Teaching Machines to Read and Comprehend

Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, +4

Oxford University Research Archive (ORA) (University of Oxford)

Artificial IntelligenceEngineeringLarge Scale TrainingElusive ChallengeLarge Language Model +15

Teaching Machines to Read and Comprehend

Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, +4

arXiv (Cornell University)

Artificial IntelligenceEngineeringLarge Scale TrainingElusive ChallengeLarge Language Model +15

Gemini: A Family of Highly Capable Multimodal Models

Gemini Robotics Team, Rohan Anil, Sebastian Borgeaud, +741

arXiv (Cornell University)

Artificial IntelligenceNatural Language ProcessingNew FamilyLarge Ai ModelImage Analysis +13

Reasoning about Entailment with Neural Attention

Tim Rocktäschel, Edward Grefenstette, Karl Moritz Hermann, +2

arXiv (Cornell University)

EngineeringMachine LearningEntailment (Linguistics)Textual EntailmentSemantics +19

Latent Predictor Networks for Code Generation

Ling Wang, Phil Blunsom, Edward Grefenstette, +4

Artificial IntelligenceEngineeringMachine LearningWang LingMathematical Linguistics +19

Learning and Evaluating General Linguistic Intelligence

Dani Yogatama, Cyprien de Masson d’Autume, Jerome T. Connor, +8

arXiv (Cornell University)

Artificial IntelligenceGeneral TasksLlm Fine-tuningEngineeringPsycholinguistics +17

Latent Predictor Networks for Code Generation

Ling Wang, Edward Grefenstette, Karl Moritz Hermann, +4

arXiv (Cornell University)

Artificial IntelligenceStructured PredictionEngineeringMachine LearningLarge Language Model +19

Aggregation and ordering in factorised databases

Nurzhan Bakibayev, Tomáš Kočiský, Dan Olteanu, +1

Proceedings of the VLDB Endowment

Relational DatabaseEngineeringData AggregationAggregate FunctionInformation Retrieval +15

Learning Bilingual Word Representations by Marginalizing Alignments

Tomáš Kočiský, Karl Moritz Hermann, Phil Blunsom

EngineeringCross-lingual RepresentationMultilingualismCorpus LinguisticsText Mining +15

Optimizing Performance of Recurrent Neural Networks on GPUs

Jeremy Appleyard, Tomáš Kočiský, Phil Blunsom

arXiv (Cornell University)

Convolutional Neural NetworkEngineeringMachine LearningComputer ArchitectureRecurrent Models +15