Jason Liang

According to our database, Jason Liang authored at least 13 papers between 2014 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Opening the Black Box: A Survey on the Mechanisms of Multi-Step Reasoning in Large Language Models.

Liangming Pan, Jason Liang, Jiaran Ye, Minglai Yang, Xinyuan Lu, Fengbin Zhu

CoRR, January, 2026

DP-HLS: A High-Level Synthesis Framework for Accelerating Dynamic Programming Algorithms in Bioinformatics.

Anshu Gupta, Yingqi Cao, Jason Liang, Yatish Turakhia

Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2026

2025

Assessing AI Simplification of Medical Texts: Readability and Content Fidelity.

Bryce Picton, Saman Andalib, Aidin Spina, Brandon Camp, Sean S. Solomon, Jason Liang, Patrick M. Chen, Jefferson W. Chen, Frank P. Hsu, Michael Y. Oh

Int. J. Medical Informatics, 2025

CP-Bench: A PyTorch Test Suite to Detect AI Hardware Failure, Performance Degradation, and Silent Data Corruption.

Xun Jiao, Sunny Yang, Suman Gumudavelli, Shreya Varshini, Abhinav Pandey, Abhinav Jauhri, Francesco Caggioni, Gautham Vunnam, Harish Dattatraya Dixit, Jason Liang, Philip Henzler, Sameeksha Gupta, Tyler Graf, Venkat Ramesh, Fan Fred Lin

Proceedings of the IEEE International Test Conference, 2025

2024

Narrative Analysis of True Crime Podcasts With Knowledge Graph-Augmented Large Language Models.

Xinyi Leng, Jason Liang, Jack Mauro, Xu Wang, Andrea L. Bertozzi, James Chapman, Junyuan Lin, Bohan Chen, Chenchen Ye, Temple Daniel, P. Jeffrey Brantingham

CoRR, 2024

Automatic Data Labeling Using Large Language Models.

Adarsh Ramanathan, Jason Liang, Dan Sommerfield, Hossein Azari

Proceedings of the Smart Multimedia - 4th International Conference, 2024

PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation.

Jason Ansel, Edward Z. Yang, Horace He, Natalia Gimelshein, Animesh Jain, Michael Voznesensky, Bin Bao, Peter Bell, David Berard, Evgeni Burovski, Geeta Chauhan, Anjali Chourdia, Will Constable, Alban Desmaison, Zachary DeVito, Elias Ellison, Will Feng, Jiong Gong, Michael Gschwind, Brian Hirsh, Sherlock Huang, Kshiteej Kalambarkar, Laurent Kirsch, Michael Lazos, Mario Lezcano, Yanbo Liang, Jason Liang, Yinghai Lu, C. K. Luk, Bert Maher, Yunjie Pan, Christian Puhrsch, Matthias Reso, Mark Saroufim, Marcos Yukio Siraichi, Helen Suk, Shunting Zhang, Michael Suo, Phil Tillet, Xu Zhao, Eikan Wang, Keren Zhou, Richard Zou, Xiaodong Wang, Ajit Mathews, William Wen, Gregory Chanan, Peng Wu, Soumith Chintala

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

2022

Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark.

Hendrik Borras, Giuseppe Di Guglielmo, Javier M. Duarte, Nicolò Ghielmetti, Benjamin Hawks, Scott Hauck, Shih-Chieh Hsu, Ryan Kastner, Jason Liang, Andres Meza, Jules Muhizi, Tai Nguyen, Rushil Roy, Nhan Tran, Yaman Umuroglu, Olivia Weng, Aidan Yokuda, Michaela Blott

CoRR, 2022

2021

First-Generation Inference Accelerator Deployment at Facebook.

Michael J. Anderson, Benny Chen, Stephen Chen, Summer Deng, Jordan Fix, Michael Gschwind, Aravind Kalaiah, Changkyu Kim, Jaewon Lee, Jason Liang, Haixin Liu, Yinghai Lu, Jack Montgomery, Arun Moorthy, Nadathur Satish, Sam Naghshineh, Avinash Nayak, Jongsoo Park, Chris Petersen, Martin Schatz, Narayanan Sundaram, Bangsheng Tang, Peter Tang, Amy Yang, Jiecao Yu, Hector Yuen, Ying Zhang, Aravind Anbudurai, Vandana Balan, Harsha Bojja, Joe Boyd, Matthew Breitbach, Claudio Caldato, Anna Calvo, Garret Catron, Sneh Chandwani, Panos Christeas, Brad Cottel, Brian Coutinho, Arun Dalli, Abhishek Dhanotia, Oniel Duncan, Roman Dzhabarov, Simon Elmir, Chunli Fu, Wenyin Fu, Michael Fulthorp, Adi Gangidi, Nick Gibson, Sean Gordon, Beatriz Padilla Hernandez, Daniel Ho, Yu-Cheng Huang, Olof Johansson, Shishir Juluri, et al.

CoRR, 2021

Training Stacked Denoising Autoencoders for Representation Learning.

Jason Liang, Keith Kelly

CoRR, 2021

Designing Counterfactual Generators using Deep Model Inversion.

Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jason Liang, Akshay Chaudhari, Andreas Spanias

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2015

UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions.

Patrick MacAlpine, Josiah Hanna, Jason Liang, Peter Stone

Proceedings of the RoboCup 2015: Robot World Cup XIX [papers from the 19th Annual RoboCup International Symposium, 2015

2014

UT Austin Villa: RoboCup 2014 3D Simulation League Competition and Technical Challenge Champions.

Patrick MacAlpine, Mike Depinet, Jason Liang, Peter Stone

Proceedings of the RoboCup 2014: Robot World Cup XVIII [papers from the 18th Annual RoboCup International Symposium, 2014