Ameya Godbole

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I am a fourth year PhD student in Computer Science at the University of Southern California advised by Prof. Robin Jia. I work on hallucination-free and faithful generation with retrieval augmentation. I worked on leveraging the planning capabilities of LLMs to guide retrieval. I also study the behavior of factuality detection systems and their reliability in model selection. In the past, I have worked on retrieval for open-domain question answering (ODQA), knowledge base completion (KBC), and semantic parsing for knowledge base QA (KBQA).

Previously, I was a Research Fellow with the wonderful Information Extraction and Synthesis Lab (IESL) at the University of Massachusetts, Amherst. In addition to research, I worked on developing and testing features for the OpenReview platform.

news

Oct 22, 2024 I will be presenting Analysis of Plan-based Retrieval for Grounded Text Generation at EMNLP 2024! See you in Miami! :sparkles:

selected publications

  1. Analysis of Plan-based Retrieval for Grounded Text Generation
    Ameya Godbole, Nicholas Monath, Seungyeon Kim, Ankit Singh Rawat, Andrew McCallum, and Manzil Zaheer
    In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, Nov 2024
  2. Benchmarking Long-tail Generalization with Likelihood Splits
    Ameya Godbole, and Robin Jia
    In Findings of the Association for Computational Linguistics: EACL 2023, May 2023
  3. Knowledge Base Question Answering by Case-based Reasoning over Subgraphs
    Rajarshi Das, Ameya Godbole, Ankita Naik, Elliot Tower, Manzil Zaheer, Hannaneh Hajishirzi, Robin Jia, and Andrew Mccallum
    In Proceedings of the 39th International Conference on Machine Learning, 17–23 jul 2022
  4. Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering
    Rajarshi Das, Ameya Godbole, Dilip Kavarthapu, Zhiyu Gong, Abhishek Singhal, Mo Yu, Xiaoxiao Guo, Tian Gao, Hamed Zamani, Manzil Zaheer, and 1 more author
    In Proceedings of the 2nd Workshop on Machine Reading for Question Answering, Nov 2019