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07/05/2023
Exploring Continual Learning for Code Generation Models
Large-scale code generation models such as Codex and CodeT5 have achieve...
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06/29/2023
Sampling weights of deep neural networks
We introduce a probability distribution, combined with an efficient samp...
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03/09/2023
Greener yet Powerful: Taming Large Code Generation Models with Quantization
ML-powered code generation aims to assist developers to write code in a ...
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10/26/2022
Multi-lingual Evaluation of Code Generation Models
We present MBXP, an execution-based code completion benchmark in 10+ pro...
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09/25/2022
Exploring Example Influence in Continual Learning
Continual Learning (CL) sequentially learns new tasks like human beings,...
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04/13/2022
Learning to Revise References for Faithful Summarization
In many real-world scenarios with naturally occurring datasets, referenc...
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05/27/2021
Neural Entity Recognition with Gazetteer based Fusion
Incorporating external knowledge into Named Entity Recognition (NER) sys...
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10/01/2020
An Empirical Investigation Towards Efficient Multi-Domain Language Model Pre-training
Pre-training large language models has become a standard in the natural ...
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08/23/2020
Learn to Talk via Proactive Knowledge Transfer
Knowledge Transfer has been applied in solving a wide variety of problem...
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05/24/2017
Bidirectional Beam Search: Forward-Backward Inference in Neural Sequence Models for Fill-in-the-Blank Image Captioning
We develop the first approximate inference algorithm for 1-Best (and M-B...
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10/07/2016