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07/11/2023
Towards Robust and Efficient Continual Language Learning
As the application space of language models continues to evolve, a natur...
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10/14/2022
Efficiently Controlling Multiple Risks with Pareto Testing
Machine learning applications frequently come with multiple diverse obje...
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08/25/2022
Calibrated Selective Classification
Selective classification allows models to abstain from making prediction...
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03/15/2021
Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence
Typical fact verification models use retrieved written evidence to verif...
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02/17/2021
Few-shot Conformal Prediction with Auxiliary Tasks
We develop a novel approach to conformal prediction when the target task...
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12/31/2020
Making Pre-trained Language Models Better Few-shot Learners
The recent GPT-3 model (Brown et al., 2020) achieves remarkable few-shot...
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11/09/2020
CapWAP: Captioning with a Purpose
The traditional image captioning task uses generic reference captions to...
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07/06/2020
Relaxed Conformal Prediction Cascades for Efficient Inference Over Many Labels
Providing a small set of promising candidates in place of a single predi...
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10/22/2019
MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension
We present the results of the Machine Reading for Question Answering (MR...
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09/20/2019
Working Hard or Hardly Working: Challenges of Integrating Typology into Neural Dependency Parsers
This paper explores the task of leveraging typology in the context of cr...
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09/12/2017
StarSpace: Embed All The Things!
We present StarSpace, a general-purpose neural embedding model that can ...
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05/18/2017
ParlAI: A Dialog Research Software Platform
We introduce ParlAI (pronounced "par-lay"), an open-source software plat...
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03/31/2017
Reading Wikipedia to Answer Open-Domain Questions
This paper proposes to tackle open- domain question answering using Wiki...
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06/09/2016