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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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05/04/2023
AutoML-GPT: Automatic Machine Learning with GPT
AI tasks encompass a wide range of domains and fields. While numerous AI...
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04/29/2023
POUF: Prompt-oriented unsupervised fine-tuning for large pre-trained models
Through prompting, large-scale pre-trained models have become more expre...
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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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02/08/2023
A Prototype-Oriented Clustering for Domain Shift with Source Privacy
Unsupervised clustering under domain shift (UCDS) studies how to transfe...
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11/02/2022
Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models
Retriever-reader models achieve competitive performance across many diff...
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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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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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05/10/2022
ALLSH: Active Learning Guided by Local Sensitivity and Hardness
Active learning, which effectively collects informative unlabeled data f...
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12/02/2021
FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimization
Generating images from natural language instructions is an intriguing ye...
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10/25/2021
Alignment Attention by Matching Key and Query Distributions
The neural attention mechanism has been incorporated into deep neural ne...
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09/09/2021
Learning with Different Amounts of Annotation: From Zero to Many Labels
Training NLP systems typically assumes access to annotated data that has...
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06/09/2021
Bayesian Attention Belief Networks
Attention-based neural networks have achieved state-of-the-art results o...
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06/02/2021
Knowing More About Questions Can Help: Improving Calibration in Question Answering
We study calibration in question answering, estimating whether model cor...
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03/06/2021
Contextual Dropout: An Efficient Sample-Dependent Dropout Module
Dropout has been demonstrated as a simple and effective module to not on...
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02/13/2021
Capturing Label Distribution: A Case Study in NLI
We study estimating inherent human disagreement (annotation label distri...
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10/20/2020