Suivre
Mohammad Taher Pilehvar
Mohammad Taher Pilehvar
Tehran Institute for Advanced Studies (TeIAS) and University of Cambridge
Adresse e-mail validée de cam.ac.uk - Page d'accueil
Titre
Citée par
Citée par
Année
From Word to Sense Embeddings: A Survey on Vector Representations of Meaning
J Camacho-Collados, MT Pilehvar
Journal of Artificial Intelligence Research (JAIR), 2018
4192018
WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations
MT Pilehvar, J Camacho-Collados
NAACL 2019, 2019
4122019
SensEmbed: Learning Sense Embeddings for Word and Relational Similarity
I Iacobacci, MT Pilehvar, R Navigli
ACL 2015, 2015
3662015
Embeddings for Word Sense Disambiguation: An Evaluation Study
I Iacobacci, MT Pilehvar, R Navigli
ACL 2016, 2016
3642016
Align, Disambiguate and Walk: A Unified Approach for Measuring Semantic Similarity
MT Pilehvar, D Jurgens, R Navigli
ACL 2013, 2013
2512013
NASARI: Integrating explicit knowledge and corpus statistics for a multilingual representation of concepts and entities
J Camacho-Collados, MT Pilehvar, R Navigli
Artificial Intelligence (AIJ) 240, 2016
2372016
On the Role of Text Preprocessing in Neural Network Architectures: An Evaluation Study on Text Categorization and Sentiment Analysis
J Camacho-Collados, MT Pilehvar
BlackboxNLP (EMNLP 2018), 2018
2072018
Semeval-2017 Task 2: Multilingual and Cross-Lingual Semantic Word Similarity
J Camacho-Collados, MT Pilehvar, N Collier, R Navigli
SemEval 2017, 2017
1812017
What’s missing in geographical parsing?
M Gritta, MT Pilehvar, N Limsopatham, N Collier
Language Resources and Evaluation 52 (2), 2018
1392018
NASARI: a novel approach to a semantically-aware representation of items
J Camacho-Collados, MT Pilehvar, R Navigli
NAACL 2015, 2015
1312015
From senses to texts: An all-in-one graph-based approach for measuring semantic similarity
MT Pilehvar, R Navigli
Artificial Intelligence (AIJ) 228, 2015
1302015
De-Conflated Semantic Representations
MT Pilehvar, N Collier
EMNLP 2016, 2016
1122016
Embeddings in Natural Language Processing: Theory and Advances in Vector Representations of Meaning
MT Pilehvar, J Camacho-Collados
Synthesis Lectures on Human Language Technologies, 2020
1012020
Will-They-Won't-They: A Very Large Dataset for Stance Detection on Twitter
C Conforti, J Berndt, MT Pilehvar, C Giannitsarou, F Toxvaerd, N Collier
ACL 2020, 2020
942020
SemEval-2014 Task 3: Cross-Level Semantic Similarity
D Jurgens, MT Pilehvar, R Navigli
SemEval 2014, 2014
872014
Mapping text to knowledge graph entities using multi-sense LSTMs
D Kartsaklis, MT Pilehvar, N Collier
EMNLP 2018, 2018
782018
SemEval-2016 Task 14: Semantic Taxonomy Enrichment
D Jurgens, MT Pilehvar
SemEval 2016, 2016
752016
A Framework for the Construction of Monolingual and Cross-lingual Word Similarity Datasets
J Camacho-Collados, MT Pilehvar, R Navigli
ACL 2015, 2015
72*2015
Analysis and evaluation of language models for word sense disambiguation
D Loureiro, K Rezaee, MT Pilehvar, J Camacho-Collados
Computational Linguistics 47 (2), 387-443, 2021
71*2021
A Large-scale Pseudoword-based Evaluation Framework for State-of-the-Art Word Sense Disambiguation
MT Pilehvar, R Navigli
Computational Linguistics 40 (4), 2014
692014
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