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11/14/2022
SPE: Symmetrical Prompt Enhancement for Fact Probing
Pretrained language models (PLMs) have been shown to accumulate factual ...
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06/26/2022
Your Autoregressive Generative Model Can be Better If You Treat It as an Energy-Based One
Autoregressive generative models are commonly used, especially for those...
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06/08/2022
Sparse Fusion Mixture-of-Experts are Domain Generalizable Learners
Domain generalization (DG) aims at learning generalizable models under d...
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07/27/2021
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
Confidence calibration is of great importance to the reliability of deci...
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06/11/2021
Invariant Information Bottleneck for Domain Generalization
The main challenge for domain generalization (DG) is to overcome the pot...
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10/09/2020
Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation
The success of supervised learning hinges on the assumption that the tra...
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06/23/2020
Rethinking Distributional Matching Based Domain Adaptation
Domain adaptation (DA) is a technique that transfers predictive models t...
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09/16/2019