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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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title: ‘Blog Post 1 - Coming Soon!’ date: 2018-06-20 permalink: /posts/2018/06/blog-post-1/ tags:
- research conferences
Published in LSDSem at EACL, 2017
Recommended citation: Goel, Pranav, and Anil Kumar Singh. "IIT (BHU): System Description for LSDSem17 Shared Task." Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics. 2017.
Prayas at EmoInt 2017: An Ensemble of Deep Neural Architectures for Emotion Intensity Prediction in Tweets [Shared Task WINNER]
Published in WASSA at EMNLP, 2017
Recommended citation: Goel, Pranav, et al. "Prayas at EmoInt 2017: An Ensemble of Deep Neural Architectures for Emotion Intensity Prediction in Tweets." Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. 2017.
Published in LREC, 2018
Recommended citation: Joshi, Aditya, Pranav Goel, Pushpak Bhattacharyya, and Mark J. Carman. "Sarcasm Target Identification: Dataset and An Introductory Approach." LREC 2018-11th edition of the Language Resources and Evaluation Conference. 2018.
Published in IWSDS, 2018
Recommended citation: Goel, Pranav, Yoichi Matsuyama, Michael Madaio, and Justine Cassell. "I think it might help if we multiply, and not add": Detecting Indirectness in Conversation. In: Proceedings of the International Workshop Series on Spoken Dialogue Systems Technology (IWSDS). 2018.
Published in International Conference on Computational Linguistics (COLING 2018), 2018
Recommended citation: Kulshreshtha, Devang, Pranav Goel, and Anil Kumar Singh. "How emotional are you? Neural Architectures for Emotion Intensity Prediction in Microblogs." Proceedings of the 27th International Conference on Computational Linguistics. 2018.
Published in COIN at EMNLP, 2019
Recommended citation: Goel, Pranav, et al. "How Pre-trained Word Representations Capture Commonsense Physical Comparisons" Proceedings of the 1st Workshop on Commonsense Inference in Natural Language Processing at EMNLP. 2019.
Poster presented for the system description paper accepted in the Story Cloze shared task at LSDSem, EACL 2017.
Final presentation describing my work during my summer research internship, working on the conversational strategy classifier for the SARA (Socially Aware Robot Assistant) project at Articulab, CMU.
Prayas at EmoInt 2017: An Ensemble of Deep Neural Architectures for Emotion Intensity Prediction in Tweets
Oral presentation for the EmoInt shared task winning system description paper accepted at WASSA, EMNLP 2017. Presentation with my voice-over was played at the workshop.
Seminal talk on the topic Transfer Learning.
A Seminar Talk on the Running Time of a Movie, for my undergrad course on Film Appreciation.
An informative talk given to undergraduates across the insititue, on applying for MS/PhD as an International/Indian student to (mainly) US schools. Presentation created with CS and related fields in mind.
Poster presentation for the full paper accepted at LREC 2018. Presented by a colleague at the conference.
Oral presentation for the full paper accepted at IWSDS 2018.
Course Presentation for the Deep Learning Course, Fall 2018.
Oral Presentation (delivered remotely) at COIN (COmmonsense INference in Natural Language Processing), EMNLP 2019.
Undergraduate (Freshmen) course, Indian Institute of Technology (BHU) Varanasi, 2017
Taught about 120 freshmen the basics of programming using C language for lab practicals. Designed assignments and helped take the first step towards an online local evaluation portal for conducting assignments and tests.
Undergraduate (Sophomore) Course, Department of Computer Science and Engineering, Indian Institute of Technology (BHU) Varanasi, 2018
Took the lab for discussion of concepts as well as programming assignments for about 80 computer science sophomores. Created a set of programming assignments from the scratch, with the help of colleagues, including starter and supporting codes and proper README based instructions. Topics covered included search, logic and machine learning.
Undergraduate Course, Computer Science, University of Maryland, 2018