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Entailment as Few-Shot Learner

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arxiv 2104.14690 v1 pith:2ZKRIA7T submitted 2021-04-29 cs.CL cs.AI

Sinong Wang , Han Fang , Madian Khabsa , Hanzi Mao , Hao Ma This is my paper · ORCID
classification cs.CLcs.AI
keywords few-shotapproachentailmentlearnerslearningmethodmodelmodels
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Large pre-trained language models (LMs) have demonstrated remarkable ability as few-shot learners. However, their success hinges largely on scaling model parameters to a degree that makes it challenging to train and serve. In this paper, we propose a new approach, named as EFL, that can turn small LMs into better few-shot learners. The key idea of this approach is to reformulate potential NLP task into an entailment one, and then fine-tune the model with as little as 8 examples. We further demonstrate our proposed method can be: (i) naturally combined with an unsupervised contrastive learning-based data augmentation method; (ii) easily extended to multilingual few-shot learning. A systematic evaluation on 18 standard NLP tasks demonstrates that this approach improves the various existing SOTA few-shot learning methods by 12\%, and yields competitive few-shot performance with 500 times larger models, such as GPT-3.

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Cited by 4 Pith papers

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    Compliance detection can be framed as multi-hop natural language inference over assurance case structures, with LLM-generated data and faithfulness metrics.

  3. CoCoP: Enhancing Text Classification with LLM through Code Completion Prompt

    cs.CL 2024-11 conditional novelty 5.0 of 10

    CoCoP, which formats text classification as code completion, improves LLM accuracy over few-shot prompting and lets small code models approach large general models.

  4. Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge

    cs.CL 2024-12 conditional novelty 4.0 of 10

    GPT-3.5 with chain-of-thought prompting still fails often on multi-hop reasoning with external knowledge, especially with distractors, counterfactual facts, non-sequential proof structures, and higher hop counts.

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