Kanishka Misra

Kanishka Misra

PhD Candidate

AKRaNLU Lab

Purdue University

I am a PhD candidate at Purdue University, where I work on Natural Language Understanding with Dr. Julia Taylor Rayz at the AKRaNLU Lab. I also work closely with Dr. Allyson Ettinger and her lab at UChicago. I am currently on the job market for post-doctoral position! Please reach out if you think I am a good fit for your lab!

My research focuses on evaluating and analyzing large language models from the perspective of human semantic cognition, investigating capacities such as their ability to encode typicality effects, recall property knowledge, demonstrate property inheritance, and perform human-like category-based induction. Through my work, I hope to contribute towards bridging the experimental paradigms in the study of human cognition with that of artificial intelligence systems.

I am currently a Research Intern at Google AI working on multi-hop reasoning and language models!

I was recently selected to be a Graduate Student Fellow in the inaugural Purdue Graduate School Mentoring Fellows program!

I am the author of minicons, a python package that facilitates large scale behavioral analyses of transformer language models.

I recently hosted a two part discussion group on Neural Nets for Cognition @ CogSci 2022!

My email is kmisra @ purdue [dot] edu.[why is it like that?]

Interests

  • Inductive Reasoning
  • Concepts and Categories
  • Language Understanding
  • Lexical Semantics
  • Typicality and Vagueness

Collaborators

  • Julia Rayz, Purdue (Advisor)
  • Allyson Ettinger, UChicago
  • Najoung Kim, NYU/Google
  • Adina Williams, Meta AI
  • Koustuv Sinha, Meta AI

Recent News

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Recent Publications

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A Property Induction Framework for Neural Language Models

Investigating how neural language generalize novel information about everyday concepts and their properties. To be presented at CogSci 2022

minicons: Enabling Flexible Behavioral and Representational Analyses of Transformer Language Models

A python library that facilitates behavioral and representational analyses of transformer Language Models.

On Semantic Cognition, Inductive Generalization, and Language Models

Thesis proposal to study Inductive Generalization in Language Models.

Do language models learn typicality judgments from text?

Investigating manifestation of category typicality effects in predictive models of language processing. Presented at CogSci 2021

Recent Posts

Introducing $\texttt{minicons}$: Running large scale behavioral analyses on transformer language models

In this post, I showcase my new python library that implements simple computations to facilitate large-scale evaluation of transformer language models.

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