Neil Band

According to our database, Neil Band authored at least 15 papers between 2020 and 2026.

Collaborative distances:

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

2026

Learned Relay Representations for Forward-Thinking Discrete Diffusion Models.

Benjamin Rozonoyer, Jacopo Minniti, Dhruvesh Patel, Neil Band, Avishek Joey Bose, Tim G. J. Rudner, Andrew McCallum

CoRR, May, 2026

Synthetic Data for any Differentiable Target.

Tristan Thrush, Sung Min Park, Herman Brunborg, Luke Bailey, Marcel Roed, Neil Band, Christopher Potts, Tatsunori Hashimoto

CoRR, April, 2026

2025

Curriculum-Guided Layer Scaling for Language Model Pretraining.

Karanpartap Singh, Neil Band, Ehsan Adeli

CoRR, June, 2025

Reasoning to Learn from Latent Thoughts.

Yangjun Ruan, Neil Band, Chris J. Maddison, Tatsunori Hashimoto

CoRR, March, 2025

Synthetic continued pretraining.

Zitong Yang, Neil Band, Shuangping Li, Emmanuel J. Candès, Tatsunori Hashimoto

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Simple Factuality Probes Detect Hallucinations in Long-Form Natural Language Generation.

Jiatong Han, Neil Band, Muhammed Razzak, Jannik Kossen, Tim G. J. Rudner, Yarin Gal

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

2024

Linguistic Calibration of Language Models.

Neil Band, Xuechen Li, Tengyu Ma, Tatsunori Hashimoto

CoRR, 2024

Linguistic Calibration of Long-Form Generations.

Neil Band, Xuechen Li, Tengyu Ma, Tatsunori Hashimoto

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2022

Plex: Towards Reliability using Pretrained Large Model Extensions.

Dustin Tran, Jeremiah Z. Liu, Michael W. Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, Kelly Buchanan, Kevin Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan

CoRR, 2022

2021

Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks.

Andrey Malinin, Neil Band, Alexander Ganshin, German Chesnokov, Yarin Gal, Mark J. F. Gales, Alexey Noskov, Andrey Ploskonosov, Liudmila Prokhorenkova, Ivan Provilkov, Vatsal Raina, Vyas Raina, Mariya Shmatova, Panos Tigas, Boris Yangel

CoRR, 2021

Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning.

Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Z. Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran

CoRR, 2021

Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks.

Andrey Malinin, Neil Band, Yarin Gal, Mark J. F. Gales, Alexander Ganshin, German Chesnokov, Alexey Noskov, Andrey Ploskonosov, Liudmila Prokhorenkova, Ivan Provilkov, Vatsal Raina, Vyas Raina, Denis Roginskiy, Mariya Shmatova, Panagiotis Tigas, Boris Yangel

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning.

Jannik Kossen, Neil Band, Clare Lyle, Aidan N. Gomez, Thomas Rainforth, Yarin Gal

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

Benchmarking Bayesian Deep Learning on Diabetic Retinopathy Detection Tasks.

Neil Band, Tim G. J. Rudner, Qixuan Feng, Angelos Filos, Zachary Nado, Mike Dusenberry, Ghassen Jerfel, Dustin Tran, Yarin Gal

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020

MemFlow: Memory-Aware Distributed Deep Learning.

Neil Band

Proceedings of the 2020 International Conference on Management of Data, 2020