
Yash Kumar Atri
University of Virginia
atri [at] virginia.edu
News
- Oct 2024 – Selected as DAAD AInet fellow 2024.
- June 2024 – Joined UVA as a postdoc.
- Feb 2024 – Presented at the ACM ARCS symposium at NISER Bhubaneswar.
- Dec 2023 – Gave tutorial at ICON 2023.
- Nov 2023 – Microsoft Travel Grant for EMNLP.
- Aug 2023 – Microsoft Travel Grant for SIGKDD.
- Apr 2023 – Webchair for Intl. Conf. on Big Data & AI.
About Me
Hi! I am a postdoc at the University of Virginia, working with Prof. Tom Hartvigsen. Before joining UVA, I completed my PhD in Computer Science and Engineering at IIIT Delhi, India, where I was advised by Prof. Vikram Goyal and Prof. Tanmoy Chakraborty. My research focuses on understanding and enhancing neural language generation models, particularly large language models (LLMs), and their applications in natural language processing tasks such as abstractive text summarization.
ResumeResearch Interests
I am interested in enabling language models to continuously learn and adapt beyond their initial pretraining. My current research explores model editing, developing methods to update models efficiently with new information and corrections. I build modular systems that apply each change locally, allowing the model to evolve while retaining its existing knowledge. My long-term vision is to create models that learn like humans: accumulating knowledge over time, refining their understanding, and remaining robust as language, technology, and societal values change. Such systems could become trusted AI partners in critical areas like healthcare, education, and policy, where outdated information is not just inconvenient but potentially harmful. Such systems could become trustworthy AI partners in critical domains like healthcare, education, and policy, where being outdated is not just a limitation but a serious risk.
Publications
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Model Editing with Graph-Based External Memory
Yash Kumar Atri, Ahmed Alaa, Thomas Hartvigsen
PreprintPreprint 2025
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Continually Self-Improving Language Models for Bariatric Surgery Question Answering
Yash Kumar Atri, Thomas H Shin, Thomas Hartvigsen
PreprintPreprint 2025
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Promoting Topic Coherence and Inter-Document Consorts in Multi-Document Summarization via Simplicial Complex and Sheaf Graph
Yash Kumar Atri, Arun Iyer, Tanmoy Chakraborty, Vikram Goyal
PaperEMNLP 2023
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Exploiting Representation Bias for Data Distillation in Abstractive Text Summarization
Yash Kumar Atri, Tanmoy Chakraborty, Vikram Goyal
PaperArxiv 2023
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Multi-Document Summarization using Selective Attention Span and Reinforcement Learning
Yash Kumar Atri, Tanmoy Chakraborty, Vikram Goyal
PaperTASL 2023
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Fusing Multimodal Signals on Hyper-complex Space for Extreme Abstractive Text Summarization (TL;DR) of Scientific Contents
Yash Kumar Atri, Tanmoy Chakraborty, Vikram Goyal
PaperSIGKDD 2023
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Inline Citation Classification using Peripheral Context and Time-evolving Augmentation
Priyanshi Gupta, Yash Kumar Atri, Apurva Nagvenkar, Sourish Dasgupta, Tanmoy Chakraborty
PaperPAKDD 2023
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See, Hear, Read: Leveraging Multimodality with Guided Attention for Abstractive Text Summarization
Yash Kumar Atri*, Shraman Pramanick*, Vikram Goyal, Tanmoy Chakraborty
PaperKBS 2021
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Assessing the Quality of the Datasets by Identifying Mislabeled Samples
Vaibhav Pulastya, Gaurav Nuti, Yash Kumar Atri, Tanmoy Chakraborty
PaperASONAM 2021
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Corpora Evaluation and System Bias detection in Multi Document Summarization
Alvin Dey*, Tanya Chowdhury*, Yash Kumar Atri*, Tanmoy Chakraborty
PaperEMNLP (Findings) 2020
Patents
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SYSTEM AND METHOD FOR TEXT SUMMARIZATION, Application Number 202311015836, Publication Number 37/2024
Simran Kalra, Yash Kumar Atri, Tanmoy Chakraborty
Patent2024
Tutorials
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Building Blocks of AI-Driven Mental Health Counseling
Aseem Srivastava, Neeraj, Yash Kumar Atri, Shivani Kumar, Shad Akhtar, Tanmoy Chakraborty
Website2023
Teaching
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CSE557 - Big Data Analytics (Winter 2020), CSE506 - Data Mining (Monsoon 2020), CSE557 (Winter 2021), CSE506 (Monsoon 2021)
Head TA (Class of 300+ students)
TechTree'20-21
Invited Talks
- Lamarr Institute NLProc Colloquium at UBonn, Germany - title: Waking LLMs from CryoSleep with Continual Learning
- ACM-India's Symposium for Academic Research and Careers for Students 2023, NISER Bhubhaneswar, India - title: Fairness in Abstractive Text Summarization
- RIISE 2024, IIIT Delhi - Poster Presentation
Program Committees
- Reviewer - ARR25, ICLR25, ARR24, EMNLP23, ACL23, BDA23, ICON22, EMNLP22, ASONAM22
- Organizer & Coordinator - BDA 2023 conf, ICON 2023 conf, ACSS 2022, 2021, 2020, Cofad 2020 Workshops
Awards and Achievements
- DAAD AInet Fellow 2025 - Postdoc-NeT-AI, Germany
- Microsoft Travel Grant, iHub-Anubhuti Travel Grant - For Travel to Singapore for EMNLP 2023
- Microsoft Travel Grant, iHub-Anubhuti Travel Grant, ACM-India Travel Grant (IARCS) - For Travel to Long Beach, USA for KDD 2023
Education
- Ph.D. CSE, IIIT Delhi, India, 2020-2024
- B. Tech. CSE, Jaypee University, India 2014-2018
Professional Experience
- Research Associate at LCS2-IIITD, Sep. 2019-Aug. 2019
- Software Engineer (Data Science) at Lumiq.ai, July 2018-Aug. 2019
- AI Engineer (Intern) at Lumiq.ai, Feb. 2018-Jun. 2019
- Data Scientist (Intern) at Primelite Technologies, May 2017-July 2017
- Android Developer (Intern) at Trignosoft Technologies, May 2017-June 2017
Contact
Email: yashkumaratri [at] gmail.com Work Email: atri [@] virginia.edu Phone: +1 (434)-**6-1**1 (Please drop an email)