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In recent years Large Language Models (LLMs) have increased the state of the art on several natural language processing tasks.
Language models are few-shot learners,
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Bart-it: An efficient sequence-to-sequence model for italian text summarization,
M. La Quatra, L. Cagliero, · 1999
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ROUGE: A package for automatic evaluation of summaries,
C.-Y. Lin, · 2004
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The wacky wide web: a collection of very large linguistically processed web-crawled corpora,
M. Baroni, S. Bernardini, A. Ferraresi, E. Zanchetta, · 2009
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Squad: 100,000+ questions for machine comprehension of text,
P. Rajpurkar, J. Zhang, K. Lopyrev, P. Liang, · 2016
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Long-term social media data collection at the university of turin,
V. Basile, M. Lai, M. Sanguinetti, et al., · 2018
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Neural learning for question answering in italian,
D. Croce, A. Zelenanska, R. Basili, · 2018
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Dear sir or madam, may i introduce the gyafc dataset: Corpus, benchmarks and metrics for formality style transfer,
S. Rao, J. Tetreault, · 2018
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Alberto: Italian bert language understanding model for nlp challenging tasks based on tweets,
M. Polignano, P. Basile, M. De Gemmis, G. Semeraro, V. Basile, et al., · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding,
J. Devlin, M.-W. Chang, K. Lee, K. Toutanova, · 2019
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Large scale datasets for image and video captioning in italian,
A. Scaiella, D. Croce, R. Basili, · 2019
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Deep bidirectional transformers for italian question answering,
D. Croce, G. Brandi, R. Basili, · 2019
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Bertscore: Evaluating text generation with bert,
T. Zhang, V. Kishore, F. Wu, K. Q. Weinberger, Y. Artzi, · 2019
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The woman worked as a babysitter: On biases in language generation,
E. Sheng, K.-W. Chang, P. Natarajan, N. Peng, · 2019
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Geppetto carves italian into a language model,
L. D. Mattei, M. Cafagna, F. Dell’Orletta, M. Nissim, M. Guerini, · 2020
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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension,
M. Lewis, Y. Liu, N. Goyal, M. Ghazvininejad, A. Mohamed, O. Levy, V. Stoyanov, L. Zettlemoyer, · 2020
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The curious case of neural text degeneration,
A. Holtzman, J. Buys, L. Du, M. Forbes, Y. Choi, · 2020
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Change-it@ evalita 2020: Change headlines, adapt news, generate,
L. De Mattei, M. Cafagna, A. AI, F. Dell’Orletta, M. Nissim, A. Gatt, · 2020
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Transformers: State-of-the-Art Natural Language Processing,
T. Wolf, L. Debut, V. Sanh, J. Chaumond, C. Delangue, A. Moi, P. Cistac, C. Ma, Y. Jernite, J. Plu, C. Xu, T. Le Scao, S. Gugger, M. Drame, Q. Lhoest, A. M. Rush, · 2020
Cited alongside, same era.
Finetuned language models are zero-shot learners,
J. Wei, M. Bosma, V. Zhao, K. Guu, A. W. Yu, B. Lester, N. Du, A. M. Dai, Q. V. Le, · 2021
Cited alongside, same era.
On the opportunities and risks of foundation models,
R. Bommasani, D. A. Hudson, E. Adeli, R. Altman, S. Arora, S. von Arx, M. S. Bernstein, J. Bohg, A. Bosselut, E. Brunskill, et al., · 2021
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale,
A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly, J. Uszkoreit, N. Houlsby, · 2021
Cited alongside, same era.
mT5: A massively multilingual pre-trained text-to-text transformer,
L. Xue, N. Constant, A. Roberts, M. Kale, R. Al-Rfou, A. Siddhant, A. Barua, C. Raffel, · 2021
S. Mangrulkar, S. Gugger, L. Debut, Y. Belkada, S. Paul, Peft: State-of-the-art parameter-efficient fine-tuning methods, https://github.com/huggingface/peft , 2022
2022
Later among the works it cites.
Llm.int8(): 8-bit matrix multiplication for transformers at scale,
T. Dettmers, M. Lewis, Y. Belkada, L. Zettlemoyer, · 2022
Later among the works it cites.
OpenAI, Gpt-4 technical report, 2023. arXiv:2303.08774
2023
Closest in time.
Llama: Open and efficient foundation language models,
H. Touvron, T. Lavril, G. Izacard, X. Martinet, M.-A. Lachaux, T. Lacroix, B. Rozière, N. Goyal, E. Hambro, F. Azhar, et al., · 2023
Closest in time.
R. Taori, I. Gulrajani, T. Zhang, Y. Dubois, X. Li, C. Guestrin, P. Liang, T. B. Hashimoto, Stanford alpaca: An instruction-following llama model, https://github.com/tatsu-lab/stanford_alpaca , 2023
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Cited alongside, same era.
Synthetic data augmentation for zero-shot cross-lingual question answering,
A. Riabi, T. Scialom, R. Keraron, B. Sagot, D. Seddah, J. Staiano, · 2021
Cited alongside, same era.
WITS: wikipedia for italian text summarization,
S. Casola, A. Lavelli, · 2021
Cited alongside, same era.
Datasets: A community library for natural language processing,
Q. Lhoest, A. Villanova del Moral, Y. Jernite, A. Thakur, P. von Platen, S. Patil, J. Chaumond, M. Drame, J. Plu, L. Tunstall, J. Davison, M. Šaško, G. Chhablani, B. Malik, S. Brandeis, T. Le Scao, V. Sanh, C. Xu, N. Patry, A. McMillan-Major, P. Schmid, S. Gugger, C. Delangue, T. Matussière, L. Debut, S. Bekman, P. Cistac, T. Goehringer, V. Mustar, F. Lagunas, A. Rush, T. Wolf, · 2021
Cited alongside, same era.
Olá, bonjour, salve! xformal: A benchmark for multilingual formality style transfer,
E. Briakou, D. Lu, K. Zhang, J. Tetreault, · 2021
Cited alongside, same era.
On the dangers of stochastic parrots: Can language models be too big?,
E. M. Bender, T. Gebru, A. McMillan-Major, S. Shmitchell, · 2021
Cited alongside, same era.
Decoupled weight decay regularization,
I. Loshchilov, F. Hutter, · 2021
Cited alongside, same era.
Palm: Scaling language modeling with pathways,
A. Chowdhery, S. Narang, J. Devlin, M. Bosma, G. Mishra, A. Roberts, P. Barham, H. W. Chung, C. Sutton, S. Gehrmann, et al., · 2022
Cited alongside, same era.
2023
Closest in time.
Latent autoregressive source separation,
E. Postolache, G. Mariani, M. Mancusi, A. Santilli, L. Cosmo, E. Rodolà, · 2023
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Multimodal neural databases,
G. Trappolini, A. Santilli, E. Rodolà, A. Halevy, F. Silvestri, · 2023
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Accelerating transformer inference for translation via parallel decoding,
A. Santilli, S. Severino, E. Postolache, V. Maiorca, M. Mancusi, R. Marin, E. Rodola, · 2023
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Fauno: The italian large language model that will leave you senza parole!,
A. Bacciu, G. Trappolini, A. Santilli, E. Rodolà, F. Silvestri, · 2023
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2023
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Michael, Stambecco: Italian instruction-following llama model, https://github.com/mchl-labs/stambecco , 2023
2023
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Instruction tuning with gpt-4,
B. Peng, C. Li, P. He, M. Galley, J. Gao, · 2023
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E. J. Wang, Alpaca-lora, https://github.com/tloen/alpaca-lora , 2023
2023
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Self-instruct: Aligning language models with self-generated instructions,
Y. Wang, Y. Kordi, S. Mishra, A. Liu, N. A. Smith, D. Khashabi, H. Hajishirzi, · 2023
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2023
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UINAUIL: A unified benchmark for Italian natural language understanding,
V. Basile, L. Bioglio, A. Bosca, C. Bosco, V. Patti, · 2023
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2023
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Survey of hallucination in natural language generation,
Z. Ji, N. Lee, R. Frieske, T. Yu, D. Su, Y. Xu, E. Ishii, Y. J. Bang, A. Madotto, P. Fung, · 2023
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