research
∙
08/16/2023
Time Travel in LLMs: Tracing Data Contamination in Large Language Models
Data contamination, i.e., the presence of test data from downstream task...
share
research
∙
07/14/2023
Do not Mask Randomly: Effective Domain-adaptive Pre-training by Masking In-domain Keywords
We propose a novel task-agnostic in-domain pre-training method that sits...
research
∙
07/11/2023
Synthetic Dataset for Evaluating Complex Compositional Knowledge for Natural Language Inference
We introduce a synthetic dataset called Sentences Involving Complex Comp...
research
∙
07/06/2023
It is not Sexually Suggestive, It is Educative. Separating Sex Education from Suggestive Content on TikTok Videos
We introduce SexTok, a multi-modal dataset composed of TikTok videos lab...
research
∙
04/28/2023
Explainable Verbal Reasoner Plus (EVR+): A Natural Language Reasoning Framework that Supports Diverse Compositional Reasoning
Languages models have been successfully applied to a variety of reasonin...
research
∙
10/30/2022
Validity Assessment of Legal Will Statements as Natural Language Inference
This work introduces a natural language inference (NLI) dataset that foc...
research
∙
10/26/2022
BioNLI: Generating a Biomedical NLI Dataset Using Lexico-semantic Constraints for Adversarial Examples
Natural language inference (NLI) is critical for complex decision-making...
research
∙
08/25/2022
A Compact Pretraining Approach for Neural Language Models
Domain adaptation for large neural language models (NLMs) is coupled wit...
research
∙
05/30/2022
Learning Open Domain Multi-hop Search Using Reinforcement Learning
We propose a method to teach an automated agent to learn how to search f...
research
∙
05/10/2022
SuMe: A Dataset Towards Summarizing Biomedical Mechanisms
Can language models read biomedical texts and explain the biomedical mec...
research
∙
05/07/2022
Better Retrieval May Not Lead to Better Question Answering
Considerable progress has been made recently in open-domain question ans...
research
∙
04/25/2022
It Takes Two Flints to Make a Fire: Multitask Learning of Neural Relation and Explanation Classifiers
We propose an explainable approach for relation extraction that mitigate...
research
∙
01/16/2022
From Examples to Rules: Neural Guided Rule Synthesis for Information Extraction
While deep learning approaches to information extraction have had many s...
research
∙
01/15/2022
Automatic Correction of Syntactic Dependency Annotation Differences
Annotation inconsistencies between data sets can cause problems for low-...
research
∙
01/10/2022
Informal Persian Universal Dependency Treebank
This paper presents the phonological, morphological, and syntactic disti...
research
∙
12/17/2021
Neural Architectures for Biological Inter-Sentence Relation Extraction
We introduce a family of deep-learning architectures for inter-sentence ...
research
∙
09/10/2021
How May I Help You? Using Neural Text Simplification to Improve Downstream NLP Tasks
The general goal of text simplification (TS) is to reduce text complexit...
research
∙
06/08/2021
Cheap and Good? Simple and Effective Data Augmentation for Low Resource Machine Reading
We propose a simple and effective strategy for data augmentation for low...
research
∙
10/15/2020
The Language of Food during the Pandemic: Hints about the Dietary Effects of Covid-19
We study the language of food on Twitter during the pandemic lockdown in...
research
∙
09/22/2020
Using the Hammer Only on Nails: A Hybrid Method for Evidence Retrieval for Question Answering
Evidence retrieval is a key component of explainable question answering ...
research
∙
05/04/2020
Unsupervised Alignment-based Iterative Evidence Retrieval for Multi-hop Question Answering
Evidence retrieval is a critical stage of question answering (QA), neces...
research
∙
11/17/2019
Quick and (not so) Dirty: Unsupervised Selection of Justification Sentences for Multi-hop Question Answering
We propose an unsupervised strategy for the selection of justification s...
research
∙
09/21/2019
On the Importance of Delexicalization for Fact Verification
In this work we aim to understand and estimate the importance that a neu...
research
∙
07/05/2018
Sanity Check: A Strong Alignment and Information Retrieval Baseline for Question Answering
While increasingly complex approaches to question answering (QA) have be...
research
∙
05/29/2018
Lightly-supervised Representation Learning with Global Interpretability
We propose a lightly-supervised approach for information extraction, in ...
research
∙
11/01/2017
Text Annotation Graphs: Annotating Complex Natural Language Phenomena
This paper introduces a new web-based software tool for annotating text,...
research
∙
09/01/2017
Learning what to read: Focused machine reading
Recent efforts in bioinformatics have achieved tremendous progress in th...
research
∙
06/30/2016
SnapToGrid: From Statistical to Interpretable Models for Biomedical Information Extraction
We propose an approach for biomedical information extraction that marrie...
research
∙
06/26/2016
This before That: Causal Precedence in the Biomedical Domain
Causal precedence between biochemical interactions is crucial in the bio...
research
∙
03/11/2016
Towards using social media to identify individuals at risk for preventable chronic illness
We describe a strategy for the acquisition of training data necessary to...
research
∙
03/11/2016
Sieve-based Coreference Resolution in the Biomedical Domain
We describe challenges and advantages unique to coreference resolution i...
research
∙
09/24/2015
