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08/11/2023
BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents
The massive successes of large language models (LLMs) encourage the emer...
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08/04/2023
Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization
Recent months have seen the emergence of a powerful new trend in which l...
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07/18/2023
REX: Rapid Exploration and eXploitation for AI Agents
In this paper, we propose an enhanced approach for Rapid Exploration and...
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06/06/2023
FAMO: Fast Adaptive Multitask Optimization
One of the grand enduring goals of AI is to create generalist agents tha...
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06/05/2023
LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
Lifelong learning offers a promising paradigm of building a generalist a...
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06/01/2023
Preference-grounded Token-level Guidance for Language Model Fine-tuning
Aligning language models (LMs) with preferences is an important problem ...
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05/18/2023
UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild
Achieving machine autonomy and human control often represent divergent o...
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03/16/2023
HIVE: Harnessing Human Feedback for Instructional Visual Editing
Incorporating human feedback has been shown to be crucial to align text ...
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02/20/2023
Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems
When learning task-oriented dialogue (ToD) agents, reinforcement learnin...
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10/12/2022
A Unified Framework for Alternating Offline Model Training and Policy Learning
In offline model-based reinforcement learning (offline MBRL), we learn a...
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08/17/2022
Metric Residual Networks for Sample Efficient Goal-Conditioned Reinforcement Learning
Goal-conditioned reinforcement learning (GCRL) has a wide range of poten...
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06/14/2022
Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning
Offline reinforcement learning (RL) extends the paradigm of classical RL...
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02/19/2022
A Regularized Implicit Policy for Offline Reinforcement Learning
Offline reinforcement learning enables learning from a fixed dataset, wi...
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01/01/2022
Operator Deep Q-Learning: Zero-Shot Reward Transferring in Reinforcement Learning
Reinforcement learning (RL) has drawn increasing interests in recent yea...
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06/02/2021
Unsupervised Out-of-Domain Detection via Pre-trained Transformers
Deployed real-world machine learning applications are often subject to u...
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04/24/2021
Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System
Text classification is usually studied by labeling natural language text...
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03/09/2021
Non-asymptotic Confidence Intervals of Off-policy Evaluation: Primal and Dual Bounds
Off-policy evaluation (OPE) is the task of estimating the expected rewar...
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10/29/2020
Off-Policy Interval Estimation with Lipschitz Value Iteration
Off-policy evaluation provides an essential tool for evaluating the effe...
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08/15/2020
Accountable Off-Policy Evaluation With Kernel Bellman Statistics
We consider off-policy evaluation (OPE), which evaluates the performance...
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10/16/2019
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation
Infinite horizon off-policy policy evaluation is a highly challenging ta...
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05/25/2019
A Kernel Loss for Solving the Bellman Equation
Value function learning plays a central role in many state-of-the-art re...
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09/29/2018
Knowledge-guided Semantic Computing Network
It is very useful to integrate human knowledge and experience into tradi...
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10/30/2017
Sample-efficient Policy Optimization with Stein Control Variate
Policy gradient methods have achieved remarkable successes in solving ch...
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07/20/2017