Search Results for author: Ehsaneddin Asgari

Found 22 papers, 8 papers with code

Docalog: Multi-document Dialogue System using Transformer-based Span Retrieval

1 code implementation dialdoc (ACL) 2022 Sayed Hesam Alavian, Ali Satvaty, Sadra Sabouri, Ehsaneddin Asgari, Hossein Sameti

Information-seeking dialogue systems, including knowledge identification and response generation, aim to respond to users with fluent, coherent, and informative answers based on users’ needs.

Response Generation Retrieval

M$^3$Face: A Unified Multi-Modal Multilingual Framework for Human Face Generation and Editing

no code implementations4 Feb 2024 Mohammadreza Mofayezi, Reza Alipour, Mohammad Ali Kakavand, Ehsaneddin Asgari

Additionally, we propose the M3CelebA Dataset, a large-scale multi-modal and multilingual face dataset containing high-quality images, semantic segmentations, facial landmarks, and different captions for each image in multiple languages.

Face Generation Semantic Segmentation

KhabarChin: Automatic Detection of Important News in the Persian Language

1 code implementation6 Dec 2023 Hamed Hematian Hemati, Arash Lagzian, Moein Salimi Sartakhti, Hamid Beigy, Ehsaneddin Asgari

This paper introduces the detection of important news, in a previously unexplored area, and presents a new benchmarking dataset (Khabarchin) for detecting important news in the Persian language.

Benchmarking Decision Making +1

Taxi1500: A Multilingual Dataset for Text Classification in 1500 Languages

no code implementations15 May 2023 Chunlan Ma, Ayyoob ImaniGooghari, Haotian Ye, Ehsaneddin Asgari, Hinrich Schütze

While natural language processing tools have been developed extensively for some of the world's languages, a significant portion of the world's over 7000 languages are still neglected.

text-classification Text Classification

XPASC: Measuring Generalization in Weak Supervision by Explainability and Association

1 code implementation3 Jun 2022 Luisa März, Ehsaneddin Asgari, Fabienne Braune, Franziska Zimmermann, Benjamin Roth

To verify this assumption, we introduce a novel method, XPASC (eXPlainability-Association SCore), for measuring the generalization of a model trained with a weakly supervised dataset.

Stateless and Rule-Based Verification For Compliance Checking Applications

no code implementations14 Apr 2022 Mohammad Reza Besharati, Mohammad Izadi, Ehsaneddin Asgari

Both of deductive and model checking verification techniques are relying on a notion of state and as a result, their underlying computational models are state dependent.

Formal Logic

KnowMAN: Weakly Supervised Multinomial Adversarial Networks

1 code implementation EMNLP 2021 Luisa März, Ehsaneddin Asgari, Fabienne Braune, Franziska Zimmermann, Benjamin Roth

The knowledge is captured in labeling functions, which detect certain regularities or patterns in the training samples and annotate corresponding labels for training.

Language Modelling Weakly-supervised Learning

Subword Sampling for Low Resource Word Alignment

no code implementations21 Dec 2020 Ehsaneddin Asgari, Masoud Jalili Sabet, Philipp Dufter, Christopher Ringlstetter, Hinrich Schütze

This method's hypothesis is that the aggregation of different granularities of text for certain language pairs can help word-level alignment.

Bayesian Optimization Machine Translation +1

EmbLexChange at SemEval-2020 Task 1: Unsupervised Embedding-based Detection of Lexical Semantic Changes

1 code implementation SEMEVAL 2020 Ehsaneddin Asgari, Christoph Ringlstetter, Hinrich Sch{\"u}tze

This paper describes EmbLexChange, a system introduced by the {``}Life-Language{''} team for SemEval-2020 Task 1, on unsupervised detection of lexical-semantic changes.

Unsupervised Embedding-based Detection of Lexical Semantic Changes

no code implementations16 May 2020 Ehsaneddin Asgari, Christoph Ringlstetter, Hinrich Schütze

This paper describes EmbLexChange, a system introduced by the "Life-Language" team for SemEval-2020 Task 1, on unsupervised detection of lexical-semantic changes.

UniSent: Universal Adaptable Sentiment Lexica for 1000+ Languages

no code implementations LREC 2020 Ehsaneddin Asgari, Fabienne Braune, Benjamin Roth, Christoph Ringlstetter, Mohammad R. K. Mofrad

We introduce a method called DomDrift to mitigate the huge domain mismatch between Bible and Twitter by a confidence weighting scheme that uses domain-specific embeddings to compare the nearest neighbors for a candidate sentiment word in the source (Bible) and target (Twitter) domain.

Sentiment Analysis Unsupervised Domain Adaptation

Past, Present, Future: A Computational Investigation of the Typology of Tense in 1000 Languages

no code implementations EMNLP 2017 Ehsaneddin Asgari, Hinrich Schütze

We present SuperPivot, an analysis method for low-resource languages that occur in a superparallel corpus, i. e., in a corpus that contains an order of magnitude more languages than parallel corpora currently in use.

Nonsymbolic Text Representation

no code implementations3 Oct 2016 Hinrich Schuetze, Heike Adel, Ehsaneddin Asgari

We introduce the first generic text representation model that is completely nonsymbolic, i. e., it does not require the availability of a segmentation or tokenization method that attempts to identify words or other symbolic units in text.


ProtVec: A Continuous Distributed Representation of Biological Sequences

1 code implementation17 Mar 2015 Ehsaneddin Asgari, Mohammad R. K. Mofrad

Named bio-vectors (BioVec) to refer to biological sequences in general with protein-vectors (ProtVec) for proteins (amino-acid sequences) and gene-vectors (GeneVec) for gene sequences, this representation can be widely used in applications of deep learning in proteomics and genomics.

Classification General Classification

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