23) "CodeAlchemy: Synthetic Code Rewriting at Scale"

    Ankit Gupta, Aditya Prasad, Rameswar Panda

• arXiv preprint, 2026.

22) "Exploring the limits of decoder-only models trained on public speech recognition corpora"

    Ankit Gupta, George Saon, Brian Kingsbury

• Annual Conference of the International Speech Communication Association (INTERSPEECH), 2024.

21) "Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors"

    Ido Amos, Jonathan Berant, Ankit Gupta

• International Conference on Learning Representations (ICLR), 2024.  (outstanding paper award)

• Sister Conferences Best Papers track @ IJCAI 2025.  (extended abstract)

20) "Simplifying and Understanding State Space Models with Diagonal Linear RNNs"

    Ankit Gupta, Harsh Mehta, Jonathan Berant

• arXiv preprint, 2022.

19) "Diagonal State Space Augmented Transformers for Speech Recognition" 

    George Saon, Ankit Gupta, Xiaodong Cui

• IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023.

18) "Analyzing Transformers in Embedding Space"

    Guy Dar, Mor Geva, Ankit Gupta, Jonathan Berant

• Annual Conference of the Association for Computational Linguistics (ACL), 2023.

• BlackboxNLP @ EMNLP 2022. (non-archival version)

17) "Long Range Language Modeling via Gated State Spaces"

    Harsh Mehta, Ankit Gupta, Ashok Cutkosky, Behnam Neyshabur

• International Conference on Learning Representations (ICLR), 2023.

16) "On the Parameterization and Initialization of Diagonal State Space Models"

    Albert Gu, Ankit Gupta, Karan Goel, Christopher Ré

• Advances in Neural Information Processing Systems (NeurIPS), 2022.

15) "Diagonal State Spaces are as Effective as Structured State Spaces"

    Ankit Gupta, Albert Gu, Jonathan Berant

• Advances in Neural Information Processing Systems (NeurIPS), 2022.  (spotlight talk)

14) "SCROLLS: Standardized CompaRison Over Long Language Sequences"

    Uri Shaham, Elad Segal, Maor Ivgi, Avia Efrat, Ori Yoran, Adi Haviv, Ankit Gupta, Wenhan Xiong, Mor Geva, Jonathan Berant, Omer Levy

• Empirical Methods in Natural Language Processing (EMNLP), 2022.

13) "Memory-efficient Transformers via Top-k Attention"

    Ankit Gupta, Guy Dar, Shaya Goodman, David Ciprut, Jonathan Berant

• Workshop on Simple and Efficient Natural Language Processing (SustaiNLP) @ EMNLP 2021.

12) "Value-aware Approximate Attention"

    Ankit Gupta, Jonathan Berant

• Empirical Methods in Natural Language Processing (EMNLP), 2021  (oral presentation)

11) "GMAT: Global Memory Augmentation for Transformers"

    Ankit Gupta, Jonathan Berant

• arXiv preprint, 2020.

• ISCOL 2020 poster

10) "Injecting Numerical Reasoning Skills into Language Models"

    Mor Geva*, Ankit Gupta* and Jonathan Berant

• Annual Conference of the Association for Computational Linguistics (ACL), 2020.

9) "Break It Down: A Question Understanding Benchmark"

    Tomer Wolfson, Mor Geva, Ankit Gupta, Matt Gardner, Yoav Goldberg, Daniel Deutch and Jonathan Berant

• Transactions of the Association for Computational Linguistics (TACL), 2020.

8) "Unexpected Power of Low-Depth Arithmetic Circuits"

    Ankit Gupta, Pritish Kamath, Neeraj Kayal and Ramprasad Saptharishi

• Communications of the ACM, 60(6): 93-100 (2017).

7) "Arithmetic Circuits: Lower Bounds, Derandomization and Reconstruction"

    Ankit Gupta

• PhD Thesis. Chennai Mathematical Institute, 2015.

6) "Algebraic Geometric Techniques for Depth-4 PIT & Sylvester-Gallai Conjectures for Varieties"

    Ankit Gupta

• ECCC, 2014.

5) "Arithmetic circuits: A chasm at depth three"

    Ankit Gupta, Pritish Kamath, Neeraj Kayal and Ramprasad Saptharishi

• IEEE Symposium on Foundations of Computer Science (FOCS) 2013, pp. 578-587.

• SIAM Journal on Computing, 45(3): 1064-1079 (2016) (special issue for FOCS)

• invited to Communications of the ACM, Research Highlights.

4) "Approaching the chasm at depth four"

    Ankit Gupta, Pritish Kamath, Neeraj Kayal and Ramprasad Saptharishi

• IEEE Conference on Computational Complexity (CCC) 2013, pp. 65-73.

• Journal of the ACM, 61(6): 33:1-33:16 (2014)

• best paper award at CCC 2013.

3) "Random Arithmetic Formulas can be Reconstructed Efficiently"

    Ankit Gupta, Neeraj Kayal and Youming Qiao

• IEEE Conference on Computational Complexity (CCC) 2013, pp. 1-9.

• Computational Complexity 23(2): 207-303 (2014) (special issue for CCC 2013) 

2) "Reconstruction of Depth-4 Multilinear Circuits with Top Fan-in 2"

    Ankit Gupta, Neeraj Kayal and Satya Lokam

• ACM Symposium on Theory of Computing (STOC) 2012, pp. 625-642.

1) "Efficient Reconstruction of Random Multilinear Formulas"

    Ankit Gupta, Neeraj Kayal and Satya Lokam

• IEEE Symposium on Foundations of Computer Science (FOCS) 2011, pp. 778-787.