James Diffenderfer

44 papers A* 9A 3B 1Journal 30Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
BOOM: Benchmarking Out-Of-distribution Molecular Property Predictions of Machine Learning Models.
CoRR
Evan R. Antoniuk, Shehtab Zaman, Tal Ben-Nun, Peggy Li, James Diffenderfer, Busra Demirci, Obadiah Smolenski, Tim Hsu, Anna M. Hiszpanski, Kenneth Chiu, Bhavya Kailkhura, Brian Van Essen
2025 J jnl
Deep learning of PDE correction and mesh adaption without automatic differentiation.
Mach. Learn.
Shaocong Ma, James Diffenderfer, Bhavya Kailkhura, Yi Zhou
2025 J jnl
Forecasting Fails: Unveiling Evasion Attacks in Weather Prediction Models.
CoRR
Huzaifa Arif, Pin-Yu Chen, Alex Gittens, James Diffenderfer, Bhavya Kailkhura
2025 J jnl
LLM Unlearning Reveals a Stronger-Than-Expected Coreset Effect in Current Benchmarks.
CoRR
Soumyadeep Pal, Changsheng Wang, James Diffenderfer, Bhavya Kailkhura, Sijia Liu
2025 J jnl
Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training.
CoRR
Brian R. Bartoldson, Siddarth Venkatraman, James Diffenderfer, Moksh Jain, Tal Ben-Nun, Seanie Lee, Minsu Kim, Johan S. Obando-Ceron, Yoshua Bengio, Bhavya Kailkhura
2025 J jnl
TruthPrInt: Mitigating LVLM Object Hallucination Via Latent Truthful-Guided Pre-Intervention.
CoRR
Jinhao Duan, Fei Kong, Hao Cheng, James Diffenderfer, Bhavya Kailkhura, Lichao Sun, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu
2025 J jnl
UProp: Investigating the Uncertainty Propagation of LLMs in Multi-Step Agentic Decision-Making.
CoRR
Jinhao Duan, James Diffenderfer, Sandeep Madireddy, Tianlong Chen, Bhavya Kailkhura, Kaidi Xu
2025 J jnl
When SNN meets ANN: Error-Free ANN-to-SNN Conversion for Extreme Edge Efficiency.
Trans. Mach. Learn. Res.
Gourav Datta, Zeyu Liu, James Diffenderfer, Bhavya Kailkhura, Peter Anthony Beerel
2025 J jnl
ZFP: A compressed array representation for numerical computations.
Int. J. High Perform. Comput. Appl.
Peter Lindstrom, Jeffrey Hittinger, James Diffenderfer, Alyson Fox, Daniel Osei-Kuffuor, Jeffrey W. Banks
2024 A* conf
Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies.
ICML
Brian R. Bartoldson, James Diffenderfer, Konstantinos Parasyris, Bhavya Kailkhura
2024 J jnl
Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies.
CoRR
Brian R. Bartoldson, James Diffenderfer, Konstantinos Parasyris, Bhavya Kailkhura
2024 A* conf
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression.
ICML
Junyuan Hong, Jinhao Duan, Chenhui Zhang, Zhangheng Li, Chulin Xie, Kelsey Lieberman, James Diffenderfer, Brian R. Bartoldson, Ajay Kumar Jaiswal, Kaidi Xu, Bhavya Kailkhura, Dan Hendrycks, Dawn Song, Zhangyang Wang, Bo Li
2024 J jnl
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression.
CoRR
Junyuan Hong, Jinhao Duan, Chenhui Zhang, Zhangheng Li, Chulin Xie, Kelsey Lieberman, James Diffenderfer, Brian R. Bartoldson, Ajay Jaiswal, Kaidi Xu, Bhavya Kailkhura, Dan Hendrycks, Dawn Song, Zhangyang Wang, Bo Li
2024 A* conf
DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training.
ICLR
Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Konstantinos Parasyris, Jiancheng Liu, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
2024 J jnl
End-to-End Mesh Optimization of a Hybrid Deep Learning Black-Box PDE Solver.
CoRR
Shaocong Ma, James Diffenderfer, Bhavya Kailkhura, Yi Zhou
2024 A* conf
GTBench: Uncovering the Strategic Reasoning Capabilities of LLMs via Game-Theoretic Evaluations.
NeurIPS
Jinhao Duan, Renming Zhang, James Diffenderfer, Bhavya Kailkhura, Lichao Sun, Elias Stengel-Eskin, Mohit Bansal, Tianlong Chen, Kaidi Xu
2024 J jnl
GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations.
CoRR
Jinhao Duan, Renming Zhang, James Diffenderfer, Bhavya Kailkhura, Lichao Sun, Elias Stengel-Eskin, Mohit Bansal, Tianlong Chen, Kaidi Xu
2024 — conf
ReTA: Recursively Thinking Ahead to Improve the Strategic Reasoning of Large Language Models.
NAACL-HLT
Jinhao Duan, Shiqi Wang, James Diffenderfer, Lichao Sun, Tianlong Chen, Bhavya Kailkhura, Kaidi Xu
2024 A* conf
SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning.
EMNLP
Jinghan Jia, Yihua Zhang, Yimeng Zhang, Jiancheng Liu, Bharat Runwal, James Diffenderfer, Bhavya Kailkhura, Sijia Liu
2024 J jnl
SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning.
CoRR
Jinghan Jia, Yihua Zhang, Yimeng Zhang, Jiancheng Liu, Bharat Runwal, James Diffenderfer, Bhavya Kailkhura, Sijia Liu
2023 J jnl
Approximate High-Performance Computing: A Fast and Energy-Efficient Computing Paradigm in the Post-Moore Era.
IT Prof.
Harshitha Menon, James Diffenderfer, Giorgis Georgakoudis, Ignacio Laguna, Michael O. Lam, Daniel Osei-Kuffuor, Konstantinos Parasyris, Jackson Vanover
2023 J jnl
DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training.
CoRR
Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
2023 A* conf
Neural Image Compression: Generalization, Robustness, and Spectral Biases.
NeurIPS
Kelsey Lieberman, James Diffenderfer, Charles Godfrey, Bhavya Kailkhura
2023 J jnl
Neural Image Compression: Generalization, Robustness, and Spectral Biases.
CoRR
Kelsey Lieberman, James Diffenderfer, Charles Godfrey, Bhavya Kailkhura
2023 J jnl
When Bio-Inspired Computing meets Deep Learning: Low-Latency, Accurate, & Energy-Efficient Spiking Neural Networks from Artificial Neural Networks.
CoRR
Gourav Datta, Zeyu Liu, James Diffenderfer, Bhavya Kailkhura, Peter A. Beerel
2022 J jnl
A Framework for Error-Bounded Approximate Computing, with an Application to Dot Products.
SIAM J. Sci. Comput.
James Diffenderfer, Daniel Osei-Kuffuor, Harshitha Menon
2022 A conf
Approximate Computing Through the Lens of Uncertainty Quantification.
SC
Konstantinos Parasyris, James Diffenderfer, Harshitha Menon, Ignacio Laguna, Jackson Vanover, Ryan Vogt, Daniel Osei-Kuffuor
2022 B conf
Benchmarking Test-Time Unsupervised Deep Neural Network Adaptation on Edge Devices.
ISPASS
Kshitij Bhardwaj, James Diffenderfer, Bhavya Kailkhura, Maya B. Gokhale
2022 J jnl
Benchmarking Test-Time Unsupervised Deep Neural Network Adaptation on Edge Devices.
CoRR
Kshitij Bhardwaj, James Diffenderfer, Bhavya Kailkhura, Maya B. Gokhale
2022 J jnl
Efficient Multi-Prize Lottery Tickets: Enhanced Accuracy, Training, and Inference Speed.
CoRR
Hao Cheng, Pu Zhao, Yize Li, Xue Lin, James Diffenderfer, Ryan A. Goldhahn, Bhavya Kailkhura
2022 A* conf
Models Out of Line: A Fourier Lens on Distribution Shift Robustness.
NeurIPS
Sara Fridovich-Keil, Brian R. Bartoldson, James Diffenderfer, Bhavya Kailkhura, Timo Bremer
2022 J jnl
Models Out of Line: A Fourier Lens on Distribution Shift Robustness.
CoRR
Sara Fridovich-Keil, Brian R. Bartoldson, James Diffenderfer, Bhavya Kailkhura, Peer-Timo Bremer
2022 A conf
Unsupervised Test-Time Adaptation of Deep Neural Networks at the Edge: A Case Study.
DATE
Kshitij Bhardwaj, James Diffenderfer, Bhavya Kailkhura, Maya B. Gokhale
2022 J jnl
Zeroth-Order SciML: Non-intrusive Integration of Scientific Software with Deep Learning.
CoRR
Ioannis C. Tsaknakis, Bhavya Kailkhura, Sijia Liu, Donald Loveland, James Diffenderfer, Anna Maria Hiszpanski, Mingyi Hong
2021 J jnl
A Winning Hand: Compressing Deep Networks Can Improve Out-Of-Distribution Robustness.
CoRR
James Diffenderfer, Brian R. Bartoldson, Shreya Chaganti, Jize Zhang, Bhavya Kailkhura
2021 A* conf
A Winning Hand: Compressing Deep Networks Can Improve Out-of-Distribution Robustness.
NeurIPS
James Diffenderfer, Brian R. Bartoldson, Shreya Chaganti, Jize Zhang, Bhavya Kailkhura
2021 A conf
HPAC: evaluating approximate computing techniques on HPC OpenMP applications.
SC
Konstantinos Parasyris, Giorgis Georgakoudis, Harshitha Menon, James Diffenderfer, Ignacio Laguna, Daniel Osei-Kuffuor, Markus Schordan
2021 A* conf
Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network.
ICLR
James Diffenderfer, Bhavya Kailkhura
2021 J jnl
Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network.
CoRR
James Diffenderfer, Bhavya Kailkhura
2021 J jnl
QDOT: Quantized Dot Product Kernel for Approximate High-Performance Computing.
CoRR
James Diffenderfer, Daniel Osei-Kuffuor, Harshitha Menon
2020 J jnl
Stability Analysis of Inline ZFP Compression for Floating-Point Data in Iterative Methods.
CoRR
Alyson Fox, James Diffenderfer, Jeffrey Hittinger, Geoffrey Sanders, Peter Lindstrom
2020 J jnl
Stability Analysis of Inline ZFP Compression for Floating-Point Data in Iterative Methods.
SIAM J. Sci. Comput.
Alyson Fox, James Diffenderfer, Jeffrey Hittinger, Geoffrey Sanders, Peter Lindstrom
2019 J jnl
Error Analysis of ZFP Compression for Floating-Point Data.
SIAM J. Sci. Comput.
James Diffenderfer, Alyson Fox, Jeffrey A. F. Hittinger, Geoffrey Sanders, Peter G. Lindstrom
2017 J jnl
Construction of a full row-rank matrix system for multiple scanning directions in discrete tomography.
J. Comput. Appl. Math.
Xiezhang Li, James Diffenderfer, Jiehua Zhu