Search Results for author: Mitra Mohtarami

Found 19 papers, 2 papers with code

Attentive Multiview Text Representation for Differential Diagnosis

no code implementations ACL 2021 Hadi Amiri, Mitra Mohtarami, Isaac Kohane

We present a text representation approach that can combine different views (representations) of the same input through effective data fusion and attention strategies for ranking purposes.

Neural Multi-Task Learning for Stance Prediction

no code implementations WS 2019 Wei Fang, Moin Nadeem, Mitra Mohtarami, James Glass

We present a multi-task learning model that leverages large amount of textual information from existing datasets to improve stance prediction.

Multi-Task Learning

Contrastive Language Adaptation for Cross-Lingual Stance Detection

no code implementations IJCNLP 2019 Mitra Mohtarami, James Glass, Preslav Nakov

In particular, we introduce a novel contrastive language adaptation approach applied to memory networks, which ensures accurate alignment of stances in the source and target languages, and can effectively deal with the challenge of limited labeled data in the target language.

Stance Detection

Automatic Fact-Checking Using Context and Discourse Information

1 code implementation4 Aug 2019 Pepa Atanasova, Preslav Nakov, Lluís Màrquez, Alberto Barrón-Cedeño, Georgi Karadzhov, Tsvetomila Mihaylova, Mitra Mohtarami, James Glass

We study the problem of automatic fact-checking, paying special attention to the impact of contextual and discourse information.

Fact Checking

FAKTA: An Automatic End-to-End Fact Checking System

no code implementations NAACL 2019 Moin Nadeem, Wei Fang, Brian Xu, Mitra Mohtarami, James Glass

We present FAKTA which is a unified framework that integrates various components of a fact checking process: document retrieval from media sources with various types of reliability, stance detection of documents with respect to given claims, evidence extraction, and linguistic analysis.

Fact Checking Stance Detection

Vector of Locally Aggregated Embeddings for Text Representation

no code implementations NAACL 2019 Hadi Amiri, Mitra Mohtarami

We present Vector of Locally Aggregated Embeddings (VLAE) for effective and, ultimately, lossless representation of textual content.

Classification General Classification +1

Adversarial Domain Adaptation for Stance Detection

no code implementations6 Feb 2019 Brian Xu, Mitra Mohtarami, James Glass

This paper studies the problem of stance detection which aims to predict the perspective (or stance) of a given document with respect to a given claim.

Domain Adaptation Fact Checking +1

Integrating Stance Detection and Fact Checking in a Unified Corpus

no code implementations NAACL 2018 Ramy Baly, Mitra Mohtarami, James Glass, Lluis Marquez, Alessandro Moschitti, Preslav Nakov

A reasonable approach for fact checking a claim involves retrieving potentially relevant documents from different sources (e. g., news websites, social media, etc.

Fact Checking Stance Detection

Automatic Stance Detection Using End-to-End Memory Networks

no code implementations NAACL 2018 Mitra Mohtarami, Ramy Baly, James Glass, Preslav Nakov, Lluis Marquez, Alessandro Moschitti

We present a novel end-to-end memory network for stance detection, which jointly (i) predicts whether a document agrees, disagrees, discusses or is unrelated with respect to a given target claim, and also (ii) extracts snippets of evidence for that prediction.

Stance Detection

Fact Checking in Community Forums

3 code implementations8 Mar 2018 Tsvetomila Mihaylova, Preslav Nakov, Lluis Marquez, Alberto Barron-Cedeno, Mitra Mohtarami, Georgi Karadzhov, James Glass

Community Question Answering (cQA) forums are very popular nowadays, as they represent effective means for communities around particular topics to share information.

Community Question Answering Fact Checking

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