
HumanPlus: Humanoid Shadowing and Imitation from Humans
CORL 2024
Robotic Control via Embodied Chain-of-Thought Reasoning
CORL 2024
Evaluating Real-World Robot Manipulation Policies in Simulation
CORL 2024
Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning
ICML 2024
PIGEON: Predicting Image Geolocations
CVPR 2024
Disentangling Length from Quality in Direct Preference Optimization
ACL 2024
Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigation
RSS 2024
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
RSS 2024
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
ICLR 2024
An Emulator for Fine-tuning Large Language Models using Small Language Models
ICLR 2024
Language Model Detectors Are Easily Optimized Against
ICLR 2024
A Critical Evaluation of AI Feedback for Aligning Large Language Models
NIPS 2024
Universal Neural Functionals
NIPS 2024
Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms
NIPS 2024
Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models
ICLR 2024
Learning to Explore in POMDPs with Informational Rewards
ICML 2024
Efficient imitation learning with conservative world models
L4DC 2024
Fine-Tuning Language Models for Factuality
ICLR 2024
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
ICML 2024
Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data
ICML 2024
RLVF: Learning from Verbal Feedback without Overgeneralization
ICML 2024
Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning
ICLR 2024
RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches
ICLR 2024
Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features
ICLR 2024
What Makes Pre-Trained Visual Representations Successful for Robust Manipulation?
CORL 2024
Mobile ALOHA: Learning Bimanual Mobile Manipulation using Low-Cost Whole-Body Teleoperation
CORL 2024
Improving Domain Generalization with Domain Relations
ICLR 2024
Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning
ICLR 2024
Octo: An Open-Source Generalist Robot Policy
RSS 2024
Yell At Your Robot: Improving On-the-Fly from Language Corrections
RSS 2024
Efficient Data Collection for Robotic Manipulation via Compositional Generalization
RSS 2024
Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs
CORL 2024
Open-World Object Manipulation using Pre-Trained Vision-Language Models
CORL 2023
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts
ICLR 2023
A Control-Centric Benchmark for Video Prediction
ICLR 2023
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts
ICLR 2023
Diversify and Disambiguate: Out-of-Distribution Robustness via Disagreement
ICLR 2023
Language-Driven Representation Learning for Robotics
RSS 2023
Permutation Equivariant Neural Functionals
NIPS 2023
Supervised Pretraining Can Learn In-Context Reinforcement Learning
NIPS 2023
Disentanglement via Latent Quantization
NIPS 2023
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
NIPS 2023
RoboCLIP: One Demonstration is Enough to Learn Robot Policies
NIPS 2023
Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning
NIPS 2023
Neural Functional Transformers
NIPS 2023
Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets
RSS 2023
Contrastive Example-Based Control
L4DC 2023
RT-1: Robotics Transformer for Real-World Control at Scale
RSS 2023
Pre-Training for Robots: Offline RL Enables Learning New Tasks in a Handful of Trials
RSS 2023
Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware
RSS 2023
Robot Parkour Learning
CORL 2023
BridgeData V2: A Dataset for Robot Learning at Scale
CORL 2023
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
CORL 2023
Waypoint-Based Imitation Learning for Robotic Manipulation
CORL 2023
Polybot: Training One Policy Across Robots While Embracing Variability
CORL 2023
Self-Improving Robots: End-to-End Autonomous Visuomotor Reinforcement Learning
CORL 2023
MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning
CORL 2023
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions
CORL 2023
NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesis
CVPR 2023
Meta-Learning Online Adaptation of Language Models
EMNLP 2023
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback
EMNLP 2023
DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature
ICML 2023
Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning
ICML 2023
Play it by Ear: Learning Skills amidst Occlusion through Audio-Visual Imitation Learning
RSS 2022
Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets
RSS 2022
MEMO: Test Time Robustness via Adaptation and Augmentation
NIPS 2022
LAPO: Latent-Variable Advantage-Weighted Policy Optimization for Offline Reinforcement Learning
NIPS 2022
Giving Feedback on Interactive Student Programs with Meta-Exploration
NIPS 2022
Vision-Based Manipulators Need to Also See from Their Hands
ICLR 2022
Learning Options via Compression
NIPS 2022
When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning
NIPS 2022
You Only Live Once: Single-Life Reinforcement Learning
NIPS 2022
Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference
EMNLP 2022
Extending the WILDS Benchmark for Unsupervised Adaptation
ICLR 2022
Do deep networks transfer invariances across classes?
ICLR 2022
Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time
NIPS 2022
Autonomous Reinforcement Learning: Formalism and Benchmarking
ICLR 2022
Fast Model Editing at Scale
ICLR 2022
Correct-N-Contrast: a Contrastive Approach for Improving Robustness to Spurious Correlations
ICML 2022
How to Leverage Unlabeled Data in Offline Reinforcement Learning
ICML 2022
Improving Out-of-Distribution Robustness via Selective Augmentation
ICML 2022
Robust Policy Learning over Multiple Uncertainty Sets
ICML 2022
A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning
ICML 2022
Memory-Based Model Editing at Scale
ICML 2022
C-Mixup: Improving Generalization in Regression
NIPS 2022
Meta-Learning with Fewer Tasks through Task Interpolation
ICLR 2022
CoMPS: Continual Meta Policy Search
ICLR 2022
Offline Reinforcement Learning at Multiple Frequencies
CORL 2022
R3M: A Universal Visual Representation for Robot Manipulation
CORL 2022
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
CORL 2022
Training and Evaluation of Deep Policies Using Reinforcement Learning and Generative Models
JMLR 2022
Offline Reinforcement Learning from Images with Latent Space Models
L4DC 2021
Visual Adversarial Imitation Learning using Variational Models
NIPS 2021
Meta-learning with an Adaptive Task Scheduler
NIPS 2021
Information is Power: Intrinsic Control via Information Capture
NIPS 2021
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning
NIPS 2021
Noether Networks: meta-learning useful conserved quantities
NIPS 2021
Autonomous Reinforcement Learning via Subgoal Curricula
NIPS 2021
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise
NIPS 2021
Adaptive Risk Minimization: Learning to Adapt to Domain Shift
NIPS 2021
Efficiently Identifying Task Groupings for Multi-Task Learning
NIPS 2021
COMBO: Conservative Offline Model-Based Policy Optimization
NIPS 2021
Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks
CORL 2021
A Workflow for Offline Model-Free Robotic Reinforcement Learning
CORL 2021
Scaling Up Multi-Task Robotic Reinforcement Learning
CORL 2021
BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning
CORL 2021
Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotation
CORL 2021
Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction
CVPR 2021
Meta-learning Symmetries by Reparameterization
ICLR 2021
SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments
ICLR 2021
Model-Based Visual Planning with Self-Supervised Functional Distances
ICLR 2021
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills
ICML 2021
Catformer: Designing Stable Transformers via Sensitivity Analysis
ICML 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts
ICML 2021
Just Train Twice: Improving Group Robustness without Training Group Information
ICML 2021
Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices
ICML 2021
Offline Meta-Reinforcement Learning with Advantage Weighting
ICML 2021
Deep Reinforcement Learning amidst Continual Structured Non-Stationarity
ICML 2021
Learning Generalizable Robotic Reward Functions from βIn-The-Wildβ Human Videos
RSS 2021
Model Based Reinforcement Learning for Atari
ICLR 2020
On the Expressivity of Neural Networks for Deep Reinforcement Learning
ICML 2020
Goal-Aware Prediction: Learning to Model What Matters
ICML 2020
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings
ICML 2020
Continual Learning of Control Primitives : Skill Discovery via Reset-Games
NIPS 2020
Weakly-Supervised Reinforcement Learning for Controllable Behavior
NIPS 2020
Learning Predictive Models from Observation and Interaction
ECCV 2020
Learning to Interactively Learn and Assist
AAAI 2020
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning
CORL 2020
MELD: Meta-Reinforcement Learning from Images via Latent State Models
CORL 2020
Learning Latent Representations to Influence Multi-Agent Interaction
CORL 2020
Reinforcement Learning with Videos: Combining Offline Observations with Interaction
CORL 2020
Continuous Meta-Learning without Tasks
NIPS 2020
Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors
NIPS 2020
MOPO: Model-based Offline Policy Optimization
NIPS 2020
One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL
NIPS 2020
Gradient Surgery for Multi-Task Learning
NIPS 2020
Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation
ICLR 2020
Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards
ICLR 2020
VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation
ICLR 2020
Meta-Learning without Memorization
ICLR 2020
Unsupervised Learning via Meta-Learning
ICLR 2019
Reasoning About Physical Interactions with Object-Oriented Prediction and Planning
ICLR 2019
Unsupervised Curricula for Visual Meta-Reinforcement Learning
NIPS 2019
Guided Meta-Policy Search
NIPS 2019
Meta-Inverse Reinforcement Learning with Probabilistic Context Variables
NIPS 2019
Language as an Abstraction for Hierarchical Deep Reinforcement Learning
NIPS 2019
Meta-Learning with Implicit Gradients
NIPS 2019
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables
ICML 2019
Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning
ICLR 2019
Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL
ICLR 2019
Online Meta-Learning
ICML 2019
Entity Abstraction in Visual Model-Based Reinforcement Learning
CORL 2019
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
CORL 2019
RoboNet: Large-Scale Multi-Robot Learning
CORL 2019
Learning a Prior over Intent via Meta-Inverse Reinforcement Learning
ICML 2019
Improvisation through Physical Understanding: Using Novel Objects As Tools with Visual Foresight
RSS 2019
Unsupervised Visuomotor Control through Distributional Planning Networks
RSS 2019
End-To-End Robotic Reinforcement Learning without Reward Engineering
RSS 2019
Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm
ICLR 2018
Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning
CORL 2018
Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control
ICML 2018
One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning
RSS 2018
Stochastic Variational Video Prediction
ICLR 2018
Probabilistic Model-Agnostic Meta-Learning
NIPS 2018
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes
ICLR 2018
Few-Shot Goal Inference for Visuomotor Learning and Planning
CORL 2018
One-Shot Visual Imitation Learning via Meta-Learning
CORL 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
ICML 2017
Self-Supervised Visual Planning with Temporal Skip Connections
CORL 2017
End-to-End Training of Deep Visuomotor Policies
JMLR 2016
Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization
ICML 2016
Unsupervised Learning for Physical Interaction through Video Prediction
NIPS 2016