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07/05/2023
OpenDelta: A Plug-and-play Library for Parameter-efficient Adaptation of Pre-trained Models
The scale of large pre-trained models (PTMs) poses significant challenge...
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07/05/2023
Won't Get Fooled Again: Answering Questions with False Premises
Pre-trained language models (PLMs) have shown unprecedented potential in...
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06/04/2023
Arbitrary Few Parameters are Good Enough for Adapting Large-scale Pre-trained Language Models
Parameter-efficient tuning (PET) methods can effectively drive extremely...
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05/31/2023
Exploring Lottery Prompts for Pre-trained Language Models
Consistently scaling pre-trained language models (PLMs) imposes substant...
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05/23/2023
Enhancing Chat Language Models by Scaling High-quality Instructional Conversations
Fine-tuning on instruction data has been widely validated as an effectiv...
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04/17/2023
Tool Learning with Foundation Models
Humans possess an extraordinary ability to create and utilize tools, all...
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04/08/2023
Decoder-Only or Encoder-Decoder? Interpreting Language Model as a Regularized Encoder-Decoder
The sequence-to-sequence (seq2seq) task aims at generating the target se...
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06/15/2022
Sparse Structure Search for Parameter-Efficient Tuning
Adapting large pre-trained models (PTMs) through fine-tuning imposes pro...
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03/18/2022
Prototypical Verbalizer for Prompt-based Few-shot Tuning
Prompt-based tuning for pre-trained language models (PLMs) has shown its...
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11/03/2021
OpenPrompt: An Open-source Framework for Prompt-learning
Prompt-learning has become a new paradigm in modern natural language pro...
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08/04/2021
Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification
Tuning pre-trained language models (PLMs) with task-specific prompts has...
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06/24/2020
