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2020 – today
- 2024
[i12]Margaret Li, Weijia Shi, Artidoro Pagnoni, Peter West, Ari Holtzman:
Predicting vs. Acting: A Trade-off Between World Modeling & Agent Modeling. CoRR abs/2407.02446 (2024)- 2023
- [c8]Artidoro Pagnoni, Alexander R. Fabbri, Wojciech Kryscinski, Chien-Sheng Wu:
Socratic Pretraining: Question-Driven Pretraining for Controllable Summarization. ACL (1) 2023: 12737-12755 - [c7]Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, Luke Zettlemoyer:
QLoRA: Efficient Finetuning of Quantized LLMs. NeurIPS 2023 - [i11]Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, Luke Zettlemoyer:
QLoRA: Efficient Finetuning of Quantized LLMs. CoRR abs/2305.14314 (2023) - 2022
- [c6]Artidoro Pagnoni, Martin Graciarena, Yulia Tsvetkov:
Threat Scenarios and Best Practices to Detect Neural Fake News. COLING 2022: 1233-1249 - [c5]Evangelia Spiliopoulou, Artidoro Pagnoni, Yonatan Bisk, Eduard H. Hovy:
EvEntS ReaLM: Event Reasoning of Entity States via Language Models. EMNLP 2022: 1982-1997 - [i10]Evangelia Spiliopoulou, Artidoro Pagnoni, Yonatan Bisk, Eduard H. Hovy:
EvEntS ReaLM: Event Reasoning of Entity States via Language Models. CoRR abs/2211.05392 (2022) - [i9]Artidoro Pagnoni, Alexander R. Fabbri, Wojciech Kryscinski, Chien-Sheng Wu:
Socratic Pretraining: Question-Driven Pretraining for Controllable Summarization. CoRR abs/2212.10449 (2022) - 2021
- [j1]Gyeong-In Yu, Saeed Amizadeh, Sehoon Kim, Artidoro Pagnoni, Ce Zhang, Byung-Gon Chun, Markus Weimer, Matteo Interlandi:
WindTunnel: Towards Differentiable ML Pipelines Beyond a Single Modele. Proc. VLDB Endow. 15(1): 11-20 (2021) - [c4]Vidhisha Balachandran, Artidoro Pagnoni, Jay Yoon Lee, Dheeraj Rajagopal, Jaime G. Carbonell, Yulia Tsvetkov:
StructSum: Summarization via Structured Representations. EACL 2021: 2575-2585 - [c3]Artidoro Pagnoni, Vidhisha Balachandran, Yulia Tsvetkov:
Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics. NAACL-HLT 2021: 4812-4829 - [i8]Artidoro Pagnoni, Vidhisha Balachandran, Yulia Tsvetkov:
Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics. CoRR abs/2104.13346 (2021) - 2020
- [c2]Evangelia Spiliopoulou, Artidoro Pagnoni, Eduard H. Hovy:
Definition Frames: Using Definitions for Hybrid Concept Representations. COLING 2020: 3060-3068 - [i7]Vidhisha Balachandran, Artidoro Pagnoni, Jay Yoon Lee, Dheeraj Rajagopal, Jaime G. Carbonell, Yulia Tsvetkov:
StructSum: Incorporating Latent and Explicit Sentence Dependencies for Single Document Summarization. CoRR abs/2003.00576 (2020)
2010 – 2019
- 2019
- [c1]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:
Machine Learning at Microsoft with ML.NET. KDD 2019: 2448-2458 - [i6]Thomas Lively, William Long, Artidoro Pagnoni:
Analyzing Branch-and-Bound Algorithms for the Multiprocessor Scheduling Problem. CoRR abs/1901.07070 (2019) - [i5]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:
Machine Learning at Microsoft with ML .NET. CoRR abs/1905.05715 (2019) - [i4]Gyeong-In Yu, Saeed Amizadeh, Artidoro Pagnoni, Byung-Gon Chun, Markus Weimer, Matteo Interlandi:
Making Classical Machine Learning Pipelines Differentiable: A Neural Translation Approach. CoRR abs/1906.03822 (2019) - 2018
- [i3]Aron Szanto, Timothy Tamm, Artidoro Pagnoni:
Taint Tracking for WebAssembly. CoRR abs/1807.08349 (2018) - [i2]Artidoro Pagnoni, Kevin Liu, Shangyan Li:
Conditional Variational Autoencoder for Neural Machine Translation. CoRR abs/1812.04405 (2018) - [i1]Artidoro Pagnoni, Stefan Gramatovici, Samuel Liu:
PAC Learning Guarantees Under Covariate Shift. CoRR abs/1812.06393 (2018)
Coauthor Index
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