Search Results for author:
Found 18 papers, 10 papers with code
IITP-CUNI@3C: Supervised Approaches for Citation Classification (Task A) and Citation Significance Detection (Task B)
With the rapid growth in research publications, automated solutions for identifying the purpose and influence of citations are becoming very important.
IDIAP_TIET@LT-EDI-ACL2022 : Hope Speech Detection in Social Media using Contextualized BERT with Attention Mechanism
With the increase of users on social media platforms, manipulating or provoking masses of people has become a piece of cake.
Hierarchical Multi-task learning framework for Isometric-Speech Language Translation
In this paper, we propose a hierarchical approach to generate isometric translation on MUST-C dataset, we achieve a BERTscore of 0. 85, a length ratio of 1. 087, a BLEU score of 42. 3, and a length range of 51. 03%.
Innovators @ SMM4H’22: An Ensembles Approach for self-reporting of COVID-19 Vaccination Status Tweets
With the Surge in COVID-19, the number of social media postings related to the vaccine has grown, specifically tracing the confirmed reports by the users regarding the COVID-19 vaccine dose termed “Vaccine Surveillance.” To mitigate this research problem, we present our novel ensembled approach for self-reporting COVID-19 vaccination status tweets into two labels, namely “Vaccine Chatter” and “Self Report.” We utilize state-of-the-art models, namely BERT, RoBERTa, and XLNet.
Innovators@SMM4H’22: An Ensembles Approach for Stance and Premise Classification of COVID-19 Health Mandates Tweets
This paper presents our submission for the Shared Task-2 of classification of stance and premise in tweets about health mandates related to COVID-19 at the Social Media Mining for Health 2022.
IDIAP Submission@LT-EDI-ACL2022 : Hope Speech Detection for Equality, Diversity and Inclusion
It reflects the belief to achieve an objective, discovers a new path, or become motivated to formulate pathways. In this paper we classify given a social media post, hope speech or not hope speech, using ensembled voting of BERT, ERNIE 2. 0 and RoBERTa for English language with 0. 54 macro F1-score (2^{st} rank).
Team Innovators at SemEval-2022 for Task 8: Multi-Task Training with Hyperpartisan and Semantic Relation for Multi-Lingual News Article Similarity
This work represents the system proposed by team Innovators for SemEval 2022 Task 8: Multilingual News Article Similarity.
Multimodality for NLP-Centered Applications: Resources, Advances and Frontiers
With the development of multimodal systems and natural language generation techniques, the resurgence of multimodal datasets has attracted significant research interests, which aims to provide new information to enrich the representation of textual data.
Automatic Summarization for Creative Writing: BART based Pipeline Method for Generating Summary of Movie Scripts
This paper documents our approach for the Creative-Summ 2022 shared task for Automatic Summarization of Creative Writing.
IDIAP Submission@LT-EDI-ACL2022: Homophobia/Transphobia Detection in social media comments
The increased expansion of abusive content on social media platforms negatively affects online users.
IDIAP Submission@LT-EDI-ACL2022: Detecting Signs of Depression from Social Media Text
Given social media postings in English, the submitted system classify the signs of depression into three labels, namely “not depressed,” “moderately depressed,” and “severely depressed.” Our best model is ranked 3^{rd} position with 0. 54% accuracy .
ELITR Minuting Corpus: A Novel Dataset for Automatic Minuting from Multi-Party Meetings in English and Czech
Our dataset, AutoMin, consists of 113 (English) and 53 (Czech) meetings, covering more than 160 hours of meeting content.
DeepCon: An End-to-End Multilingual Toolkit for Automatic Minuting of Multi-Party Dialogues
In this paper, we present our minuting tool DeepCon, an end-to-end toolkit for minuting the multiparty dialogues of meetings.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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IDIAPers @ Causal News Corpus 2022: Efficient Causal Relation Identification Through a Prompt-based Few-shot Approach
In this paper, we describe our participation in the subtask 1 of CASE-2022, Event Causality Identification with Casual News Corpus.
IDIAPers @ Causal News Corpus 2022: Extracting Cause-Effect-Signal Triplets via Pre-trained Autoregressive Language Model
In this paper, we describe our shared task submissions for Subtask 2 in CASE-2022, Event Causality Identification with Casual News Corpus.
ALIGNMEET: A Comprehensive Tool for Meeting Annotation, Alignment, and Evaluation
To facilitate the research in this area, we present ALIGNMEET, a comprehensive tool for meeting annotation, alignment, and evaluation.
RerrFact: Reduced Evidence Retrieval Representations for Scientific Claim Verification
Finally, we carry out two-step stance predictions that first differentiate non-relevant rationales and then identify supporting or refuting rationales for a given claim.
