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05/27/2023
FERMAT: An Alternative to Accuracy for Numerical Reasoning
While pre-trained language models achieve impressive performance on vari...
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04/25/2023
Lessons Learned from a Citizen Science Project for Natural Language Processing
Many Natural Language Processing (NLP) systems use annotated corpora for...
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09/06/2022
Layer or Representation Space: What makes BERT-based Evaluation Metrics Robust?
The evaluation of recent embedding-based evaluation metrics for text gen...
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08/30/2022
Transformers with Learnable Activation Functions
Activation functions can have a significant impact on reducing the topol...
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05/24/2022
Scoring Coreference Chains with Split-Antecedent Anaphors
Anaphoric reference is an aspect of language interpretation covering a v...
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05/13/2022
Improving the Numerical Reasoning Skills of Pretrained Language Models
State-of-the-art pretrained language models tend to perform below their ...
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05/12/2022
Falsesum: Generating Document-level NLI Examples for Recognizing Factual Inconsistency in Summarization
Neural abstractive summarization models are prone to generate summaries ...
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05/03/2022
Adaptable Adapters
State-of-the-art pretrained NLP models contain a hundred million to tril...
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09/09/2021
Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning
Recent prompt-based approaches allow pretrained language models to achie...
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04/16/2021
Learning to Reason for Text Generation from Scientific Tables
In this paper, we introduce SciGen, a new challenge dataset for the task...
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04/12/2021
Stay Together: A System for Single and Split-antecedent Anaphora Resolution
The state-of-the-art on basic, single-antecedent anaphora has greatly im...
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12/31/2020
Coreference Reasoning in Machine Reading Comprehension
The ability to reason about multiple references to a given entity is ess...
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10/31/2020
Free the Plural: Unrestricted Split-Antecedent Anaphora Resolution
Now that the performance of coreference resolvers on the simpler forms o...
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10/23/2020
Improving Robustness by Augmenting Training Sentences with Predicate-Argument Structures
Existing NLP datasets contain various biases, and models tend to quickly...
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10/07/2020
Improving QA Generalization by Concurrent Modeling of Multiple Biases
Existing NLP datasets contain various biases that models can easily expl...
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09/25/2020
Towards Debiasing NLU Models from Unknown Biases
NLU models often exploit biases to achieve high dataset-specific perform...
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05/01/2020
Mind the Trade-off: Debiasing NLU Models without Degrading the In-distribution Performance
Models for natural language understanding (NLU) tasks often rely on the ...
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11/13/2019
Neural Duplicate Question Detection without Labeled Training Data
Supervised training of neural models to duplicate question detection in ...
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09/19/2019
Improving Generalization by Incorporating Coverage in Natural Language Inference
The task of natural language inference (NLI) is to identify the relation...
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06/16/2019
Using Automatically Extracted Minimum Spans to Disentangle Coreference Evaluation from Boundary Detection
The common practice in coreference resolution is to identify and evaluat...
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08/01/2017
Enhancing the Input Representation: From Complexity to Simplicity
We introduce an efficient algorithm for mining informative combinations ...
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07/20/2017
Revisiting Selectional Preferences for Coreference Resolution
Selectional preferences have long been claimed to be essential for coref...
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04/22/2017
Lexical Features in Coreference Resolution: To be Used With Caution
Lexical features are a major source of information in state-of-the-art c...
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02/24/2017