CV of Mohammad Taher Pilehvar

Card-660: A Reliable Evaluation Framework for Rare Word Representation Models

Authors: Mohammad Taher Pilehvar, Dimitri Kartsaklis, Victor Prokhorov, Nigel Collier

Article Title: EMNLP 2018

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Classification of Persian textual documents using learning vector quantization

Authors: Mohammad Taher Pilevar, Heshaam Feili, Mahmood Soltani

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De-Conflated Semantic Representations

Authors: Mohammad Taher Pilehvar, Nigel Collier

Article Title: EMNLP 2016

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Don't Discard All the Biased Instances: Investigating a Core Assumption in Dataset Bias Mitigation Techniques

Authors: Hossein Amirkhani, Mohammad Taher Pilehvar

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Embeddings for Word Sense Disambiguation: An Evaluation Study

Authors: Ignacio Iacobacci, Mohammad Taher Pilehvar, Roberto Navigli

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Embeddings in Natural Language Processing

Authors: Jose Camacho-Collados, Mohammad Taher Pilehvar

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Embeddings in Natural Language Processing: Theory and Advances in Vector Representations of Meaning

Authors: Mohammad Taher Pilehvar, Jose Camacho-Collados

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Exploring the Role of BERT Token Representations to Explain Sentence Probing Results

Authors: Hosein Mohebbi, Ali Modarressi, Mohammad Taher Pilehvar

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From senses to texts: An all-in-one graph-based approach for measuring semantic similarity

Authors: Mohammad Taher Pilehvar, Roberto Navigli

Article Title: Artificial Intelligence

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From Word to Sense Embeddings: A Survey on Vector Representations of Meaning

Authors: Jose Camacho-Collados, Mohammad Taher Pilehvar

Article Title: Journal of Artificial Intelligence Research

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Card-660: A Reliable Evaluation Framework for Rare Word Representation Models

Classification of Persian textual documents using learning vector quantization

De-Conflated Semantic Representations

Don't Discard All the Biased Instances: Investigating a Core Assumption in Dataset Bias Mitigation Techniques

Embeddings for Word Sense Disambiguation: An Evaluation Study

Embeddings in Natural Language Processing

Embeddings in Natural Language Processing: Theory and Advances in Vector Representations of Meaning

Exploring the Role of BERT Token Representations to Explain Sentence Probing Results

From senses to texts: An all-in-one graph-based approach for measuring semantic similarity

From Word to Sense Embeddings: A Survey on Vector Representations of Meaning

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Card-660: A Reliable Evaluation Framework for Rare Word Representation Models

Classification of Persian textual documents using learning vector quantization

De-Conflated Semantic Representations

Don&#39;t Discard All the Biased Instances: Investigating a Core Assumption in Dataset Bias Mitigation Techniques

Embeddings for Word Sense Disambiguation: An Evaluation Study

Embeddings in Natural Language Processing

Embeddings in Natural Language Processing: Theory and Advances in Vector Representations of Meaning

Exploring the Role of BERT Token Representations to Explain Sentence Probing Results

From senses to texts: An all-in-one graph-based approach for measuring semantic similarity

From Word to Sense Embeddings: A Survey on Vector Representations of Meaning

Contact Us

WebsiteOwnershipTitle

Don't Discard All the Biased Instances: Investigating a Core Assumption in Dataset Bias Mitigation Techniques