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06/05/2023
DecompX: Explaining Transformers Decisions by Propagating Token Decomposition
An emerging solution for explaining Transformer-based models is to use v...
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05/29/2023
LM-CPPF: Paraphrasing-Guided Data Augmentation for Contrastive Prompt-Based Few-Shot Fine-Tuning
In recent years, there has been significant progress in developing pre-t...
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04/03/2023
PEACH: Pre-Training Sequence-to-Sequence Multilingual Models for Translation with Semi-Supervised Pseudo-Parallel Document Generation
Multilingual pre-training significantly improves many multilingual NLP t...
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11/10/2022
BERT on a Data Diet: Finding Important Examples by Gradient-Based Pruning
Current pre-trained language models rely on large datasets for achieving...
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11/07/2022
Looking at the Overlooked: An Analysis on the Word-Overlap Bias in Natural Language Inference
It has been shown that NLI models are usually biased with respect to the...
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05/06/2022
GlobEnc: Quantifying Global Token Attribution by Incorporating the Whole Encoder Layer in Transformers
There has been a growing interest in interpreting the underlying dynamic...
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03/26/2022
Metaphors in Pre-Trained Language Models: Probing and Generalization Across Datasets and Languages
Human languages are full of metaphorical expressions. Metaphors help peo...
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12/25/2021
PerCQA: Persian Community Question Answering Dataset
Community Question Answering (CQA) forums provide answers for many real-...
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11/22/2020
Cross-Domain Generalization Through Memorization: A Study of Nearest Neighbors in Neural Duplicate Question Detection
Duplicate question detection (DQD) is important to increase efficiency o...
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04/25/2020
Quantifying the Contextualization of Word Representations with Semantic Class Probing
Pretrained language models have achieved a new state of the art on many ...
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11/10/2019
Robust Natural Language Inference Models with Example Forgetting
We investigate whether example forgetting, a recently introduced measure...
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11/06/2019
Unsupervised Domain Adaptation of Contextual Embeddings for Low-Resource Duplicate Question Detection
Answering questions is a primary goal of many conversational systems or ...
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09/02/2019
On the Knowledge Graph Completion Using Translation Based Embedding: The Loss Is as Important as the Score
Knowledge graphs (KGs) represent world's facts in structured forms. KG c...
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06/09/2019
Probing for Semantic Classes: Diagnosing the Meaning Content of Word Embeddings
Word embeddings typically represent different meanings of a word in a si...
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10/24/2018
Multi-Multi-View Learning: Multilingual and Multi-Representation Entity Typing
Knowledge bases (KBs) are paramount in NLP. We employ multiview learning...
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07/18/2018
Evaluating Word Embeddings in Multi-label Classification Using Fine-grained Name Typing
Embedding models typically associate each word with a single real-valued...
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06/12/2018
Recurrent One-Hop Predictions for Reasoning over Knowledge Graphs
Large scale knowledge graphs (KGs) such as Freebase are generally incomp...
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08/07/2017
Corpus-level Fine-grained Entity Typing
This paper addresses the problem of corpus-level entity typing, i.e., in...
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01/08/2017
Multi-level Representations for Fine-Grained Typing of Knowledge Base Entities
Entities are essential elements of natural language. In this paper, we p...
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12/22/2016
Noise Mitigation for Neural Entity Typing and Relation Extraction
In this paper, we address two different types of noise in information ex...
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06/25/2016
Intrinsic Subspace Evaluation of Word Embedding Representations
We introduce a new methodology for intrinsic evaluation of word represen...
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06/25/2016
