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05/24/2023
PURR: Efficiently Editing Language Model Hallucinations by Denoising Language Model Corruptions
The remarkable capabilities of large language models have been accompani...
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03/14/2023
Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs
Training data attribution (TDA) methods offer to trace a model's predict...
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12/05/2022
Meta-Learning Fast Weight Language Models
Dynamic evaluation of language models (LMs) adapts model parameters at t...
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10/17/2022
RARR: Researching and Revising What Language Models Say, Using Language Models
Language models (LMs) now excel at many tasks such as few-shot learning,...
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09/23/2022
Promptagator: Few-shot Dense Retrieval From 8 Examples
Much recent research on information retrieval has focused on how to tran...
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05/23/2022
Tracing Knowledge in Language Models Back to the Training Data
Neural language models (LMs) have been shown to memorize a great deal of...
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05/18/2022
Dialog Inpainting: Turning Documents into Dialogs
Many important questions (e.g. "How to eat healthier?") require conversa...
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09/03/2021
Finetuned Language Models Are Zero-Shot Learners
This paper explores a simple method for improving the zero-shot learning...
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02/02/2021
Neural Data Augmentation via Example Extrapolation
In many applications of machine learning, certain categories of examples...
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01/01/2021
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned
We review the EfficientQA competition from NeurIPS 2020. The competition...
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07/12/2020
Learning Abstract Models for Strategic Exploration and Fast Reward Transfer
Model-based reinforcement learning (RL) is appealing because (i) it enab...
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05/20/2020
Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models
Recent models for unsupervised representation learning of text have empl...
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02/10/2020
REALM: Retrieval-Augmented Language Model Pre-Training
Language model pre-training has been shown to capture a surprising amoun...
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06/04/2019
KERMIT: Generative Insertion-Based Modeling for Sequences
We present KERMIT, a simple insertion-based approach to generative model...
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12/04/2018
A Retrieve-and-Edit Framework for Predicting Structured Outputs
For the task of generating complex outputs such as source code, editing ...
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09/09/2018
Transforming Question Answering Datasets Into Natural Language Inference Datasets
Existing datasets for natural language inference (NLI) have propelled re...
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08/28/2018
Mapping Natural Language Commands to Web Elements
The web provides a rich, open-domain environment with textual, structura...
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02/24/2018
Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration
Reinforcement learning (RL) agents improve through trial-and-error, but ...
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09/26/2017
Generating Sentences by Editing Prototypes
We propose a new generative model of sentences that first samples a prot...
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04/25/2017
From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood
Our goal is to learn a semantic parser that maps natural language uttera...
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06/03/2015