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07/18/2023
Multi-Stage Cable Routing through Hierarchical Imitation Learning
We study the problem of learning to perform multi-stage robotic manipula...
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05/25/2023
The False Promise of Imitating Proprietary LLMs
An emerging method to cheaply improve a weaker language model is to fine...
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11/28/2022
Offline Q-Learning on Diverse Multi-Task Data Both Scales And Generalizes
The potential of offline reinforcement learning (RL) is that high-capaci...
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10/24/2022
FCM: Forgetful Causal Masking Makes Causal Language Models Better Zero-Shot Learners
Large language models (LLM) trained using the next-token-prediction obje...
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05/27/2022
Multimodal Masked Autoencoders Learn Transferable Representations
Building scalable models to learn from diverse, multimodal data remains ...
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02/17/2022
Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization
Black-box model-based optimization (MBO) problems, where the goal is to ...
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07/14/2021
Conservative Objective Models for Effective Offline Model-Based Optimization
Computational design problems arise in a number of settings, from synthe...
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12/14/2020
Variable-Shot Adaptation for Online Meta-Learning
Few-shot meta-learning methods consider the problem of learning new task...
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06/12/2020
Meta-Reinforcement Learning Robust to Distributional Shift via Model Identification and Experience Relabeling
Reinforcement learning algorithms can acquire policies for complex tasks...
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02/25/2020
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement
Multi-task reinforcement learning (RL) aims to simultaneously learn poli...
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07/18/2019
Dynamical Distance Learning for Unsupervised and Semi-Supervised Skill Discovery
Reinforcement learning requires manual specification of a reward functio...
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05/17/2017
Automatic Goal Generation for Reinforcement Learning Agents
Reinforcement learning is a powerful technique to train an agent to perf...
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05/08/2017
