I am Rachit, a PhD student at Harvard University. I am super fortunate to be advised by Prof. David Alvarez-Melis and Prof. Martin Wattenberg. Broadly, I am interested in making language models more useful and controllable. I am also interested in understanding and analysis.
Over the past few years, I walked my first baby steps as a researcher owing to some wonderful people and collaborations. Most recently, I was a pre-doctoral researcher at Google DeepMind, working on modularizing LLMs with Partha and Prateek. Before that, I pursued my bachelor’s thesis research with Yonatan at the Technion in Israel. There I had a great time studying how intrinsic properties of a neural network are informative of generalization behaviours. Before that, I was a research intern at Adobe’s Media and Data Science Research Lab, where I worked on commonsense reasoning for large language models.
I was fortunate to collaborate with Danish for more than two years to evaluate explanation methods in NLP1. I also had an amazing time working with Naomi studying mode connectivity in loss surfaces of language models2.
I also spent a couple of wonderful summers as a part of the Google Summer of Code program with the Cuneiform Digital Library Initiative (CDLI). Here, I was advised by Jacob and Niko.
News and Timeline
2024
- August Starting my doctorate at Harvard University!
- May Presenting our work on composing large language models at ICLR 2024 in Vienna!
2023
- May Presenting our work on linear mode connectivity at ICLR 2023 in Kigali!
2022
- September My bachelor’s thesis work done at the Technion was accepted at NeurIPS 2022!
- August Joining Google Research India as a pre-doctoral researcher.
- June Releasing the pre-print for our work on analyzing linear mode connectivity and out-of-distribution behaviour. Led by Jeevesh and mentored by Naomi.
- May Two papers on commonsense and factual reasoning done at Adobe MDSR accepted at NAACL 2022!
- January Starting my bachelor’s thesis with Yonatan at the Technion, Israel!
2021
- November After a year-long review and revision process, our work evaluating model explanations has been accepted at TACL. In collaboration with Danish.
- July Attending the 11th Lisbon Machine Learning Summer School (LXMLS 2021).
- May Work with CDLI accepted at ACL SRW 2021. Gauging machine translation and sequence labeling for extremely low-resource languages.
- May Starting as a Research Intern at Adobe’s Media and Data Science Research (MDSR).
2020
- November Started collaborating with Danish (LTI, CMU) on evaluating neural explanations for NLP.
- June Contributing to the Cuneiform Digital Library Initiative (CDLI) as a part of GSoC!
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Started with a meek awe-inspired email ↩