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Deploying large language models (LLMs) encounters challenges due to intensive computational and memory requirements.
Smooth bilingual n n -gram translation
Holger Schwenk, Marta R. Costa-jussà, and Jose A. R. Fonollosa. 2007 · 2007
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Continuous space translation models with neural networks
Hai Son Le, Alexandre Allauzen, and François Yvon. 2012 · 2012
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Fast and robust neural network joint models for statistical machine translation
Jacob Devlin, Rabih Zbib, Zhongqiang Huang, Thomas Lamar, Richard Schwartz, and John Makhoul. 2014 · 2014
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Load what you need: Smaller versions of mutililingual BERT
Amine Abdaoui, Camille Pradel, and Grégoire Sigel. 2020 · 2020
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Edinburgh’s submissions to the 2020 machine translation efficiency task
Nikolay Bogoychev, Roman Grundkiewicz, Alham Fikri Aji, Maximiliana Behnke, Kenneth Heafield, Sidharth Kashyap, Emmanouil-Ioannis Farsarakis, and Mateusz Chudyk. 2020 · 2020
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 2020
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The highs and lows of simple lexical domain adaptation approaches for neural machine translation
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WikiMatrix: Mining 135M parallel sentences in 1620 language pairs from Wikipedia
Holger Schwenk, Vishrav Chaudhary, Shuo Sun, Hongyu Gong, and Francisco Guzmán. 2021 · 2021
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Llm.int8(): 8-bit matrix multiplication for transformers at scale
Tim Dettmers, Mike Lewis, Younes Belkada, and Luke Zettlemoyer. 2022 · 2022
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The devil is in the details: On the pitfalls of vocabulary selection in neural machine translation
Tobias Domhan, Eva Hasler, Ke Tran, Sony Trenous, Bill Byrne, and Felix Hieber. 2022 · 2022
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Openassistant conversations - democratizing large language model alignment
Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, Sotiris Anagnostidis, Zhi-Rui Tam, Keith Stevens, Abdullah Barhoum, Nguyen Minh Duc, Oliver Stanley, Richárd Nagyfi, et al. 2023 · 2023
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Stanford alpaca: An instruction-following llama model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto. 2023 · 2023
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LLaMA: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al. 2023 · 2023
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Efficient multilingual language model compression through vocabulary trimming
Asahi Ushio, Yi Zhou, and Jose Camacho-Collados. 2023 · 2023
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Monolingual or multilingual instruction tuning: Which makes a better alpaca
Pinzhen Chen, Shaoxiong Ji, Nikolay Bogoychev, Andrey Kutuzov, Barry Haddow, and Kenneth Heafield. 2024 · 2024
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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. 2022 · 2022
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