🏙️ Delhi

🏛️ Institutions (5)

4 universities, 1 research institute.

🎓 Universities (4)

1. 🎓Indraprastha Institute of Information Technology DelhiUniversity · Delhi, India7 works · 1,233 citations
2. 🎓Indian Institute of Technology DelhiUniversity · New Delhi, India10 works · 915 citations
3. 🎓Delhi Technological UniversityUniversity · New Delhi, India2 works · 188 citations
4. 🎓Netaji Subhas University of TechnologyUniversity · New Delhi, India2 works · 56 citations

🔬 Labs and research institutes (1)

1. 🔬IBM Research - IndiaResearch institute · New Delhi, India6 works · 715 citations

📄 Works in our library (24)

Works of its institutions, the most cited first.

1. SemEval-2020 Task 8: Memotion Analysis- the Visuo-Lingual Metaphor!International Workshop on Semantic Evaluation (SemEval)Chhavi Sharma, Deepesh Bhageria, William Scott, et al.2020 · 260 citations
2. Factuality Challenges in the Era of Large Language ModelsNature Machine IntelligenceIsabelle Augenstein, Timothy Baldwin, Meeyoung Cha, et al.2023 · 242 citations
3. SemEval-2020 Task 9: Overview of Sentiment Analysis of Code-Mixed TweetsInternational Workshop on Semantic Evaluation (SemEval)Parth Patwa, Gustavo Aguilar, Sudipta Kar, et al.2020 · 240 citations
4. Humanity's Last ExamNatureLong Phan, Alice Gatti, Ziwen Han, et al.2025 · 235 citations
5. A Deep Generative Framework for Paraphrase GenerationarXiv:1709.05074Ankush Gupta, Arvind Agarwal, Prawaan Singh, et al.2017 · 232 citations
6. MOMENTA: A Multimodal Framework for Detecting Harmful Memes and Their TargetsFindings of the Association for Computational LinguisticsShraman Pramanick, Shivam Sharma, Dimitar Dimitrov, et al.2021 · 212 citations
7. Detecting Harmful Memes and Their TargetsFindings of the Association for Computational LinguisticsShraman Pramanick, Dimitar Dimitrov, Rituparna Mukherjee, et al.2021 · 171 citations
8. Explanations for CommonsenseQA: New Dataset and ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Shourya Aggarwal, Divyanshu Mandowara, Vishwajeet Agrawal, et al.2021 · 163 citations
9. Learning Cognitive Features from Gaze Data for Sentiment and Sarcasm Classification using Convolutional Neural NetworkAnnual Meeting of the Association for Computational Linguistics (ACL)Abhijit Mishra, Kuntal Dey, Pushpak Bhattacharyya2017 · 141 citations
10. Edition 1.1 of the PARSEME Shared Task on Automatic Identification of Verbal Multiword ExpressionsInternational Conference on Computational Linguistics (COLING)Carlos Ramisch, Silvio Ricardo Cordeiro, Agata Savary, et al.2018 · 124 citations
11. Evaluating Explanations: How Much Do Explanations from the Teacher Aid Students?Transactions of the Association for Computational Linguistics (TACL)Danish Pruthi, Rachit Bansal, Bhuwan Dhingra, et al.2022 · 107 citations
12. Harnessing Cognitive Features for Sarcasm DetectionAnnual Meeting of the Association for Computational Linguistics (ACL)Abhijit Mishra, Diptesh Kanojia, Seema Nagar, et al.2016 · 85 citations
13. Multilingual LLMs are Better Cross-lingual In-context Learners with AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Eshaan Tanwar, Subhabrata Dutta, Manish Borthakur, et al.2023 · 81 citations
14. Speaker and Time-aware Joint Contextual Learning for Dialogue-act Classification in Counselling ConversationsACM International Conference on Web Search and Data Mining (WSDM)Ganeshan Malhotra, Abdul Waheed, Aseem Srivastava, et al.2021 · 64 citations
15. Context-Aware Sarcasm Detection Using BERTWorkshop on Figurative Language ProcessingArup Baruah, Kaushik Das, Ferdous Barbhuiya, et al.2020 · 59 citations
16. When did you become so smart, oh wise one?! Sarcasm Explanation in Multi-modal Multi-party DialoguesAnnual Meeting of the Association for Computational Linguistics (ACL)Shivani Kumar, Atharva Kulkarni, Md Shad Akhtar, et al.2022 · 51 citations
17. Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language ModelLeonie Weissweiler, Valentin Hofmann, Anjali Kantharuban2023 · 47 citations
18. Sarcasm Detection using Context Separators in Online DiscourseWorkshop on Figurative Language ProcessingTanvi Dadu, Kartikey Pant2020 · 37 citations
19. A Multimodal Corpus for Emotion Recognition in SarcasmLanguage Resources and Evaluation Conference (LREC)Anupama Ray, Shubham Mishra, Apoorva Nunna, et al.2022 · 35 citations
20. Towards Universal Dialogue Act Tagging for Task-Oriented DialoguesShachi Paul, Rahul Goel, Dilek Hakkani-Tur2019 · 19 citations
21. Effects of Duration, Locality, and Surprisal in Speech Disfluency Prediction in English Spontaneous SpeechSociety for Computation in Linguistics (SCiL)Samvit Dammalapati, Rajakrishnan Rajkumar, Sidharth Ranjan, et al.2021 · 14 citations
22. Recognizing Textual Entailment using Dependency Analysis and Machine LearningConference of the North American Chapter of the Association for Computational Linguistics: Student Research WorkshopNidhi Sharma, Richa Sharma, Kanad K. Biswas2015 · 8 citations
23. Can RNNs trained on harder subject-verb agreement instances still perform well on easier ones?Society for Computation in Linguistics (SCiL)Hritik Bansal, Gantavya Bhatt, Sumeet Agarwal2021 · 1 citation
24. Determinants of Hesitations and Repetitions in Hindi Spontaneous SpeechSociety for Computation in Linguistics (SCiL)Eashani Sharma, Ishita Arun, Samar Husain2026

📅 Works by year

2020s

2010s

🧭 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

Agglomerations: the GHSL Urban Centre Database 2025; populations: the GHSL functional urban areas 2015 (urban centre and commuting zone), else the urban centre, as each page says (European Commission, Joint Research Centre, CC BY 4.0). An institution belongs to the urban centre its coordinates (ROR, OpenAlex) fall in, or one within 5 km. Land: Natural Earth.

Updated 24 October 2026

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