Advances in phonotactic language recognition. - Ondrej Glembek; Pavel Matejka; Lukás Burget; Tomás Mikolov (INTERSPEECH, 2008)

BUT language recognition system for NIST 2007 evaluations. - Pavel Matejka; Lukás Burget; Ondrej Glembek; Petr Schwarz; Valiantsina Hubeika; Michal Fapso; Tomás Mikolov; Oldrich Plchot; Jan Cernocký (INTERSPEECH, 2008)

Neural network based language models for highly inflective languages. - Tomás Mikolov; Jirí Kopecký; Lukás Burget; Ondrej Glembek; Jan Cernocký (ICASSP, 2009)

Recurrent neural network based language model. - Tomás Mikolov; Martin Karafiát; Lukás Burget; Jan Cernocký; Sanjeev Khudanpur (INTERSPEECH, 2010)

Data selection and calibration issues in automatic language recognition - investigation with BUT-AGNITIO NIST LRE 2009 system. - Zdenek Jancik; Oldrich Plchot; Niko Brümmer; Lukás Burget; Ondrej Glembek; Valiantsina Hubeika; Martin Karafiát; Pavel Matejka; Tomás Mikolov; Albert Strasheim; Jan Cernocký (Odyssey, 2010)

PCA-based Feature Extraction for Phonotactic Language Recognition. - Tomás Mikolov; Oldrich Plchot; Ondrej Glembek; Lukás Burget; Jan Cernocký (Odyssey, 2010)

Strategies for training large scale neural network language models. - Tomás Mikolov; Anoop Deoras; Daniel Povey; Lukás Burget; Jan Cernocký (ASRU, 2011)

A Fast Re-scoring Strategy to Capture Long-Distance Dependencies. - Anoop Deoras; Tomás Mikolov; Kenneth Church 001 (EMNLP, 2011)

Variational approximation of long-span language models for lvcsr. - Anoop Deoras; Tomás Mikolov; Stefan Kombrink; Martin Karafiát; Sanjeev Khudanpur (ICASSP, 2011)

Extensions of recurrent neural network language model. - Tomás Mikolov; Stefan Kombrink; Lukás Burget; Jan Cernocký; Sanjeev Khudanpur (ICASSP, 2011)

Recurrent Neural Network Based Language Modeling in Meeting Recognition. - Stefan Kombrink; Tomás Mikolov; Martin Karafiát; Lukás Burget (INTERSPEECH, 2011)

Empirical Evaluation and Combination of Advanced Language Modeling Techniques. - Tomás Mikolov; Anoop Deoras; Stefan Kombrink; Lukás Burget; Jan Cernocký (INTERSPEECH, 2011)

Improving language models for ASR using translated in-domain data. - Stefan Kombrink; Tomás Mikolov; Martin Karafiát; Lukás Burget (ICASSP, 2012)

Context dependent recurrent neural network language model. - Tomás Mikolov; Geoffrey Zweig (SLT, 2012)

Understanding the exploding gradient problem - Razvan Pascanu; Tomás Mikolov; Yoshua Bengio (CoRR, 2012)

On the difficulty of training recurrent neural networks. - Razvan Pascanu; Tomás Mikolov; Yoshua Bengio (ICML (3), 2013)

Linguistic Regularities in Continuous Space Word Representations. - Tomás Mikolov; Wen-tau Yih; Geoffrey Zweig (HLT-NAACL, 2013)

Combining Heterogeneous Models for Measuring Relational Similarity. - Alisa Zhila; Wen-tau Yih; Christopher Meek; Geoffrey Zweig; Tomás Mikolov (HLT-NAACL, 2013)

DeViSE: A Deep Visual-Semantic Embedding Model. - Andrea Frome; Gregory S. Corrado; Jonathon Shlens; Samy Bengio; Jeffrey Dean; Marc'Aurelio Ranzato; Tomás Mikolov (NIPS, 2013)

Distributed Representations of Words and Phrases and their Compositionality. - Tomás Mikolov; Ilya Sutskever; Kai Chen 010; Gregory S. Corrado; Jeffrey Dean (NIPS, 2013)

One Billion Word Benchmark for Measuring Progress in Statistical Language Modeling. - Ciprian Chelba; Tomás Mikolov; Mike Schuster; Qi Ge; Thorsten Brants; Phillipp Koehn (CoRR, 2013)

Exploiting Similarities among Languages for Machine Translation. - Tomás Mikolov; Quoc V. Le; Ilya Sutskever (CoRR, 2013)

Efficient Estimation of Word Representations in Vector Space - Tomás Mikolov; Kai Chen 010; Greg Corrado; Jeffrey Dean (ICLR (Workshop Poster), 2013)

Approximate inference: A sampling based modeling technique to capture complex dependencies in a language model. - Anoop Deoras; Tomás Mikolov; Stefan Kombrink; Kenneth Church 001 (Speech Commun., 2013)

Using Neural Networks for Modeling and Representing Natural Languages. - Tomás Mikolov (COLING (Tutorials), 2014)

Distributed Representations of Sentences and Documents. - Quoc V. Le; Tomás Mikolov (ICML, 2014)

One billion word benchmark for measuring progress in statistical language modeling. - Ciprian Chelba; Tomás Mikolov; Mike Schuster; Qi Ge; Thorsten Brants; Phillipp Koehn; Tony Robinson (INTERSPEECH, 2014)

Zero-Shot Learning by Convex Combination of Semantic Embeddings. - Mohammad Norouzi 002; Tomás Mikolov; Samy Bengio; Yoram Singer; Jonathon Shlens; Andrea Frome; Greg Corrado; Jeffrey Dean (ICLR, 2014)

Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets. - Armand Joulin; Tomás Mikolov (NIPS, 2015)

Alternative structures for character-level RNNs. - Piotr Bojanowski; Armand Joulin; Tomás Mikolov (CoRR, 2015)

Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie Reviews. - Grégoire Mesnil; Tomás Mikolov; Marc'Aurelio Ranzato; Yoshua Bengio (ICLR (Workshop), 2015)

Learning Longer Memory in Recurrent Neural Networks. - Tomás Mikolov; Armand Joulin; Sumit Chopra; Michaël Mathieu; Marc'Aurelio Ranzato (ICLR (Workshop), 2015)

A Roadmap Towards Machine Intelligence. - Tomás Mikolov; Armand Joulin; Marco Baroni (CICLing (1), 2016)

Learning Simple Algorithms from Examples. - Wojciech Zaremba; Tomás Mikolov; Armand Joulin; Rob Fergus (ICML, 2016)

FastText.zip: Compressing text classification models. - Armand Joulin; Edouard Grave; Piotr Bojanowski; Matthijs Douze; Hervé Jégou; Tomás Mikolov (CoRR, 2016)

Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks. - Jason Weston; Antoine Bordes; Sumit Chopra; Tomás Mikolov (ICLR (Poster), 2016)

Fast Linear Model for Knowledge Graph Embeddings. - Armand Joulin; Edouard Grave; Piotr Bojanowski; Maximilian Nickel; Tomás Mikolov (AKBC@NIPS, 2017)

Bag of Tricks for Efficient Text Classification. - Armand Joulin; Edouard Grave; Piotr Bojanowski; Tomás Mikolov (EACL (2), 2017)

CommAI: Evaluating the first steps towards a useful general AI. - Marco Baroni; Armand Joulin; Allan Jabri; Germán Kruszewski; Angeliki Lazaridou; Klemen Simonic; Tomás Mikolov (ICLR (Workshop), 2017)

Variable Computation in Recurrent Neural Networks. - Yacine Jernite; Edouard Grave; Armand Joulin; Tomás Mikolov (ICLR (Poster), 2017)

Learning Simpler Language Models with the Delta Recurrent Neural Network Framework. - Alexander G. Ororbia II; Tomás Mikolov; David Reitter (CoRR, 2017)

Learning Simpler Language Models with the Differential State Framework. - Alexander G. Ororbia II; Tomás Mikolov; David Reitter (Neural Comput., 2017)

Enriching Word Vectors with Subword Information. - Piotr Bojanowski; Edouard Grave; Armand Joulin; Tomás Mikolov (Trans. Assoc. Comput. Linguistics, 2017)

Efficient Large-Scale Multi-Modal Classification. - Douwe Kiela; Edouard Grave; Armand Joulin; Tomás Mikolov (AAAI, 2018)

Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion. - Armand Joulin; Piotr Bojanowski; Tomás Mikolov; Hervé Jégou; Edouard Grave (EMNLP, 2018)

Learning Word Vectors for 157 Languages. - Edouard Grave; Piotr Bojanowski; Prakhar Gupta; Armand Joulin; Tomás Mikolov (LREC, 2018)

Advances in Pre-Training Distributed Word Representations. - Tomás Mikolov; Edouard Grave; Piotr Bojanowski; Christian Puhrsch; Armand Joulin (LREC, 2018)

Improving Supervised Bilingual Mapping of Word Embeddings. - Armand Joulin; Piotr Bojanowski; Tomás Mikolov; Edouard Grave (CoRR, 2018)

Evolving Structures in Complex Systems. - Hugo Cisneros; Josef Sivic; Tomás Mikolov (SSCI, 2019)

Place Deduplication with Embeddings. - Carl Yang 001; Do Huy Hoang; Tomás Mikolov; Jiawei Han 001 (WWW, 2019)

Updating Pre-trained Word Vectors and Text Classifiers using Monolingual Alignment. - Piotr Bojanowski; Onur Celebi; Tomás Mikolov; Edouard Grave; Armand Joulin (CoRR, 2019)

Visualizing computation in large-scale cellular automata. - Hugo Cisneros; Josef Sivic; Tomás Mikolov (ALIFE, 2020)

Classification of Complex Systems Based on Transients. - Barbora Hudcová; Tomás Mikolov (ALIFE, 2020)

Combinatory Chemistry: Towards a Simple Model of Emergent Evolution. - Germán Kruszewski; Tomás Mikolov (ALIFE, 2020)

Class-Agnostic Continual Learning of Alternating Languages and Domains. - Germán Kruszewski; Ionut-Teodor Sorodoc; Tomás Mikolov (CoRR, 2020)

Special Issue "On Defining Artificial Intelligence" - Commentaries and Author's Response. - Dagmar Monett; Colin W. P. Lewis; Kristinn R. Thórisson; Joscha Bach; Gianluca Baldassarre; Giovanni Granato; Istvan S. N. Berkeley; François Chollet; Matthew Crosby; Henry Shevlin; John F. Sowa; John E. Laird; et al. (J. Artif. Gen. Intell., 2020)

Language Modeling and Artificial Intelligence. - Tomás Mikolov (Interspeech, 2021)

Computational Hierarchy of Elementary Cellular Automata. - Barbora Hudcová; Tomás Mikolov (ALIFE, 2021)

Benchmarking Learning Efficiency in Deep Reservoir Computing. - Hugo Cisneros; Tomás Mikolov; Josef Sivic (CoLLAs, 2022)

Emergence of Novelty in Evolutionary Algorithms. - David Herel; Dominika Zogatova; Matej Kripner; Tomás Mikolov (CoRR, 2022)

Classification of Discrete Dynamical Systems Based on Transients. - Barbora Hudcová; Tomás Mikolov (Artif. Life, 2022)

Emergence of Self-Reproducing Metabolisms as Recursive Algorithms in an Artificial Chemistry. - Germán Kruszewski; Tomás Mikolov (Artif. Life, 2022)

Preserving Semantics in Textual Adversarial Attacks. - David Herel; Hugo Cisneros; Tomás Mikolov (ECAI, 2023)

Advancing State of the Art in Language Modeling. - David Herel; Tomás Mikolov (CoRR, 2023)

Collapse of Self-trained Language Models. - David Herel; Tomás Mikolov (Tiny Papers @ ICLR, 2024)

Large Language Models: A Survey. - Shervin Minaee; Tomás Mikolov; Narjes Nikzad; Meysam Chenaghlu; Richard Socher; Xavier Amatriain; Jianfeng Gao 001 (CoRR, 2024)

Thinking Tokens for Language Modeling. - David Herel; Tomás Mikolov (CoRR, 2024)

Time Awareness in Large Language Models: Benchmarking Fact Recall Across Time. - David Herel; Vojtech Bartek; Tomás Mikolov (CoRR, 2024)