Arindam Mitra
Arindam Mitra studies how language models learn to reason and follow instructions. His early papers address logic puzzles and numerical reasoning, and he earned a computer-science doctorate at Arizona State University in 2019. At Microsoft Research, he led the Orca project and coauthored work on Orca 2 and AgentInstruct. His later work included Orca-Math for grade-school mathematics and Explorer, a multimodal web agent trained with synthesized web trajectories. As of October 2026, he is at Meta.
- Now at
- Meta
Timeline
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2015
A logic-grid puzzle paper
The village Oodlabari is his home, and he coauthors an EMNLP paper on solving logic-grid puzzles in 2015.
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2019
A doctorate in reading comprehension
His computer-science doctorate at Arizona State University, completed in 2019, examines knowledge representation, reasoning, and non-extractive reading comprehension.
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2022
The NumGLUE benchmark
He coauthors NumGLUE, an eight-task benchmark for arithmetic reasoning, in 2022.
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June 2023–November 2023
Orca and Orca 2
In 2023, he coauthors Orca, a 13-billion-parameter model that learns from GPT-4 explanation traces. He also coauthors Orca 2, which uses tailored synthetic data to teach smaller models varied reasoning techniques.
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February 2024
Math with Orca-Math
In February 2024, he coauthors Orca-Math, a 7-billion-parameter model based on Mistral-7B for grade-school mathematics.
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July 2024–November 2024
Building AgentInstruct
At Microsoft Research, he leads the Orca project and coauthors AgentInstruct in 2024. The framework uses agentic flows to create prompts and responses from raw documents for language-model post-training.
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February 2025
The Explorer web agent
In February 2025, he coauthors Explorer, which creates over 94,000 multimodal web trajectories and uses them to train a web agent.
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As of October 2026
At Meta
As of October 2026, he is at Meta.
Sources and credits
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- Arindam Mitra
- Learning to Automatically Solve Logic Grid Puzzles - ACL Anthology
- Cognition and Intelligence Lab @ASU
- NumGLUE: A Suite of Fundamental yet Challenging Mathematical Reasoning Tasks - ACL Anthology
- [2306.02707] Orca: Progressive Learning from Complex Explanation Traces of GPT-4
- Orca 2: Teaching Small Language Models How to Reason - Microsoft Research
- [2402.14830] Orca-Math: Unlocking the potential of SLMs in Grade School Math
- Abstracts: July 18, 2024 - Microsoft Research
- Orca-AgentInstruct: Agentic flows can be effective synthetic-data generators - Microsoft Research
- [2502.11357] Explorer: Scaling Exploration-driven Web Trajectory Synthesis for Multimodal Web Agents