Efficient Reconstruction of Random Multilinear Formulas. - Ankit Gupta 001; Neeraj Kayal; Satyanarayana V. Lokam (FOCS, 2011)

Reconstruction of Depth-4 Multilinear Circuits with Top fanin 2. - Ankit Gupta 001; Neeraj Kayal; Satyanarayana V. Lokam (Electron. Colloquium Comput. Complex., 2011)

Reconstruction of depth-4 multilinear circuits with top fan-in 2. - Ankit Gupta 001; Neeraj Kayal; Satyanarayana V. Lokam (STOC, 2012)

An exponential lower bound for homogeneous depth four arithmetic circuits with bounded bottom fanin. - Ankit Gupta 001; Pritish Kamath; Neeraj Kayal; Ramprasad Saptharishi (Electron. Colloquium Comput. Complex., 2012)

Arithmetic circuits: A chasm at depth three. - Ankit Gupta 001; Pritish Kamath; Neeraj Kayal; Ramprasad Saptharishi (Electron. Colloquium Comput. Complex., 2013)

Random arithmetic formulas can be reconstructed efficiently. - Ankit Gupta 001; Neeraj Kayal; Youming Qiao (Comput. Complex., 2014)

Algebraic Geometric Techniques for Depth-4 PIT & Sylvester-Gallai Conjectures for Varieties. - Ankit Gupta 001 (Electron. Colloquium Comput. Complex., 2014)

Approaching the Chasm at Depth Four. - Ankit Gupta 001; Pritish Kamath; Neeraj Kayal; Ramprasad Saptharishi (J. ACM, 2014)

Arithmetic Circuits: A Chasm at Depth 3. - Ankit Gupta 001; Pritish Kamath; Neeraj Kayal; Ramprasad Saptharishi (SIAM J. Comput., 2016)

Unexpected power of low-depth arithmetic circuits. - Ankit Gupta 001; Pritish Kamath; Neeraj Kayal; Ramprasad Saptharishi (Commun. ACM, 2017)

Injecting Numerical Reasoning Skills into Language Models. - Mor Geva; Ankit Gupta 001; Jonathan Berant (ACL, 2020)

GMAT: Global Memory Augmentation for Transformers. - Ankit Gupta 001; Jonathan Berant (CoRR, 2020)

Break It Down: A Question Understanding Benchmark. - Tomer Wolfson; Mor Geva; Ankit Gupta 001; Yoav Goldberg; Matt Gardner 001; Daniel Deutch; Jonathan Berant (Trans. Assoc. Comput. Linguistics, 2020)

Value-aware Approximate Attention. - Ankit Gupta 001; Jonathan Berant (EMNLP (1), 2021)

Memory-efficient Transformers via Top-k Attention. - Ankit Gupta 001; Guy Dar; Shaya Goodman; David Ciprut; Jonathan Berant (SustaiNLP@EMNLP, 2021)

SCROLLS: Standardized CompaRison Over Long Language Sequences. - Uri Shaham 002; Elad Segal; Maor Ivgi; Avia Efrat; Ori Yoran; Adi Haviv; Ankit Gupta 001; Wenhan Xiong; Mor Geva; Jonathan Berant; Omer Levy (EMNLP, 2022)

Diagonal State Spaces are as Effective as Structured State Spaces. - Ankit Gupta 001; Albert Gu; Jonathan Berant (NeurIPS, 2022)

On the Parameterization and Initialization of Diagonal State Space Models. - Albert Gu; Karan Goel; Ankit Gupta 001; Christopher Ré (NeurIPS, 2022)

Diagonal State Spaces are as Effective as Structured State Spaces. - Ankit Gupta 001 (CoRR, 2022)

Simplifying and Understanding State Space Models with Diagonal Linear RNNs. - Ankit Gupta 001; Harsh Mehta; Jonathan Berant (CoRR, 2022)

Analyzing Transformers in Embedding Space. - Guy Dar; Mor Geva; Ankit Gupta 001; Jonathan Berant (ACL (1), 2023)

Diagonal State Space Augmented Transformers for Speech Recognition. - George Saon; Ankit Gupta 001; Xiaodong Cui (ICASSP, 2023)

Long Range Language Modeling via Gated State Spaces. - Harsh Mehta; Ankit Gupta 001; Ashok Cutkosky; Behnam Neyshabur (ICLR, 2023)

Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors. - Ido Amos; Jonathan Berant; Ankit Gupta 001 (ICLR, 2024)

Exploring the limits of decoder-only models trained on public speech recognition corpora. - Ankit Gupta 001; George Saon; Brian Kingsbury (INTERSPEECH, 2024)