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06/01/2023
Did You Read the Instructions? Rethinking the Effectiveness of Task Definitions in Instruction Learning
Large language models (LLMs) have shown impressive performance in follow...
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05/30/2023
SWiPE: A Dataset for Document-Level Simplification of Wikipedia Pages
Text simplification research has mostly focused on sentence-level simpli...
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11/11/2022
Improving Factual Consistency in Summarization with Compression-Based Post-Editing
State-of-the-art summarization models still struggle to be factually con...
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05/05/2022
Interactive Model Cards: A Human-Centered Approach to Model Documentation
Deep learning models for natural language processing (NLP) are increasin...
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03/08/2022
iSEA: An Interactive Pipeline for Semantic Error Analysis of NLP Models
Error analysis in NLP models is essential to successful model developmen...
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12/14/2021
Exploring Neural Models for Query-Focused Summarization
Query-focused summarization (QFS) aims to produce summaries that answer ...
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10/14/2021
MoFE: Mixture of Factual Experts for Controlling Hallucinations in Abstractive Summarization
Neural abstractive summarization models are susceptible to generating fa...
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04/15/2021
SummVis: Interactive Visual Analysis of Models, Data, and Evaluation for Text Summarization
Novel neural architectures, training strategies, and the availability of...
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01/13/2021
Robustness Gym: Unifying the NLP Evaluation Landscape
Despite impressive performance on standard benchmarks, deep neural netwo...
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12/01/2020
Profile Prediction: An Alignment-Based Pre-Training Task for Protein Sequence Models
For protein sequence datasets, unlabeled data has greatly outpaced label...
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06/26/2020
BERTology Meets Biology: Interpreting Attention in Protein Language Models
Transformer architectures have proven to learn useful representations fo...
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04/26/2020
Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Bias
Common methods for interpreting neural models in natural language proces...
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06/12/2019
A Multiscale Visualization of Attention in the Transformer Model
The Transformer is a sequence model that forgoes traditional recurrent a...
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06/07/2019
Analyzing the Structure of Attention in a Transformer Language Model
The Transformer is a fully attention-based alternative to recurrent netw...
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04/04/2019
Visualizing Attention in Transformer-Based Language Representation Models
We present an open-source tool for visualizing multi-head self-attention...
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04/04/2019
