William F. Shen

According to our database, William F. Shen authored at least 16 papers between 2024 and 2026.

Collaborative distances:

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

2026

Rethinking Rubric Generation for Improving LLM Judge and Reward Modeling for Open-ended Tasks.

William F. Shen, Xinchi Qiu, Chenxi Whitehouse, Lisa Alazraki, Shashwat Goel, Francesco Barbieri, Timon Willi, Akhil Mathur, Ilias Leontiadis

CoRR, February, 2026

LoRDO: Distributed Low-Rank Optimization with Infrequent Communication.

Andrej Jovanovic, Alex Iacob, Mher Safaryan, Ionut-Vlad Modoranu, Lorenzo Sani, William F. Shen, Xinchi Qiu, Dan Alistarh, Nicholas D. Lane

CoRR, February, 2026

Scaling Small Agents Through Strategy Auctions.

Lisa Alazraki, William F. Shen, Yoram Bachrach, Akhil Mathur

CoRR, February, 2026

Balanced Accuracy: The Right Metric for Evaluating LLM Judges - Explained through Youden's J statistic.

Stephane Collot, Colin Fraser, Justin Zhao, William F. Shen, Timon Willi, Ilias Leontiadis

Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026

Editing as Unlearning: Are Knowledge Editing Methods Strong Baselines for Large Language Model Unlearning?

Zexi Li, Xiangzhu Wang, William F. Shen, Meghdad Kurmanji, Xinchi Qiu, Dongqi Cai, Chao Wu, Nicholas D. Lane

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Training AI Co-Scientists Using Rubric Rewards.

Shashwat Goel, Rishi Hazra, Dulhan Jayalath, Timon Willi, Parag Jain, William F. Shen, Ilias Leontiadis, Francesco Barbieri, Yoram Bachrach, Jonas Geiping, Chenxi Whitehouse

CoRR, December, 2025

MT-DAO: Multi-Timescale Distributed Adaptive Optimizers with Local Updates.

Alex Iacob, Andrej Jovanovic, Mher Safaryan, Meghdad Kurmanji, Lorenzo Sani, Samuel Horváth, William F. Shen, Xinchi Qiu, Nicholas D. Lane

CoRR, October, 2025

AbbIE: Autoregressive Block-Based Iterative Encoder for Efficient Sequence Modeling.

Preslav Aleksandrov, Meghdad Kurmanji, Fernando García-Redondo, David O'Shea, William F. Shen, Alex Iacob, Lorenzo Sani, Xinchi Qiu, Nicola Cancedda, Nicholas D. Lane

CoRR, July, 2025

Don't Make It Up: Preserving Ignorance Awareness in LLM Fine-Tuning.

William F. Shen, Xinchi Qiu, Nicola Cancedda, Nicholas D. Lane

CoRR, June, 2025

DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models.

Alex Iacob, Lorenzo Sani, Mher Safaryan, Paris Giampouras, Samuel Horváth, Andrej Jovanovic, Meghdad Kurmanji, Preslav Aleksandrov, William F. Shen, Xinchi Qiu, Nicholas D. Lane

CoRR, May, 2025

LUNAR: LLM Unlearning via Neural Activation Redirection.

William F. Shen, Xinchi Qiu, Meghdad Kurmanji, Alex Iacob, Lorenzo Sani, Yihong Chen, Nicola Cancedda, Nicholas D. Lane

CoRR, February, 2025

Permissioned LLMs: Enforcing Access Control in Large Language Models.

Bargav Jayaraman, Virendra J. Marathe, Hamid Mozaffari, William F. Shen, Krishnaram Kenthapadi

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

DEPT: Decoupled Embeddings for Pre-training Language Models.

Alex Iacob, Lorenzo Sani, Meghdad Kurmanji, William F. Shen, Xinchi Qiu, Dongqi Cai, Yan Gao, Nicholas Donald Lane

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

PISTOL: Dataset Compilation Pipeline for Structural Unlearning of LLMs.

Xinchi Qiu, William F. Shen, Yihong Chen, Nicola Cancedda, Pontus Stenetorp, Nicholas D. Lane

CoRR, 2024

Worldwide Federated Training of Language Models.

Alex Iacob, Lorenzo Sani, Bill Marino, Preslav Aleksandrov, William F. Shen, Nicholas Donald Lane

CoRR, 2024

The Future of Large Language Model Pre-training is Federated.

Lorenzo Sani, Alex Iacob, Zeyu Cao, Bill Marino, Yan Gao, Tomás Paulik, Wanru Zhao, William F. Shen, Preslav Aleksandrov, Xinchi Qiu, Nicholas D. Lane

CoRR, 2024