Fetching the paper…
Reading the bibliography…
Recent advancements in Large Language Models (LLMs) have significantly enhanced their ability to generate and manipulate human language, highlighting their potential across various applications.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
Earlier work this paper cites.
Le rilevazioni invalsi: a che cosa servono?
Cristiano Corsini and Bruno Losito · 2013
Earlier work this paper cites.
La validità di contenuto delle prove invalsi di comprensione della lettura
Cristiano Corsini · 2013
Earlier work this paper cites.
Il servizio nazionale di valutazione e le prove invalsi. stato dell’arte e proposte per una valutazione come agente di cambiamento
Roberto Trinchero · 2014
Earlier work this paper cites.
Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang · 2016
Earlier work this paper cites.
Il database gestinv delle prove standardizzate invalsi: Uno strumento per la ricerca: Alcuni esempi di utilizzo nell’ambito della matematica
Giorgio Bolondi, Alessandro Gambini, and Federica Ferretti · 2017
Earlier work this paper cites.
“questione di feedback”: dati invalsi e pratiche di valutazione in classe
Serafina Pastore, Michela Freddano, et al · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Think you have solved question answering? try arc, the ai2 reasoning challenge
Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord · 2018
Earlier work this paper cites.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
Earlier work this paper cites.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Earlier work this paper cites.
How multilingual is multilingual bert?
Telmo Pires, Eva Schlinger, and Dan Garrette · 2019
Earlier work this paper cites.
Hellaswag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi · 2019
Earlier work this paper cites.
Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi · 2019
Earlier work this paper cites.
Improving multilingual models with language-clustered vocabularies
Hyung Won Chung, Dan Garrette, Kiat Chuan Tan, and Jason Riesa · 2020
Earlier work this paper cites.
Geppetto carves italian into a language model
Lorenzo De Mattei, Michele Cafagna, Felice Dell’Orletta, Malvina Nissim, and Marco Guerini · 2020
Earlier work this paper cites.
Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2020
Earlier work this paper cites.
Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei · 2020
Earlier work this paper cites.
On the multilingual capabilities of very large-scale english language models
Jordi Armengol-Estapé, Ona de Gibert Bonet, and Maite Melero · 2021
Cited alongside, same era.
Training verifiers to solve math word problems, 2021
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al · 2021
Cited alongside, same era.
Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
Cited alongside, same era.
Truthfulqa: Measuring how models mimic human falsehoods
Stephanie Lin, Jacob Hilton, and Owain Evans · 2021
Cited alongside, same era.
Uinauil: A unified benchmark for italian natural language understanding
Valerio Basile, Livio Bioglio, Alessio Bosca, Cristina Bosco, and Viviana Patti · 2023
Later among the works it cites.
A survey on evaluation of large language models, 2023
Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, and Xing Xie · 2023
Later among the works it cites.
La competenza grammaticale nelle prove invalsi
Giulia Guzzo · 2023
Later among the works it cites.
Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al · 2023
Later among the works it cites.
Evalita 2023: Overview of the 8th evaluation campaign of natural language processing and speech tools for italian
Mirko Lai, Stefano Menini, Marco Polignano, Valentina Russo, Rachele Sprugnoli, Giulia Venturi, et al · 2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Sebastian Ruder, Noah Constant, Jan Botha, Aditya Siddhant, Orhan Firat, Jinlan Fu, Pengfei Liu, Junjie Hu, Dan Garrette, Graham Neubig, et al · 2021
Cited alongside, same era.
Winogrande: An adversarial winograd schema challenge at scale
Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi · 2021
Cited alongside, same era.
Towards reasoning in large language models: A survey
Jie Huang and Kevin Chen-Chuan Chang · 2022
Cited alongside, same era.
Quality at a glance: An audit of web-crawled multilingual datasets
Julia Kreutzer, Isaac Caswell, Lisa Wang, Ahsan Wahab, Daan van Esch, Nasanbayar Ulzii-Orshikh, Allahsera Tapo, Nishant Subramani, Artem Sokolov, Claytone Sikasote, et al · 2022
Cited alongside, same era.
Two new datasets for italian-language abstractive text summarization
Nicola Landro, Ignazio Gallo, Riccardo La Grassa, and Edoardo Federici · 2022
Cited alongside, same era.
Holistic evaluation of language models
Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, et al · 2022
Cited alongside, same era.
Peft: State-of-the-art parameter-efficient fine-tuning methods
Sourab Mangrulkar, Sylvain Gugger, Lysandre Debut, Younes Belkada, Sayak Paul, and Benjamin Bossan · 2022
Cited alongside, same era.
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, et al · 2022
Cited alongside, same era.
Later among the works it cites.
Bloom: A 176b-parameter open-access multilingual language model
Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, Matthias Gallé, et al · 2023
Later among the works it cites.
Xlm-v: Overcoming the vocabulary bottleneck in multilingual masked language models
Davis Liang, Hila Gonen, Yuning Mao, Rui Hou, Naman Goyal, Marjan Ghazvininejad, Luke Zettlemoyer, and Madian Khabsa · 2023
Later among the works it cites.
Camoscio: An italian instruction-tuned llama
Andrea Santilli and Emanuele Rodolà · 2023
Later among the works it cites.
Gemini: a family of highly capable multimodal models
Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al · 2023
Later among the works it cites.
Riflettere sulle parole: la formazione delle parole nelle prove invalsi
Zuzana Tóth · 2023
Later among the works it cites.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
Later among the works it cites.
Zephyr: Direct distillation of lm alignment, 2023
Lewis Tunstall, Edward Beeching, Nathan Lambert, Nazneen Rajani, Kashif Rasul, Younes Belkada, Shengyi Huang, Leandro von Werra, Clémentine Fourrier, Nathan Habib, Nathan Sarrazin, Omar Sanseviero, Alexander M. Rush, and Thomas Wolf · 2023
Later among the works it cites.
Llama 3 model card
AI@Meta · 2024
Closest in time.
Qlora: Efficient finetuning of quantized llms
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer · 2024
Closest in time.
Albert Q Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, et al · 2024
Closest in time.
Eliciting the translation ability of large language models via multilingual finetuning with translation instructions
Jiahuan Li, Hao Zhou, Shujian Huang, Shanbo Cheng, and Jiajun Chen · 2024
Closest in time.
Advanced natural-based interaction for the italian language: Llamantino-3-anita, 2024
Marco Polignano, Pierpaolo Basile, and Giovanni Semeraro · 2024
Closest in time.
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, et al · 2024
Closest in time.