FIRE 2024
FIRE 2024 Working Notes

Table of Contents

• Preface
  Kripabandhu Ghosh , Thomas Mandl , Prasenjit Majumder , Debasis Ganguly

Indian Language Summarization (ILSUM)

• Overview of the Third Shared Task on Indian Language Summarization (ILSUM 2024) 1-12
  Shrey Satapara , Parth Mehta , Sandip Modha , Asha Hegde , H. L. Shashirekha , Debasis Ganguly
• Text Summarization for Indian Languages: Extractive summarization using graph based technique 13-21
  Ansh Vora , Aastha Shah , Rinit Jain , Sheetal Sonawane
• CrossFactual: A Novel Approach for Detecting Factual Inaccuracies in Machine-Generated Summaries 22-31
  Aniket Deroy , Subhankar Maity
• Enhancing Accuracy in Indian Language Summarization 32-38
  Rishika Jha , Rakshit Ahuja , Sainik Kumar Mahata , Monalisa Dey , Dipankar Das
• Enhancing Extractive Summarization for Low Resource Indian Languages using TF-IDF and SVD 39-47
  Sangita Singh , Jyoti Prakash Singh , Akshay Deepak , Supriya
• Overcoming Code-Mixing and Script-Mixing in Indian Language Summarization with Transformer Models 48-57
  Pulkit Chatwal , Amit Agarwal , Ankush Mittal
• Indian Language Summarization and Factual Error Detection using Pretrained Sequence-to-Sequence Models and Large Language Models 58-68
  Abhijith Balan , Chittoor Karthik , Oswald Christopher
• Text Summarization using Pre-Trained Models on Tamil English Gujarati and Bengali 69-81
  Tanisha Sriram , Ananya Raman , Sowmya Anand , Durairaj Thenmozhi
• Abstractive Summarization of large articles in Hindi Language using IndicBART 82-87
  Chaitanya Subhedar , Sheetal Sonawane
• Text Summarization and Detection of Factual Incorrectness for Indian Languages 88-97
  Durairaj Thenmozhi , Rohan R , Niranjana A , Madussree Ravi , Padmashri R
• Summarizing English News Articles: Leveraging T5 and Google Gemini 1.0 Pro 98-106
  M Saipranav , Murari Sreekumar , Durairaj Thenmozhi , Shreyas Karthik , Rahul VS
• Enhancing News Article Summarization Through Post-Processing Techniques 107-115
  Fathima Firose A , Reshma Sheik , Kathijaafrose A , S. Jaya Nirmala
• Assessing Factual Accuracy in Machine Generated Cross Lingual Summaries using Logistic Regression and BERT 116-123
  Kushaal Shyam Potta , Jaswanth Sridharan , Mahadev Ramesh Ramya , Shriram Gopalakrishnan , Durairaj Thenmozhi

Code-Mixed Information Retrieval

• Overview of the shared task on code-mixed information retrieval from social media data 124-128
  Supriya Chanda , Sukomal Pal
• RetrieveGPT: Merging Prompts and Mathematical Models for Enhanced Code-Mixed Information Retrieval 129-139
  Aniket Deroy , Subhankar Maity
• InfoTextCM: Addressing Code-Mixed Data Retrieval Challenges via Text Classification 140-147
  Aditya Sharma

CoLI-Dravidian: Word-level Code-Mixed Language Identification in Dravidian Languages

• Overview of CoLI-Dravidian: Word-level Code-Mixed Language Identification in Dravidian Languages 148-157
  Asha Hegde , Fazlourrahman Balouchzahi , Sabur Butt , Sharal Coelho , Kavya G , Harshitha S Kumar , Sonith D , Shashirekha Hosahalli Lakshmaiah , Ameeta Agrawal
• Prompt Engineering Using GPT for Word-Level Code-Mixed Language Identification in Low-Resource Dravidian Languages 158-168
  Aniket Deroy , Subhankar Maity
• Finding the Right Language Model Goes a Long Way Towards Accurate Language Identification 169-181
  Rob van der Goot
• Cracking the Code: Machine Learning Approaches for Dravidian Code-Mixed Texts 182-190
  Nikhil Narayan , Sachin Mohanty
• Leveraging MuRIL for Word-Level Language Identification in Code-Mixed Dravidian Text 191-198
  Akhil Bhogal , Soumyadeep Sar , Dwaipayan Roy , Kripabandhu Ghosh
• Machine Learning Based Model for Word-level Language Identification in Code-mixed Kannada Texts 199-206
  Abdollah Abadian
• Word-Level Language Identification in Dravidian Code-Mixed Text Using Machine Learning: A Comparative Analysis of Models and Vectorization Techniques 207-215
  Ponsubash Raj R , Bharathi B
• Word Level Language Identification in Code-mixed Dravidian Languages 216-223
  Harshitha S Kumar , Sharal Coelho , Asha Hegde , Kavya G , Hosahalli Lakshmaiah Shashirekha
• Enhancing Word-Level Language Identification in Code-Mixed Dravidian Languages 224-232
  Sonith D , Kavya G , Asha Hegde , Hosahalli Lakshmaiah Shashirekha

Sarcasm Identification of Dravidian Languages Tamil & Malayalam (DravidianCodeMix)

• Overview of Sarcasm Identification of Dravidian Languages in DravidianCodeMix@FIRE-2024 233-243
  Sripriya N , Bharathi B , Thenmozhi Durairaj , Nandhini K , Rahul Ponnusamy , Prasanna Kumar Kumaresan , Kishore Kumar Ponnusamy , Charmathi Rajkumar , Bharathi Raja Chakravarthi
• YouTube Comments Decoded: Leveraging LLMs for Low Resource Language Classification 244-254
  Aniket Deroy , Subhankar Maity
• Text Classification Based on Ensembles of Pre-Trained Models for Sarcasm Identification in Dravidian Languages 255-265
  Jaime Cerda-Flores , Daniel Castro-Pineda , Miguel G. Juarez , Rodrigo I Hernandez-Mazariegos , Jaime Cerda-Jacobo , Mario Graff , José Ortiz-Bejar
• Sarcasm Detection and Identification of Dravidian Language Using Machine Learning Approach 266-273
  Moogambigai A , Kamesh S , Paruvatha Priya B , Bharathi B
• A Hybrid Approach to Sarcasm Detection in Dravidian Code-Mixed Texts 274-278
  Prasun Maity , Dipanjan Saha , Sayan Das , Sainik Kumar Mahata
• Sarcasm Detection in Dravidian Languages Using Bi-directional LSTM 279-288
  Sulaksha B K , Shruthi Priyaa G K , Amritha P , C. Jerin Mahibha
• Unmasking Sarcasm: Exploring mBERT+CNN and LSTM Models for Sarcasm Identification in Code-Mixed Tamil and Malayalam Texts 289-298
  Sonith D , Kavya G , H L Shashirekha
• A Transformer-based Model for Detecting Multilingual Sarcasm in Social Media Posts 299-309
  Shraddha Chauhan , Abhinav Kumar
• Sarcasm Identification Of Dravidian Languages Malayalam and Tamil 310-317
  Shreyas Karthik , Murari Sreekumar , Kushaal Shyam Potta , Durairaj Thenmozhi
• Sarcasm Detection in Dravidian Languages 318-324
  Aioshi Chowdhury , Soumyajit Paul , Souvik Kundu , Anurag Kumar Thakur , Anuska Sarkar , Anusmita Ray Chaudhuri , Anirban Ray , Debasree Mitra
• MSD: Multilingual Sarcasm Detection using Deep Learning-Based Model 325-332
  Ranjeet Kumar , Abhinav Kumar
• Investigation of Machine Learning and Transformer Models for Sarcasm Detection in Dravidian Languages 333-339
  Malliga Subramanian , Ananthakumar S , Deepiga P , Dharshini S , Kogilavani S V
• Sarcasm Detection from Dravidian Language Text 340-347
  C.Jerin Mahibha , Gersome Shimi , Durairaj Thenmozhi
• Leveraging ChatGPT and XLM-RoBERTa for Sarcasm Detection in Dravidian Code-Mixed Languages 348-356
  Supriya Chanda , Krishna Tewari , Arjun Mukherjee , Sukomal Pal
• Automated Sarcasm Identification in Code-Mixed Social Media Text using Machine Learning Techniques 357-364
  Kogilavani S V , Palani Murugan V , Pooja Sree M , Pavul Chinnappan D
• Detecting Sarcasm in Social Media Text Using Indic Transliteration and Machine Learning Techniques 365-372
  Kogilavani S V , Malliga Subramnanian , Prenitha S P , Varshini S H
• Enhanced Sarcasm Detection in Code-Mixed Tamil-English Text Using GRU and LSTM with SMOTE and Padding Techniques 373-383
  Kogilavani S V , Navbila K , Sridhar S
• Leveraging Transfer Learning and Deep Recurrent Networks for Sarcasm Detection in Tamil Language Text 384-389
  Kogilavani S V , Subhadevi K , Sowbharanika Janani J S , Rahul K
• Sarcasm Unveiled: Advanced Detection Techniques for Tamil and Malayalam Using Multi modal Approaches 390-403
  Sumathi S , Jayaseelan S , Kevin Jeyaraj P
• BI-LSTM and Hybrid Model Based Approaches for Accurate Sarcasm Identification in Tamil and Malayalam Languages 404-410
  Kogilavani S V , Malliga Subramnanian , Sanjai R , Mohammed Sameer B , Motheeswaran K
• Leveraging Machine Learning and BERT for Sarcasm Detection in Text 411-417
  Kogilavani S V , Priyadharshini C , Varshini L , Sathyaa S
• Sarcasm Detection in Dravidian Languages Using Machine Learning and Transformer Models 418-422
  Malliga Subramnanian , Aruna A , Anbarasan T , Amudhavan M , Kogilavani S V

Personalized Information Retrieval (PIR)

• Overview of the PIR Track at FIRE 2024: Evaluation of Personalised Information Retrieval 423-426
  Pranav Kasela , Marco Braga , Effrosyni Sokli , Gian Carlo Milanese , Georgios Peikos , Sandip Modha , Alessandro Raganato , Marco Viviani , Gabriella Pasi
• Fusing Retrieval Techniques for Enhanced Personalized Community Question Answering 427-431
  Vraj Patel , Palak Vanpariya , Kandarp Gajjar , Himani Trivedi

CryptOQA: Opinion Extraction and Question Answering from CryptoCurrency-Related Tweets and Reddit posts

• Overview of CryptOQA: Opinion Extraction and Question Answering from CryptoCurrency-Related Tweets and Reddit posts 432-438
  Gourav Sen , Sougata Sarkar , Subham Kumar , Koustav Rudra , Kripabandhu Ghosh
• CryptoLLM: Unleashing the Power of Prompted LLMs for SmartQnA and Classification of Crypto Posts 439-447
  Aniket Deroy , Subhankar Maity
• Navigating Crypto Conversations: A Multi-Level Approach to Classify Cryptocurrency Opinions on Social Media 448-455
  Kavya G , Sonith D , H L Shashirekha
• CryptoOpinionMining: A Comparative Analysis of Hierarchical and Flat Classification Models for Social Media Content 456-463
  Rudra Roy , Pritam Pal , Rishika Jha , Dipankar Das

Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages (HASOC)

• Overview of the HASOC Track at FIRE 2024: Hate-Speech Identification in English and Bengali 464-474
  Nishat Raihan , Koyel Ghosh , Sandip Modha , Shrey Satapara , Tanishka Gaur , Yaashu Dave , Marcos Zampieri , Sylvia Jaki , Thomas Mandl
• Hate Speech and Offensive Content Identification in English Language Based on BERT Model 475-481
  Jing Li , Xutao Yang
• Detecting Hate Speech and Offensive Content in English: A Model Using DistilBERT and A Model Based on FastText Strategies 482-492
  Kongqiang Wang , Xiaobing Zhou
• Detection of Hate Speech using Universal Sentence Encoding and Bidirectional Long Short-Term Memory Models 493-502
  Pedro Alonso , György Kovács , Rajkumar Saini , Marcus Liwicki
• HateGPT: Unleashing GPT-3.5 Turbo to Combat Hate Speech on X 503-510
  Aniket Deroy , Subhankar Maity
• Zero-Shot and Multitask Learning Synergy for Robust Hate Speech Detection across English and Bangla 511-521
  Kavya G , Asha Hegde , Sonith D , Subrahmanya , H L Shashirekha
• Detecting Hate Speech in Bangla: A Hybrid Model Using Machine Learning and Lexicon-Based Strategies 522-528
  Vinayak Vijay , Avishikta Bhattacharjee , Kirti Kumari , Upkar Kumar Kedia
• Detecting Hate Speech in Hinglish: A BiLSTM Neural Network Approach 529-534
  Kirti Kumari , Avishikta Bhattacharjee , Vinayak Vijay

Spoken-Query Cross-Lingual Information Retrieval for the Indic Languages (SqCLIR)

• Overview of the FIRE 2024 SqCLIR Track: Spoken Query Cross-Lingual Information Retrieval for the Indic Languages 535-540
  Bhargav Dave , Prasenjit Majumder , Debasis Ganguly , Evangelos Kanoulas
• Spoken Query Retrieval in Monolingual Contexts with Whisper and SBERT Models 541-548
  Prabhu Ram Nagarajan , Livin Nector Dhasan , Meera Devi Thiagarajan

Information Retrieval in Software Engineering (IRSE)

• LLMs for Code: Overview of the information retrieval in software engineering track at fire 2024 549-555
  Soumen Paul , Srijoni Majumdar , Raj Shah , Susmita Das , Madhusudan Ghosh , Debasis Ganguly , Gul Calikli , Debarshi Sanyal , Partha Pratim Das , Paul D. Clough , Ayan Bandhyopadhyay , Samiran Chattopadhyay
• Categorizing Code Comments based on its Relevance for Code Readability 556-561
  Om Joshi
• Can we predict Comment Quality using Machine Learning? 562-567
  Ashwin Gaikwad
• Code and Comment Classification in C using Machine Learning 568-573
  Sahil Walunj
• Code and Comments Categorization in terms of Program Comprehension 574-579
  Abhinav Daggubelli
• Assessing the Quality of Source Code Comments with Binary Classification Models 580-586
  Krishna K
• Improving Code Readability: A Machine Learning Approach to Classifying Valuable Source Code Comments 587-593
  Subhash Agrawal
• Source Code Comment Classification in C 594-599
  Devyani Remulkar
• Classification of Code and Comments in a Machine Learning Framework 600-605
  Adwita Deshpande
• Classifying useful and not useful code comments in C 606-610
  Atharva Keny
• Enhancing Code Annotation Reliability: Generative AI’s Role in Comment Quality Assessment Models 611-619
  Seetharam Killivalavan , Durairaj Thenmozhi
• Improving Binary Code Comment Quality Classification with Augmented Code-Comment Pairs Using Generative AI 620-629
  Rohith Arumugam , Angel Deborah
• Assessing the Utility of C Comments with SVM and Naïve Bayes Classifier 630-634
  Anamitra Mukhopadhyay
• Exploring Usefulness of C Comments with Silver-Standard Machine Learning Models 635-640
  Aritra Mitra
• Coding Smarter Not Harder: Leveraging GPT-3.5 Turbo for Automated Code Solution Scoring 641-646
  Aniket Deroy , Subhankar Maity

Conversational System for Differential Diagnosis of GI Cancer

• Conversational System for Differential Diagnosis of GI Cancer: Track Overview 647-650
  Manjira Sinha , Rajat Pal , Tirthankar Dasgupta
• Cancer-Answer: Empowering Cancer Care with Advanced Large Language Models 651-659
  Aniket Deroy , Subhankar Maity
• A Retrieval-Augmented Generation (RAG) Pipeline for GI-Cancer Prediction and Classification Using Quantized Large Language Models 660-665
  Arti Jha , Nidhi Shah , Vikas Kumawat , Yashvardhan Sharma
• Gastrointestinal Cancer Related Question Answering Using BERT 666-671
  S ArunaDevi , J Abirami , B Bharathi