Aleksandra Piktus
Aleksandra Piktus
Other namesOla Piktus
Cohere | Sapienza, University of Rome
Verified email at
Cited by
Cited by
Retrieval-augmented generation for knowledge-intensive nlp tasks
P Lewis, E Perez, A Piktus, F Petroni, V Karpukhin, N Goyal, H Küttler, ...
Advances in Neural Information Processing Systems 33, 9459-9474, 2020
Kilt: a benchmark for knowledge intensive language tasks
F Petroni, A Piktus, A Fan, P Lewis, M Yazdani, N De Cao, J Thorne, ...
arXiv preprint arXiv:2009.02252, 2020
How Context Affects Language Models' Factual Predictions
F Petroni, P Lewis, A Piktus, T Rocktäschel, Y Wu, AH Miller, S Riedel
arXiv preprint arXiv:2005.04611, 2020
Paq: 65 million probably-asked questions and what you can do with them
P Lewis, Y Wu, L Liu, P Minervini, H Küttler, A Piktus, P Stenetorp, ...
Transactions of the Association for Computational Linguistics 9, 1098-1115, 2021
Scaling data-constrained language models
N Muennighoff, A Rush, B Barak, T Le Scao, N Tazi, A Piktus, S Pyysalo, ...
Advances in Neural Information Processing Systems 36, 2024
Misspelling Oblivious Word Embeddings
B Edizel, A Piktus, P Bojanowski, R Ferreira, E Grave, F Silvestri
arXiv preprint arXiv:1905.09755, 2019
How Decoding Strategies Affect the Verifiability of Generated Text
L Massarelli, F Petroni, A Piktus, M Ott, T Rocktäschel, V Plachouras, ...
arXiv preprint arXiv:1911.03587, 2019
Domain-matched Pre-training Tasks for Dense Retrieval
B Oğuz, K Lakhotia, A Gupta, P Lewis, V Karpukhin, A Piktus, X Chen, ...
arXiv preprint arXiv:2107.13602, 2021
Generating Fact Checking Briefs
A Fan, A Piktus, F Petroni, G Wenzek, M Saeidi, A Vlachos, A Bordes, ...
Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020
The Web Is Your Oyster--Knowledge-Intensive NLP against a Very Large Web Corpus
A Piktus, F Petroni, V Karpukhin, D Okhonko, S Broscheit, G Izacard, ...
arXiv preprint arXiv:2112.09924, 2021
The ROOTS Search Tool: Data Transparency for LLMs
A Piktus, C Akiki, P Villegas, H Laurençon, G Dupont, AS Luccioni, ...
arXiv preprint arXiv:2302.14035, 2023
FinGPT: Large Generative Models for a Small Language
R Luukkonen, V Komulainen, J Luoma, A Eskelinen, J Kanerva, ...
arXiv preprint arXiv:2311.05640, 2023
Evaluate & evaluation on the hub: Better best practices for data and model measurements
L Von Werra, L Tunstall, A Thakur, S Luccioni, T Thrush, A Piktus, F Marty, ...
Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022
Node Masking: Making Graph Neural Networks Generalize and Scale Better
P Mishra, A Piktus, G Goossen, F Silvestri
arXiv preprint arXiv:2001.07524, 2020
Improving wikipedia verifiability with ai
F Petroni, S Broscheit, A Piktus, P Lewis, G Izacard, L Hosseini, ...
Nature Machine Intelligence 5 (10), 1142-1148, 2023
Spacerini: Plug-and-play Search Engines with Pyserini and Hugging Face
C Akiki, O Ogundepo, A Piktus, X Zhang, A Oladipo, J Lin, M Potthast
arXiv preprint arXiv:2302.14534, 2023
GAIA Search: Hugging Face and Pyserini Interoperability for NLP Training Data Exploration
A Piktus, O Ogundepo, C Akiki, A Oladipo, X Zhang, H Schoelkopf, ...
arXiv preprint arXiv:2306.01481, 2023
Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models
P Verga, S Hofstatter, S Althammer, Y Su, A Piktus, A Arkhangorodsky, ...
arXiv preprint arXiv:2404.18796, 2024
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