33 citations · 42 across the 6 of their papers we have counts for
8 papers · 1 filter
Generative Adversarial Training Can Improve Neural Language Models
Sajad Movahedi, Azadeh Shakery
While deep learning in the form of recurrent neural networks (RNNs) has caused a significant improvement in neural language modeling, the fact that they are extremely prone to over…
ARMAN: Pre-training with Semantically Selecting and Reordering of Sentences for Persian Abstractive Summarization
Alireza Salemi, Emad Kebriaei, Ghazal Neisi Minaei +1
Abstractive text summarization is one of the areas influenced by the emergence of pre-trained language models. Current pre-training works in abstractive summarization give more poi…
NLP-IIS@UT at SemEval-2021 Task 4: Machine Reading Comprehension using the Long Document Transformer
Hossein Basafa, Sajad Movahedi, Ali Ebrahimi +2
This paper presents a technical report of our submission to the 4th task of SemEval-2021, titled: Reading Comprehension of Abstract Meaning. In this task, we want to predict the co…
UTNLP at SemEval-2021 Task 5: A Comparative Analysis of Toxic Span Detection using Attention-based, Named Entity Recognition, and Ensemble Models
Alireza Salemi, Nazanin Sabri, Emad Kebriaei +2
Detecting which parts of a sentence contribute to that sentence's toxicity -- rather than providing a sentence-level verdict of hatefulness -- would increase the interpretability o…
Enriching Conversation Context in Retrieval-based Chatbots
Amir Vakili Tahami, Azadeh Shakery
Work on retrieval-based chatbots, like most sequence pair matching tasks, can be divided into Cross-encoders that perform word matching over the pair, and Bi-encoders that encode t…
Aspect Category Detection via Topic-Attention Network
Sajad Movahedi, Erfan Ghadery, Heshaam Faili +1
The e-commerce has started a new trend in natural language processing through sentiment analysis of user-generated reviews. Different consumers have different concerns about variou…