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ORCIDFIRE 2023: Panjim / Goa, India - Working Notes
- Kripabandhu Ghosh, Thomas Mandl, Prasenjit Majumder, Mandar Mitra:
Working Notes of FIRE 2023 - Forum for Information Retrieval Evaluation (FIRE-WN 2023), Goa, India, December 15-18, 2023. CEUR Workshop Proceedings 3681, CEUR-WS.org 2024 - Preface.
Artificial Intelligence on Social Media (AISoMe)
- Moumita Basu, Soham Poddar, Moumita Basu, Saptarshi Ghosh, Kripabandhu Ghosh:
Overview of the FIRE 2023 Track: Artificial Intelligence on Social Media (AISoMe). 1-5 - Aritra Mandal:
Enhancing Multilabel Classification of Anti-Vaccine Tweets with the COVID-Twitter-BERT. 6-11 - Kaustav Das:
Vaccine Vision: A deep learning approach towards identifying societal concerns regarding vaccines. 12-17 - Aniket Deroy, Subhankar Maity:
Multi-Label Classification of COVID-Tweets Using Large Language Models. 18-23 - Swastik Anupam:
Tweet Classifier: Advancements in Multi-Label Analysis. 24-29 - Sumit Das, Palvika Bansal, Vikas Rai, Shalini Kumari:
Multi-label Classification of Covid-19 Vaccine Tweet. 30-43 - Shankha S. Das, Sohan Choudhury, Priyam Saha, Dipankar Das:
VaxTweetClassifier: BERT for Dealing with Vaccination Tweets. 44-51 - Aditya O. Patil, Raj Awate, Shivakumar Ranade, Sheetal Sonawane:
VaxVerdict: a RoBERTa Based Multilabel Tweet Classifier. 52-58 - Rajat Singh, Shivangi Bithel, Samidha Verma, Prachi:
VaxiBERT: A BERT-Based Classifier for Vaccine Tweets with Multi-Label Annotations. 59-66 - Shriram M. S:
Deciphering Vaccine Sentiments: Transformer Models in Social Media Analysis. 67-74 - Ranjit Patro, Asutosh Mishra:
BERT-Powered Multi-label Classifier: Analyzing Public COVID Vaccination Discourse. 75-81 - Lakshmi Gopal:
Analysing Crowd-Sourced Vaccine Data Using Machine Learning: Uncovering Concerns and Insights. 82-90 - K. Shanmukha Naveen, S. Sharon Roshini, S. Karthika:
Unveiling Diverse Vaccine Sentiments: Multi-Label Text Classification. 91-98 - Somsubhra De, Shaurya Vats:
Decoding Concerns: Multi-label Classification of Vaccine Sentiments in Social Media. 99-111 - Baivab Chakraborty, Subhajit Srimani, Souvit Biswas:
TweetClass: COVID-19 Vaccine Tweet Classification with scikit-learn. 112-117
Cross-lingual Information Retrieval for African Languages (CIRAL)
- Mofetoluwa Adeyemi, Akintunde Oladipo, Xinyu Crystina Zhang, David Alfonso-Hermelo, Mehdi Rezagholizadeh, Boxing Chen, Jimmy Lin:
Overview of the CIRAL Track at FIRE 2023: Cross-lingual Information Retrieval for African Languages. 118-136 - Eugene Yang, Dawn J. Lawrie, Paul McNamee, James Mayfield:
Extending Translate-Train for ColBERT-X to African Language CLIR. 137-146
Uncovering Truth in Social Media through Claim Detection and Identification of Claim Spans (CLAIMSCAN)
- Megha Sundriyal, Md. Shad Akhtar, Tanmoy Chakraborty:
Overview of the CLAIMSCAN-2023: Uncovering Truth in Social Media through Claim Detection and Identification of Claim Spans. 147-158 - Albert Pritzkau, Julia Waldmüller, Olivier Blanc, Michaela Geierhos, Ulrich Schade:
Current language models' poor performance on pragmatic aspects of natural language. 159-169 - Michael Sullivan, Navid Madani, Sougata Saha, Rohini K. Srihari:
Positional Transformers for Claim Span Identification. 170-178
Word-level Language Identification in Code-mixed Tulu Texts (CoLI-Tunglish)
- Asha Hegde, Fazlourrahman Balouchzahi, Sharal Coelho, H. L. Shashirekha, Hamada A. Nayel, Sabur Butt:
Overview of CoLI-Tunglish: Word-level Language Identification in Code-mixed Tulu Text at FIRE 2023. 179-190 - Yves Bestgen:
Using Character Ngrams for Word-Level Language Identification in Trilingual Code-Mixed Data (and Even More). 191-197 - Poorvi Shetty:
Word-Level Language Identification of Code-Mixed Tulu-English Data. 198-204 - Ahmed M. Fetouh, Hamada Nayel:
BFCAI at CoLI-Tunglish@FIRE 2023: Machine Learning Based Model for Word-level Language Identification in Code-mixed Tulu Texts. 205-212 - Sushma N, Asha Hegde, Hosahalli Lakshmaiah Shashirekha:
Word-level Language Identification in Code-mixed Tulu Texts. 213-222 - Supriya Chanda, Anshika Mishra, Sukomal Pal:
Advancing Language Identification in Code-Mixed Tulu Texts: Harnessing Deep Learning Techniques. 223-230
Scarcasm Identification of Dravidian Languages (Malayalam and Tamil) in DravidianCodeMix 2023 (DravidianCodeMix)
- Bharathi Raja Chakravarthi, Sripriya N, Bharathi B, Nandhini K, Subalalitha Chinnaudayar Navaneethakrishnan, Thenmozhi Durairaj, Rahul Ponnusamy, Prasanna Kumar Kumaresan, Kishore Kumar Ponnusamy, Charmathi Rajkumar:
Overview of Sarcasm Identification of Dravidian Languages in DravidianCodeMix@FIRE-2023. 231-239 - Poorvi Shetty:
Sarcasm Identification in Dravidian Languages Tamil and Malayalam. 240-248 - Anik Basu Bhaumik, Mithun Das:
Sarcasm Detection in Dravidian Code-Mixed Text Using Transformer-Based Models. 249-258 - Dhanya Krishnan, Krithika Dharanikota, B. Bharathi:
Cross-Linguistic Sarcasm Detection in Tamil and Malayalam: A Multilingual Approach. 259-269 - Anusha M. D, Parameshwar R. Hegde:
Unmasking Sarcasm: Sarcastic Language Detection with BiLSTMs. 270-277 - Ramya Sivakumar, Jerin Mahibha C, B. Monica Jenefer:
Identifying the Type of Sarcasm in Dravidian Languages using Deep-Learning Models. 278-286 - Navya N, Vanitha V, Asha Hegde, H. L. Shashirekha:
Learning Models with Text Augmentation for Sarcasm Detection in Malayalam and Tamil Code-mixed Texts. 287-298 - Shanmitha Thirumoorthy, Manavh N. R, Durairaj Thenmozhi, Ratnavel Rajalakshmi:
A Few Shot Learning to Detect Sarcasm in Tamil and Malayalam Code Mixed Data. 299-305 - Madhumitha. M, Kunguma Akshatra. M, Tejashri. J, C. Jerin Mahibha, Durairaj Thenmozhi:
Sarcasm Detection in Dravidian Languages using Transformer Models. 306-318 - Prabhu Ram. N, Meera Devi. T, Kanisha. V, Meharnath. S, Manoji. B:
Sarcasm Identification in Codemix Dravidian Languages. 319-326 - V. Indirakanth, Dharunkumar Udayakumar, Thenmozhi Durairaj, B. Bharathi:
Sarcasm Identification Of Dravidian Languages (Malayalam and Tamil). 327-335 - Supriya Chanda, Anshika Mishra, Sukomal Pal:
Sarcasm Detection in Tamil and Malayalam Dravidian Code-Mixed Text. 336-343
Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages (HASOC)
- Shrey Satapara, Hiren Madhu, Tharindu Ranasinghe, Alphaeus Eric Dmonte, Marcos Zampieri, Pavan Pandya, Nisarg Shah, Sandip Modha, Prasenjit Majumder, Thomas Mandl:
Overview of the HASOC Subtrack at FIRE 2023: Hate-Speech Identification in Sinhala and Gujarati. 344-350 - Hiren Madhu, Shrey Satapara, Pavan Pandya, Nisarg Shah, Thomas Mandl, Sandip Modha:
Overview of the HASOC Subtrack at FIRE 2023: Identification of Conversational Hate-Speech. 351-359 - Sarah Masud, Mohammad Aflah Khan, Md. Shad Akhtar, Tanmoy Chakraborty:
Overview of the HASOC Subtrack at FIRE 2023: Identification of Tokens Contributing to Explicit Hate in English by Span Detection. 360-367 - Koyel Ghosh, Apurbalal Senapati, Aditya Shankar Pal:
Annihilate Hates (Task 4 HASOC 2023): Hate Speech Detection in Assamese Bengali and Bodo languages. 368-382 - Olumide Ebenezer Ojo, Olaronke Oluwayemisi Adebanji, Hiram Calvo, Alexander F. Gelbukh, Anna Feldman, Grigori Sidorov:
Hate and Offensive Content Identification in Indo-Aryan Languages using Transformer-based Models. 383-392 - Niyar R. Barman, Krish Sharma, Yashraj Poddar, Advaitha Vetagiri, Partha Pakray:
Addressing Hate Speech: ATLANTIS for Efficient Hate Span Detection. 393-402 - Mohammadmostafa Rostamkhani, Sauleh Eetemadi:
Detecting Hate Speech and Offensive Content in English and Indo-Aryan Texts. 403-410 - Yves Bestgen:
Using Only Character Ngrams for Hate Speech and Offensive Content Identification in Five Low-Ressource Languages. 411-417 - Avigail Stekel, Avital Prives, Yaakov HaCohen-Kerner:
Detecting Offensive Language in Bengali Bodo and Assamese using Word Unigrams Char N-grams Classical Machine Learning and Deep Learning Methods. 418-426 - Ananya Joshi, Raviraj Joshi:
Harnessing Pre-Trained Sentence Transformers for Offensive Language Detection in Indian Languages. 427-434 - G. Gnana Sai, Aswath Venkatesh, Kishore N, Olirva M, Balaji V. A, Prabavathy Balasundaram:
Enhancing Hate Speech Detection in Sinhala and Gujarati: Leveraging BERT Models and Linguistic Constraints. 435-444 - Abhinav Reddy Gutha, Nidamanuri Sai Adarsh, Ananya Alekar, Dinesh Reddy:
Multilingual Hate Speech and Offensive Language Detection of Low Resource Languages. 445-458 - Ch Muhammad Awais, Jayveersinh Raj:
Breaking Barriers: Multilingual Toxicity Analysis for Hate Speech and Offensive Language in Low-Resource Indo-Aryan Languages. 459-473 - Gyandeep Kalita, Eisha Halder, Chetna Taparia, Advaitha Vetagiri, Partha Pakray:
Examining Hate Speech Detection Across Multiple Indo-Aryan Languages in Tasks 1 & 4. 474-485 - Supriya Chanda, Abhishek Dhaka, Sukomal Pal:
Crossing Borders: Multilingual Hate Speech Detection. 486-500 - Muhammad Deedahwar Mazhar Qureshi, Madhuri Sawant, Muhammad Atif Qureshi, Wael Rashwan, Arjumand Younus, Simon Caton:
Hate speech classification for Sinhalese and Gujarati. 501-515 - Sougata Saha, Michael Sullivan, Rohini K. Srihari:
Hate Speech Detection in Low Resource Indo-Aryan Languages. 516-520 - M. Krithik Sathya, K. H. Gopalakrishnan, Manickam PA, Prabavathy Balasundaram:
Sinhala and Gujarati Hate Speech Detection. 521-531 - Jhuma Kabir Mim, Mourad Oussalah, Akash Singhal:
Cross-Linguistic Offensive Language Detection: BERT-Based Analysis of Bengali Assamese & Bodo Conversational Hateful Content from Social Media. 532-543 - Surya Agustian, Zaky Idhafi, Agit Fadillah Rihardi:
Improving Detection of Hate Speech, Offensive Language and Profanity in Short Texts with SVM Classifier. 544-552 - Chandan Senapati, Utpal Roy:
Bengali Hate Speech Detection Using Deep Learning Technique. 553-562 - Prajnashree M, Rachana K, Asha Hegde, Kavya Girish, Sharal Coelho, H. L. Shashirekha:
Taming Toxicity: Learning Models for Hate Speech and Offensive Language Detection in Social Media Text. 563-573 - Nikhil Narayan, Mrutyunjay Biswal, Pramod Goyal, Abhranta Panigrahi:
Hate Speech and Offensive Content Detection in Indo-Aryan Languages: A Battle of LSTM and Transformers. 574-587 - Md Saroar Jahan, Fadi Hassan, Walid Aransa, Abdessalam Bouchekif:
Multilingual Hate Speech Detection Using Ensemble of Transformer Models. 588-597
Information Retrieval in Software Engineering (IRSE)
- Srijoni Majumdar, Soumen Paul, Bhargav Dave, Debjyoti Paul, Ayan Bandyopadhyay, Samiran Chattopadhyay, Partha Pratim Das, Paul D. Clough, Prasenjit Majumder:
Generative AI for Software Metadata: Overview of the Information Retrieval in Software Engineering Track at FIRE 2023. 598-604 - Hanna Abi Akl:
A ML-LLM pairing for better code comment classification. 605-614 - Seetharam Killivalavan, Durairaj Thenmozhi:
Software Metadata Classification based on Generative Artificial Intelligence. 615-623 - Samah Syed, Angel Deborah S:
Leveraging Generative AI: Improving Software Metadata Classification with Generated Code-Comment Pairs. 624-632 - Trisha Datta:
Source Code Comment Classification using machine learning algorithms. 633-641 - Rohith Arumugam S, Angel Deborah S:
Enhancing Binary Code Comment Quality Classification: Integrating Generative AI for Improved Accuracy. 642-651 - Lisa Sarkar:
Binary Classification of Source Code Comments using Machine Learning Models. 652-660 - Tripti Kumari, Chakali Sai Charan, Ayan Das:
A study of the impact of generative AI-based data augmentation on software metadata classification. 661-669 - Jagrat T. Patel:
Leveraging Language Models for Code Comment Classification. 670-678 - Jaivin Barot:
Enhancing Code Comment Classification Using Language Models. 679-688 - Aritra Mitra:
Assessing the Utility of C Comments with SVM and Naïve Bayes Classifier. 689-695 - Raj Jitendra Shah:
Source Code Comment Classification using Naive Bayes and Support Vector Machine. 696-703 - Vishesh Agarwal:
On the Impact of Synthetic Data on Code Comment Usefulness Prediction. 704-710 - Priyam Dalmia:
Exploring LLM-based Data Augmentation Techniques for Code Comment Quality Classification. 711-717 - Paheli Bhattacharya, Manojit Chakraborty, Kartheek N. S. N. Palepu, Vikas Pandey, Ishan Dindorkar, Rakesh Rajpurohit, Rishabh Gupta:
Exploring Large Language Models for Code Explanation. 718-723
Indian Language Summarization (ILSUM)
- Shrey Satapara, Parth Mehta, Sandip Modha, Debasis Ganguly:
Key Takeaways from the Second Shared Task on Indian Language Summarization (ILSUM 2023). 724-733 - Aniket Deroy, Subhankar Maity, Saptarshi Ghosh:
Prompted Zero-Shot Multi-label Classification of Factual Incorrectness in Machine-Generated Summaries. 734-746 - Saliq Gowhar, Bhavya Sharma, Ashutosh K. Gupta, Anand Kumar Madasamy:
Advancing Human-Like Summarization: Approaches to Text Summarization. 747-754 - Saumay Gupta, Sukomal Pal:
Named Entity-Aware Abstractive Text Summarization for Hindi Language. 755-765 - V. Ilanchezhiyan, R. Darshan, E. M. Milin Dhitshithaa, B. Bharathi:
Text Summarization for Indian Languages: Finetuned Transformer Model Application. 766-774
Machine Translation for Indian Languages (MTIL)
- Surupendu Gangopadhyay:
Overview of MTIL Track at FIRE 2023: Machine Translation for Indian Languages. 775-782 - Rakesh Chandra Balabantaray:
Hindi-Odia Machine Translation System. 783-789 - Amulya Ratna Dash:
Fine tuning based Domain Adaptation for Machine Translation of Low Resource Indic Languages. 790-795 - Mukund K. Roy:
Bidirectional Hindi-Punjabi Machine Translation. 796-801
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