Lample, Guillaume

LLaMA: Open and Efficient Foundation Language Models

Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.-A., Lacroix, T., Rozière, B., Goyal, N., Hambro, E., Azhar, F., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 4,602

Neural Architectures for Named Entity Recognition

Lample, G., Ballesteros, M., Subramanian, S., Kawakami, K., & Dyer, C. (2016) · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingNatural Language Processing Techniques

Cited by 4,401

Cross-lingual Language Model Pretraining

Lample, G., & Conneau, A. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1,586

What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic properties

Conneau, A., Kruszewski, G., Lample, G., Barrault, L., & Baroni, M. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingSentiment Analysis and Opinion Mining

Cited by 657

Unsupervised Machine Translation Using Monolingual Corpora Only

Lample, G., Conneau, A., Denoyer, L., & Ranzato, M. (2017) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 584

Mistral 7B

Jiang, A. Q., Sablayrolles, A., Mensch, A., Bamford, C., Chaplot, D. S., Casas, D. D. L., Bressand, F., Lengyel, G., Lample, G., Saulnier, L., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 340

Mixtral of Experts

Jiang, A. Q., Sablayrolles, A., Roux, A., Mensch, A., Savary, B., Bamford, C., Chaplot, D. S., Casas, D. D. L., Hanna, E. B., Bressand, F., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 143

Unsupervised translation of programming languages

Lachaux, M.-A., Roziere, B., Chanussot, L., & Lample, G. (2020) · arXiv

Software Engineering ResearchNatural Language Processing Techniques

Cited by 83

Augmenting Self-attention with Persistent Memory

Sukhbaatar, S., Grave, E., Lample, G., Jegou, H., & Joulin, A. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 75

Large Memory Layers with Product Keys

Lample, G., Sablayrolles, A., Ranzato, M., Denoyer, L., & Jégou, H. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 72

Ministral 3

Liu, A. H., Khandelwal, K., Subramanian, S., Jouault, V., Rastogi, A., Sadé, A., Jeffares, A., Jiang, A., Cahill, A., Gavaudan, A., et al. (2026) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 64

HyperTree Proof Search for Neural Theorem Proving

Lample, G., Lachaux, M.-A., Lavril, T., Martinet, X., Hayat, A., Ebner, G., Rodriguez, A., & Lacroix, T. (2022) · arXiv

Logic, programming, and type systemsLogic, Reasoning, and Knowledge

Cited by 45

HyperTree Proof Search for Neural Theorem Proving

Lample, G., Lacroix, T., Lachaux, M.-A., Rodriguez, A., Hayat, A., Lavril, T., Ebner, G., & Martinet, X. (2022) · Advances in Neural Information Processing Systems 35

Logic, programming, and type systemsLogic, Reasoning, and Knowledge

Cited by 45

Leveraging automated unit tests for unsupervised code translation

Roziere, B., Zhang, J. M., Charton, F., Harman, M., Synnaeve, G., & Lample, G. (2021) · arXiv

Software Engineering ResearchNatural Language Processing Techniques

Cited by 39

Pixtral 12B

Agrawal, P., Antoniak, S., Hanna, E. B., Bout, B., Chaplot, D., Chudnovsky, J., Costa, D., De Monicault, B., Garg, S., Gervet, T., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 8