Ankit Garg

Senior Researcher

Publications

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- EigenLI: Spectral Approximations to Late Interaction
  
  S. Archish, Sabyasachi Basu, Ankit Garg, Ravishankar Krishnaswamy, Kirankumar Shiragur
  
  September 2026
  
  arXiv | September 2026
  
  Publication
- Retrieval Needs Multivectors: An Exponential Separation
  
  Mihir Agarwal, Viraj Agrawal, Sabyasachi Basu, Ankit Garg, Kirankumar Shiragur
  
  August 2026
  
  arXiv | August 2026
  
  Publication
- Incorporating Token Importance in Multi-Vector Retrieval
  
  S. Archish, Ankit Garg, Kirankumar Shiragur, Neeraj Kayal
  
  November 2025
  
  arXiv | November 2025
  
  Publication
- Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning
  
  Pritam Chandra, Ankit Garg, Neeraj Kayal, Kunal Mittal, Tanmay Sinha
  
  Electronic Colloquium on Computational Complexity, 2023 | November 2023
  
  DOI Publication
- Low-depth arithmetic circuit lower bounds via shifted partials
  
  Prashanth Amireddy, Ankit Garg, Neeraj Kayal, Chandan Saha, Bhargav Thankey
  
  Electronic Colloquium on Computational Complexity, 2022 | November 2022
  
  DOI Publication
- Learning sums of powers of low-degree polynomials in the non-degenerate case
  
  Ankit Garg, Neeraj Kayal, Chandan Saha
  
  2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS) | April 2020, pp. 889-899
  
  DOI Publication Publication Publication

- EigenLI: Spectral Approximations to Late Interaction
  
  S. Archish, Sabyasachi Basu, Ankit Garg, Ravishankar Krishnaswamy, Kirankumar Shiragur
  
  September 2026
  
  arXiv | September 2026
  
  Publication
- Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning
  
  Pritam Chandra, Ankit Garg, Neeraj Kayal, Kunal Mittal, Tanmay Sinha
  
  Electronic Colloquium on Computational Complexity, 2023 | November 2023
  
  DOI Publication
- EigenLI: Spectral Approximations to Late Interaction
  
  S. Archish, Sabyasachi Basu, Ankit Garg, Ravishankar Krishnaswamy, Kirankumar Shiragur
  
  September 2026
  
  arXiv | September 2026
  
  Publication
- Retrieval Needs Multivectors: An Exponential Separation
  
  Mihir Agarwal, Viraj Agrawal, Sabyasachi Basu, Ankit Garg, Kirankumar Shiragur
  
  August 2026
  
  arXiv | August 2026
  
  Publication
- Incorporating Token Importance in Multi-Vector Retrieval
  
  S. Archish, Ankit Garg, Kirankumar Shiragur, Neeraj Kayal
  
  November 2025
  
  arXiv | November 2025
  
  Publication
- Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning
  
  Pritam Chandra, Ankit Garg, Neeraj Kayal, Kunal Mittal, Tanmay Sinha
  
  Electronic Colloquium on Computational Complexity, 2023 | November 2023
  
  DOI Publication
- Low-depth arithmetic circuit lower bounds via shifted partials
  
  Prashanth Amireddy, Ankit Garg, Neeraj Kayal, Chandan Saha, Bhargav Thankey
  
  Electronic Colloquium on Computational Complexity, 2022 | November 2022
  
  DOI Publication
- Learning sums of powers of low-degree polynomials in the non-degenerate case
  
  Ankit Garg, Neeraj Kayal, Chandan Saha
  
  2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS) | April 2020, pp. 889-899
  
  DOI Publication Publication Publication
- Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning
  
  Pritam Chandra, Ankit Garg, Neeraj Kayal, Kunal Mittal, Tanmay Sinha
  
  Electronic Colloquium on Computational Complexity, 2023 | November 2023
  
  DOI Publication
- Learning sums of powers of low-degree polynomials in the non-degenerate case
  
  Ankit Garg, Neeraj Kayal, Chandan Saha
  
  2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS) | April 2020, pp. 889-899
  
  DOI Publication Publication Publication

- EigenLI: Spectral Approximations to Late Interaction
  
  S. Archish, Sabyasachi Basu, Ankit Garg, Ravishankar Krishnaswamy, Kirankumar Shiragur
  
  September 2026
  
  arXiv | September 2026
  
  Publication
- Retrieval Needs Multivectors: An Exponential Separation
  
  Mihir Agarwal, Viraj Agrawal, Sabyasachi Basu, Ankit Garg, Kirankumar Shiragur
  
  August 2026
  
  arXiv | August 2026
  
  Publication
- Incorporating Token Importance in Multi-Vector Retrieval
  
  S. Archish, Ankit Garg, Kirankumar Shiragur, Neeraj Kayal
  
  November 2025
  
  arXiv | November 2025
  
  Publication
- Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning
  
  Pritam Chandra, Ankit Garg, Neeraj Kayal, Kunal Mittal, Tanmay Sinha
  
  Electronic Colloquium on Computational Complexity, 2023 | November 2023
  
  DOI Publication
- Low-depth arithmetic circuit lower bounds via shifted partials
  
  Prashanth Amireddy, Ankit Garg, Neeraj Kayal, Chandan Saha, Bhargav Thankey
  
  Electronic Colloquium on Computational Complexity, 2022 | November 2022
  
  DOI Publication
- Learning sums of powers of low-degree polynomials in the non-degenerate case
  
  Ankit Garg, Neeraj Kayal, Chandan Saha
  
  2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS) | April 2020, pp. 889-899
  
  DOI Publication Publication Publication

Ankit Garg

Publications

EigenLI: Spectral Approximations to Late Interaction

Retrieval Needs Multivectors: An Exponential Separation

Incorporating Token Importance in Multi-Vector Retrieval

Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning

Low-depth arithmetic circuit lower bounds via shifted partials

Learning sums of powers of low-degree polynomials in the non-degenerate case

EigenLI: Spectral Approximations to Late Interaction

Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning

EigenLI: Spectral Approximations to Late Interaction

Retrieval Needs Multivectors: An Exponential Separation

Incorporating Token Importance in Multi-Vector Retrieval

Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning

Low-depth arithmetic circuit lower bounds via shifted partials

Learning sums of powers of low-degree polynomials in the non-degenerate case

Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning

Learning sums of powers of low-degree polynomials in the non-degenerate case

EigenLI: Spectral Approximations to Late Interaction

Retrieval Needs Multivectors: An Exponential Separation

Incorporating Token Importance in Multi-Vector Retrieval

Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning

Low-depth arithmetic circuit lower bounds via shifted partials

Learning sums of powers of low-degree polynomials in the non-degenerate case

Contact Ankit Garg

Microsoft Research India