← Authors

Chelsea Finn

190 papers · 2016–2025 · 13 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (14) 🧭 Keyword Pioneer 🌍 Conference Polyglot (13) πŸ—ΊοΈ Taxonomy Completionist (24) 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (9) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🏠 Conference Loyalist (40) 🌟 Keyword Trendsetter Combo (9) 🀝 Dynamic Duo (90) πŸ‘‘ Triple Crown 🌱 Topic Pioneer πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ‘₯ Mega-Team (98) πŸ”¬ Deep Specialist (44) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (10) ❓ The Questioner (2) πŸ’Ž Century Club (190) πŸ—ƒοΈ Keyword Collector (75) ⚑ 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

Sergey Levine (90) Tianhe Yu (21) Karol Hausman (21) Rafael Rafailov (18) Archit Sharma (17) Suraj Nair (17) Karl Pertsch (16) Quan Vuong (15) Eric Mitchell (15) Annie Xie (14)

Research topics

Reinforcement Learning (1) Systems (1) Education (1)

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
Ο€β‚€: 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 β€œIn-The-Wild” 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