Kelvin Guu

Promptagator: Few-shot Dense Retrieval From 8 Examples

2022 · arXiv (Cornell University)

Much recent research on information retrieval has focused on how to transfer from one task (typically with abundant supervised data) to various other tasks where supervision is limited, with the implicit assumption that it is …

Transforming Question Answering Datasets Into Natural Language Inference Datasets

2018 · arXiv (Cornell University)

Existing datasets for natural language inference (NLI) have propelled research on language understanding. We propose a new method for automatically deriving NLI datasets from the growing abundance of large-scale question answering datasets. Our approach hinges …

Generating Sentences by Editing Prototypes

2018 · Transactions of the Association for Computational Linguistics

We propose a new generative language model for sentences that first samples a prototype sentence from the training corpus and then edits it into a new sentence. Compared to traditional language models that generate from …

From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood

2017

Our goal is to learn a semantic parser that maps natural language utterances into executable programs when only indirect supervision is available: examples are labeled with the correct execution result, but not the program itself. …

REALM: Retrieval-Augmented Language Model Pre-Training

2020 · arXiv (Cornell University)

Language model pre-training has been shown to capture a surprising amount of world knowledge, crucial for NLP tasks such as question answering. However, this knowledge is stored implicitly in the parameters of a neural network, …