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04/17/2023
Learning to Compress Prompts with Gist Tokens
Prompting is now the primary way to utilize the multitask capabilities o...
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12/28/2022
Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP
Retrieval-augmented in-context learning has emerged as a powerful approa...
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12/19/2022
Evaluating Human-Language Model Interaction
Many real-world applications of language models (LMs), such as code auto...
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10/27/2022
Contrastive Decoding: Open-ended Text Generation as Optimization
Likelihood, although useful as a training loss, is a poor search objecti...
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05/27/2022
Diffusion-LM Improves Controllable Text Generation
Controlling the behavior of language models (LMs) without re-training is...
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01/01/2021
Prefix-Tuning: Optimizing Continuous Prompts for Generation
Fine-tuning is the de facto way to leverage large pretrained language mo...
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10/14/2020
Decoding Methods for Neural Narrative Generation
Narrative generation is an open-ended NLP task in which a model generate...
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05/10/2020
Posterior Control of Blackbox Generation
Text generation often requires high-precision output that obeys task-spe...
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10/01/2019
Specializing Word Embeddings (for Parsing) by Information Bottleneck
Pre-trained word embeddings like ELMo and BERT contain rich syntactic an...
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06/26/2019
