Preetam Dammu

PhD Student, University of Washington, Seattle.

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Hello! I am a fourth-year PhD student at the University of Washington, Seattle. My research focuses on leveraging generative AI for information retrieval tasks and addressing challenges associated with its adoption. Alongside this, I have a long-standing interest in explainability and robustness in machine learning, which continues to shape my work today. I am fortunate to be advised by Prof. Chirag Shah.

News

Jul 14, 2025 New paper – Dynamic-KGQA: Framework for Generating Adaptive QA Datasets accepted at SIGIR 2025!
Jun 16, 2025 Interning with AWS AI this summer to work on dynamic evaluation of web agents.
Nov 7, 2024 New paper on autonomous generative agent for subjective needs accepted at WSDM 2025!
Sep 21, 2024 New preprint on covert harms in LLM conversations accepted at EMNLP 2024 (Main - Oral)!
Sep 20, 2024 New paper on claim-level verification and evidence attribution through KGs accepted at EMNLP 2024 (Findings)!

Selected Publications

  1. claimver_fig1.png
    ClaimVer: Explainable Claim-Level Verification and Evidence Attribution of Text Through Knowledge Graphs
    Preetam Prabhu Srikar Dammu, Himanshu Naidu, Mouly Dewan, and 4 more authors
    2024
  2. chast_fig1.png
    ’They are uncultured’: Unveiling Covert Harms and Social Threats in LLM Generated Conversations
    Preetam Prabhu Srikar Dammu, Hayoung Jung, Anjali Singh, and 2 more authors
    2024
  3. Neurips_XAIA.png
    Detecting Spurious Correlations via Robust Visual Concepts in Real and AI-Generated Image Classification
    Preetam Prabhu Srikar Dammu, and Chirag Shah
    In 37th Conference on Neural Information Processing Systems (NeurIPS), XAIA Workshop, 2023
  4. Dammu2023AddressingWD.png
    Addressing Weak Decision Boundaries in Image Classification by Leveraging Web Search and Generative Models
    Preetam Prabhu Srikar Dammu, Yunhe Feng, and Chirag Shah
    In International Joint Conference on Artificial Intelligence, 2023