Artidoro Pagnoni

According to our database, Artidoro Pagnoni authored at least 20 papers between 2018 and 2026.

Collaborative distances:

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

2026

Fast Byte Latent Transformer.

Julie Kallini, Artidoro Pagnoni, Tomasz Limisiewicz, Gargi Ghosh, Luke Zettlemoyer, Christopher Potts, Xiaochuang Han, Srinivasan Iyer

CoRR, May, 2026

Compute Optimal Tokenization.

Tomasz Limisiewicz, Artidoro Pagnoni, Srinivasan Iyer, Mike Lewis, Sachin Mehta, Alisa Liu, Margaret Li, Gargi Ghosh, Luke Zettlemoyer

CoRR, May, 2026

2025

Byte Latent Transformer: Patches Scale Better Than Tokens.

Artidoro Pagnoni, Ramakanth Pasunuru, Pedro Rodríguez, John Nguyen, Benjamin Muller, Margaret Li, Chunting Zhou, Lili Yu, Jason E. Weston, Luke Zettlemoyer, Gargi Ghosh, Mike Lewis, Ari Holtzman, Srini Iyer

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Predicting vs. Acting: A Trade-off Between World Modeling & Agent Modeling.

Margaret Li, Weijia Shi, Artidoro Pagnoni, Peter West, Ari Holtzman

CoRR, 2024

2023

QLoRA: Efficient Finetuning of Quantized LLMs.

Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, Luke Zettlemoyer

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Socratic Pretraining: Question-Driven Pretraining for Controllable Summarization.

Artidoro Pagnoni, Alexander R. Fabbri, Wojciech Kryscinski, Chien-Sheng Wu

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

EvEntS ReaLM: Event Reasoning of Entity States via Language Models.

Evangelia Spiliopoulou, Artidoro Pagnoni, Yonatan Bisk, Eduard H. Hovy

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Threat Scenarios and Best Practices to Detect Neural Fake News.

Artidoro Pagnoni, Martin Graciarena, Yulia Tsvetkov

Proceedings of the 29th International Conference on Computational Linguistics, 2022

2021

WindTunnel: Towards Differentiable ML Pipelines Beyond a Single Modele.

Gyeong-In Yu, Saeed Amizadeh, Sehoon Kim, Artidoro Pagnoni, Ce Zhang, Byung-Gon Chun, Markus Weimer, Matteo Interlandi

Proc. VLDB Endow., 2021

Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics.

Artidoro Pagnoni, Vidhisha Balachandran, Yulia Tsvetkov

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

StructSum: Summarization via Structured Representations.

Vidhisha Balachandran, Artidoro Pagnoni, Jay Yoon Lee, Dheeraj Rajagopal, Jaime G. Carbonell, Yulia Tsvetkov

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

2020

StructSum: Incorporating Latent and Explicit Sentence Dependencies for Single Document Summarization.

Vidhisha Balachandran, Artidoro Pagnoni, Jay Yoon Lee, Dheeraj Rajagopal, Jaime G. Carbonell, Yulia Tsvetkov

CoRR, 2020

Definition Frames: Using Definitions for Hybrid Concept Representations.

Evangelia Spiliopoulou, Artidoro Pagnoni, Eduard H. Hovy

Proceedings of the 28th International Conference on Computational Linguistics, 2020

2019

Making Classical Machine Learning Pipelines Differentiable: A Neural Translation Approach.

Gyeong-In Yu, Saeed Amizadeh, Artidoro Pagnoni, Byung-Gon Chun, Markus Weimer, Matteo Interlandi

CoRR, 2019

Machine Learning at Microsoft with ML .NET.

Zeeshan Ahmed, Saeed Amizadeh, Mikhail Bilenko, Rogan Carr, Wei-Sheng Chin, Yael Dekel, Xavier Dupré, Vadim Eksarevskiy, Eric Erhardt, Costin Eseanu, Senja Filipi, Tom Finley, Abhishek Goswami, Monte Hoover, Scott Inglis, Matteo Interlandi, Shon Katzenberger, Najeeb Kazmi, Gleb Krivosheev, Pete Luferenko, Ivan Matantsev, Sergiy Matusevych, Shahab Moradi, Gani Nazirov, Justin Ormont, Gal Oshri, Artidoro Pagnoni, Jignesh Parmar, Prabhat Roy, Sarthak Shah, Mohammad Zeeshan Siddiqui, Markus Weimer, Shauheen Zahirazami, Yiwen Zhu

CoRR, 2019

Analyzing Branch-and-Bound Algorithms for the Multiprocessor Scheduling Problem.

Thomas Lively, William Long, Artidoro Pagnoni

CoRR, 2019

Machine Learning at Microsoft with ML.NET.

Zeeshan Ahmed, Saeed Amizadeh, Mikhail Bilenko, Rogan Carr, Wei-Sheng Chin, Yael Dekel, Xavier Dupré, Vadim Eksarevskiy, Senja Filipi, Tom Finley, Abhishek Goswami, Monte Hoover, Scott Inglis, Matteo Interlandi, Najeeb Kazmi, Gleb Krivosheev, Pete Luferenko, Ivan Matantsev, Sergiy Matusevych, Shahab Moradi, Gani Nazirov, Justin Ormont, Gal Oshri, Artidoro Pagnoni, Jignesh Parmar, Prabhat Roy, Mohammad Zeeshan Siddiqui, Markus Weimer, Shauheen Zahirazami, Yiwen Zhu

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018

PAC Learning Guarantees Under Covariate Shift.

Artidoro Pagnoni, Stefan Gramatovici, Samuel Liu

CoRR, 2018

Conditional Variational Autoencoder for Neural Machine Translation.

Artidoro Pagnoni, Kevin Liu, Shangyan Li

CoRR, 2018

Taint Tracking for WebAssembly.

Aron Szanto, Timothy Tamm, Artidoro Pagnoni

CoRR, 2018