Kumar Shridhar. Ping me
I will be at NeurIPS in San Diego. Our latest work on LLM Fusion paper got accepted at EMNLP 2025.

ML Researcher — San Francisco

Hi! I am
Shridhar

I am a Machine Learning researcher building language models that can deconstruct reasoning problems, improvise, and critique themselves. Currently designing an effective LLM routing system at Ema.

ETH Zürich Meta FAIR Microsoft Research
Kumar standing on a snowy mountain range

Glacier 3000 • Switzerland

Work

Selected Research

ACL 2023 Distillation

Distilling Reasoning into Smaller Models

Distill a large model's reasoning into small cooperating models that can learn to solve complex reasoning tasks nearly as well as much larger LMs but with far fewer parameters.

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ACL 2025 Distillation

SIKeD: Self-guided Iterative Knowledge Distillation

Self guided distillation where a student decides when to explore new learning with teacher and when to exploit and solidify what it knows.

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NAACL 2024 Refinement

The ART of LLM Refinement: ASK, REFINE, TRUST

A refinement paradigm where an asker asks questions to decided when an LLM should refine its outputs and a truster decides whether to trust the refined answer.

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EMNLP 2022 Decomposition

Socratic Subquestions for Teaching Math Word Problems

Socratic style decomposition to guide language models to break complex problems into simpler ones and then solve it iteratively.

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EMNLP 2025 Routing

LLM Fusion

Taxonomy guided Routing for LLMs.

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AAAI 2025 Calibration

LLM Calibration

Gauging the confidence of LLMs.

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NeurIPS 2022 Generative

Variational AutoEncoders

Adversarial approach to train VAEs.

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Contact

Let's
Connect

Thoughtful emails, spicy prototypes, student collabs, event invites—send them all. I answer fastest when you include context and write yourself.

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