Sai Praneeth Karimireddy
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
17
Venues
6
Active years
2018–2026
Best venue rank
A*
Where they publish
Papers
17 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | Psychological Steering in LLMs: An Evaluation of Effectiveness and Trustworthiness. | Amin Banayeeanzade, Ala N. Tak, Fatemeh Bahrani, Anahita Bolourani, Leonardo Blas, Emilio Ferrara, Jonathan Gratch, Sai Praneeth Karimireddy |
| 2025 | ACL | Reconsidering LLM Uncertainty Estimation Methods in the Wild. | Yavuz Faruk Bakman, Duygu Nur Yaldiz, Sungmin Kang, Tuo Zhang, Baturalp Buyukates, Salman Avestimehr, Sai Praneeth Karimireddy |
| 2025 | EMNLP | A Systematic Analysis of Base Model Choice for Reward Modeling. | Kian Ahrabian, Pegah Jandaghi, Negar Mokhberian, Sai Praneeth Karimireddy, Jay Pujara |
| 2025 | EMNLP | TruthTorchLM: A Comprehensive Library for Predicting Truthfulness in LLM Outputs. | Duygu Nur Yaldiz, Yavuz Faruk Bakman, Sungmin Kang, Alperen zis, Hayrettin Eren Yildiz, Mitash Ashish Shah, Zhiqi Huang, Anoop Kumar, Alfy Samuel, Daben Liu, Sai Praneeth Karimireddy, Salman Avestimehr |
| 2024 | ICML | Collaborative Heterogeneous Causal Inference Beyond Meta-analysis. | Tianyu Guo, Sai Praneeth Karimireddy, Michael I. Jordan |
| 2023 | ICLR | Agree to Disagree: Diversity through Disagreement for Better Transferability. | Matteo Pagliardini, Martin Jaggi, Franois Fleuret, Sai Praneeth Karimireddy |
| 2023 | ICML | Federated Conformal Predictors for Distributed Uncertainty Quantification. | Charles Lu, Yaodong Yu, Sai Praneeth Karimireddy, Michael I. Jordan, Ramesh Raskar |
| 2022 | ICLR | Towards Model Agnostic Federated Learning Using Knowledge Distillation. | Andrei Afonin, Sai Praneeth Karimireddy |
| 2022 | ICLR | Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing. | Sai Praneeth Karimireddy, Lie He, Martin Jaggi |
| 2021 | ICML | Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data. | Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi |
| 2021 | ICML | Learning from History for Byzantine Robust Optimization. | Sai Praneeth Karimireddy, Lie He, Martin Jaggi |
| 2020 | AISTATS | Accelerating Gradient Boosting Machines. | Haihao Lu, Sai Praneeth Karimireddy, Natalia Ponomareva, Vahab S. Mirrokni |
| 2020 | ICML | SCAFFOLD: Stochastic Controlled Averaging for Federated Learning. | Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh |
| 2020 | MICCAI | Weight Erosion: An Update Aggregation Scheme for Personalized Collaborative Machine Learning. | Felix Grimberg, Mary-Anne Hartley, Martin Jaggi, Sai Praneeth Karimireddy |
| 2019 | AISTATS | Efficient Greedy Coordinate Descent for Composite Problems. | Sai Praneeth Karimireddy, Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi |
| 2019 | ICML | Error Feedback Fixes SignSGD and other Gradient Compression Schemes. | Sai Praneeth Karimireddy, Quentin Rebjock, Sebastian U. Stich, Martin Jaggi |
| 2018 | ICML | On Matching Pursuit and Coordinate Descent. | Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy, Gunnar Rtsch, Bernhard Schlkopf, Sebastian U. Stich, Martin Jaggi |