I'm a final year CS PhD candidate working on Deep Learning and NLP. My advisor is Prof. Chris Manning.

My research focuses on building LLMs that can generalize out-of-distribution, either through structured inductive biases, or by interacting with their environments.

These days, I'm working on robust LLM assistants that can translate user instructions to action sequences on digital environments like web browsers.

News

Feb. 2025

Talk circuit

Talking about Building the learning-from-interaction pipeline for LLMs at Together AI, MIT, Harvard, and Brown.

Dec. 2024

System-2 Generalization at Scale

We organized a workshop at NeurIPS 2024 on 'System-2 Generalization at Scale' with talks from Josh Tenenbaum, Melanie Mitchell, and others.

Nov. 2024

Session on Intelligent Agents

Invited to lead a session on 'Intelligent Agents' at Foundation Capital AI Unconference, 2024 in San Francisco

March 2024

Invited Talks

Talks in NYC (NYU / Columbia / Cornell) on 'Improving the Structure and Interpretation of Language in Modern Sequence Models'

Representative Works

Please check out my Google Scholar for all papers.

Pre-print 2025

NNetNav: Unsupervised Learning of Browser Agents Through Environment Interaction in the Wild

Shikhar Murty, Hao Zhu, Dzmitry Bahdanau, Christopher D. Manning

An unsupervised approach for training LLM web-agents, through open-ended exploration of live websites

ICML 2024

Bootstrapping Agents by Guiding Exploration with Language

Shikhar Murty, Christopher D. Manning, Peter Shaw, Mandar Joshi, Kenton Lee

A back-translation inspired method to automatically induce synthetic demonstrations for an LLM agent for browser control and multi-step tool use.

EMNLP 2023

Pushdown layers: Encoding Recursive structure in transformer language models

Shikhar Murty, Pratyusha Sharma, Jacob Andreas, Christopher D. Manning

A stack-augmented self-attention layer that can be trained in parallel, that helps transformers generalize better on tasks that require recursive reasoning.

ACL 2023

Grokking of Hierarchical Structure in Vanilla Transformers

Shikhar Murty, Pratyusha Sharma, Jacob Andreas, Christopher D. Manning

We discover a new kind of grokking behavior where stanford transformers sometimes learn the underlying hierarchical structure of natural language.

ICLR 2023

Characterizing Intrinsic Compositionality in Transformers with Tree Projections

Shikhar Murty, Pratyusha Sharma, Jacob Andreas, Christopher D. Manning

We propose a method to functionally approximate transformers with tree-structures, and find correlation between generalization and emergent tree-structuredness.

EMNLP 2022

Fixing Model Bugs with Natural Language Patches

Shikhar Murty, Christopher D. Manning, Scott M. Lundberg, and Marco Tulio Ribeiro

Experience

Oct 2024 to Dec 2024

Part-time visitor ServiceNow Research

Advisor: Alexandre Lacoste, Dzmitry Bahdanau

Post-training for LLM browser agents

June 2023 to Feb 2024

Research Intern DeepMind

Advisor: Mandar Joshi, Kenton Lee, Pete Shaw

Unsupervised browser control with LLMs

Summer 2022

Research Intern Microsoft Research

Advisor: Marco Tulio Ribiero, Scott Lundberg

Fixing model bugs with language feedback

Education

2019—Present

Stanford University

Ph.D. in Computer Science

Advisor: Prof. Christopher D. Manning

2013—2017

Indian Institute of Technology, New Delhi

B.Tech in Electrical Engineering

Thesis: Inference over Knowledge Bases with Deep Learning