I am a PhD student at ETH Zürich where I am advised by Prof. Mrinmaya Sachan and Prof. Thomas Hofmann
Before that, I spent two years as a Research Engineer at Microsoft Research Montréal where I worked with T.J. Hazen. Previously, I was a Master's student at UMass Amherst where I was advised by Prof. Andrew Mccallum.
I am interested in building reasoning systems that are explainable, trustable, and robust to distributional shifts. Broadly, I work on machine learning and study its application in various fields of natural language processing.

I am grateful to be a recipient of the IBM PhD fellowship 2021

Publications

Google Scholar

2023

• Towards Aligning Language Models with Textual Feedback
  Saüc Abadal Lloret*, Shehzaad Dhuliawala*, Keerthiram Murugesan, Mrinmaya Sachan
  EMNLP 2024
• Implicit Personalization in Language Models: A Systematic Study
  Zhijing Jin, Nils Heil, Jiarui Liu, Shehzaad Dhuliawala, Yahang Qi, Bernhard Schölkopf, Rada Mihalcea, Mrinmaya Sachan
  EMNLP 2024 Findings
• Chain-of-Verification Reduces Hallucinations in Large Language Models
  Shehzaad Dhuliawala, Mojtaba Komeili, Jing Xu, Roberta Raileanu, Xian Li, Asli Celikyilmaz, Jason Weston.
  ACL 2024 Findings
• A Diachronic Perspective on User Trust in AI under Uncertainty
  Shehzaad Dhuliawala*, Vilém Zouhar*, Mennatallah El-Assady, Mrinmaya Sachan.
  (EMNLP) 2023 (Oral)
• Variational Classification
  Shehzaad Dhuliawala, Mrinmaya Sachan, Carl Allen
  TMLR 2023

2022

• Calibration of Machine Reading systems at Scale
  Shehzaad Dhuliawala, Leonard Adolphs, Rajarshi Das, and Mrinmaya Sachan.
  ACL 2022 findings.
• Case-based Reasoning for Better Generalization in Text-Adventure Games
  Mattia Atzeni, Shehzaad Dhuliawala, Keerthiram Murugesan, and Mrinmaya Sachan.
  International Conference on Learning Representations (ICLR) 2022.

2021

• TopiOCQA: Open-domain Conversational Question Answering with Topic Switching
  Vaibhav Adlakha, Shehzaad Dhuliawala, Kaheer Suleman, Harm de Vries, and Siva Reddy
  TACL 2021
• How to Query Language Models?
  Leonard Adolphs, Shehzaad Dhuliawala, and Thomas Hofmann.
  Preprint 2021

2020

• A Simple Approach to Case-Based Reasoning in Knowledge Bases
  Rajarshi Das, Ameya Godbole, Shehzaad Dhuliawala, Manzil Zaheer, and Andrew McCallum.
  Automated Knowledge Base Construction (AKBC) 2020

2019

• Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering
  Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, and Andrew McCallum.
  International Conference on Learning Representations (ICLR) 2019.

2018

• Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning
  Shehzaad Dhuliawala*, Rajarshi Das*, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Alex Smola and Andrew McCallum.
  International Conference on Learning Representations (ICLR) 2018. Also Won Best Paper at the workshop on Automated Knowledge Base Construction (AKBC) at Neurips 2017. [code]