BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Computer Science and Engineering - ECPv6.13.0//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://homecse.iitd.ac.in
X-WR-CALDESC:Events for Computer Science and Engineering
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Asia/Kolkata
BEGIN:STANDARD
TZOFFSETFROM:+0530
TZOFFSETTO:+0530
TZNAME:IST
DTSTART:20260101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260115T110000
DTEND;TZID=Asia/Kolkata:20260115T120000
DTSTAMP:20261010T153546
CREATED:20260114T064025Z
LAST-MODIFIED:20260114T064025Z
UID:2361-1768474800-1768478400@homecse.iitd.ac.in
SUMMARY:Agentic Information Seeking for Knowledge Acquisition by Revanth Reddy
DESCRIPTION:Venue: SIT001 \nAbstract:  The vast expansion of online information has shifted the challenge from simply locating data to efficiently filtering and aggregating relevant content from diverse sources. This talk introduces innovative methodologies aimed at enhancing automated information seeking capabilities within intelligent systems. I will present a modular\, agent-based framework that decomposes the information-seeking process into navigation\, extraction\, and aggregation components. This approach enables exploratory behaviors that significantly outperform current web agents. Next\, I will discuss the application of these techniques to tackle novel challenges in knowledge acquisition across various domains: 1) Automated Wikipedia Updates: An approach to automatically update and maintain Wikipedia articles using real-time online sources\, and 2) Software Issue Localization: How enabling information-seeking over code repositories helps identify and address localization issues for software problems. \nBio: Revanth Gangi Reddy is a research scientist at Google DeepMind\, working on Gemini Post-Training. He finished his Ph.D. in Computer Science at the University of Illinois Urbana-Champaign\, advised by Prof. Heng Ji. His research interests lie in knowledge-driven natural language processing\, focusing on agentic search\, ranking models\, and retrieval-augmented generation. Revanth’s work has been published in leading conferences such as ICLR\, ACL\, AAAI\, EMNLP\, NAACL\, and SIGIR\, and he also presented a tutorial on Open-Retrieval Question Answering at IJCAI 2023. Revanth has previously done research internships at Salesforce Research\, Apple\, AI2\, IBM Research\, and Amazon Science\, and was the team lead for UIUC at the Alexa SocialBot Grand Challenge 5. Revanth holds a Bachelor’s degree in Computer Science from the Indian Institute of Technology Madras and is a Siebel Scholar (class of 2022).
URL:https://homecse.iitd.ac.in/event/agentic-information-seeking-for-knowledge-acquisition-by-revanth-reddy/
LOCATION:SIT 001\, Amar Nath and Shashi Khosla School of Information Technology\, IIT Delhi\, Hauz Khas\, New Delhi 110016\, India\, Delhi\, Delhi\, 110016\, India
END:VEVENT
END:VCALENDAR