Average-Case Fine-Grained Hardness. - Marshall Ball; Alon Rosen; Manuel Sabin; Prashant Nalini Vasudevan (Electron. Colloquium Comput. Complex., 2017)

Proofs of Useful Work. - Marshall Ball; Alon Rosen; Manuel Sabin; Prashant Nalini Vasudevan (IACR Cryptol. ePrint Arch., 2017)

XOR Codes and Sparse Random Linear Equations with Noise. - Andrej Bogdanov; Manuel Sabin; Prashant Nalini Vasudevan (Electron. Colloquium Comput. Complex., 2018)

Fine-Grained Derandomization: From Problem-Centric to Resource-Centric Complexity. - Marco Carmosino; Russell Impagliazzo; Manuel Sabin (Electron. Colloquium Comput. Complex., 2018)

Proofs of Work from Worst-Case Assumptions. - Marshall Ball; Alon Rosen; Manuel Sabin; Prashant Nalini Vasudevan (IACR Cryptol. ePrint Arch., 2018)

XOR Codes and Sparse Learning Parity with Noise. - Andrej Bogdanov; Manuel Sabin; Prashant Nalini Vasudevan (SODA, 2019)

Manifesting the sociotechnical: experimenting with methods for social context and social justice. - Ezra Goss; Lily Hu; Manuel Sabin; Stephanie Teeple (FAT*, 2020)

On The Utility of Fine-Grained Complexity Theory - Manuel Sabin (2020)

Learning with distributional inverters. - Eric Binnendyk; Marco Carmosino; Antonina Kolokolova; Ramyaa Ramyaa; Manuel Sabin (CoRR, 2021)

Learning with Distributional Inverters. - Eric Binnendyk; Marco Carmosino; Antonina Kolokolova; R. Ramyaa; Manuel Sabin (ALT, 2022)