Tomáš Kočiský

Latent Predictor Networks for Code Generation

2016 · arXiv (Cornell University)

Many language generation tasks require the production of text conditioned on both structured and unstructured inputs. We present a novel neural network architecture which generates an output sequence conditioned on an arbitrary number of input …

Learning and Evaluating General Linguistic Intelligence

2019 · arXiv (Cornell University)

We define general linguistic intelligence as the ability to reuse previously acquired knowledge about a language's lexicon, syntax, semantics, and pragmatic conventions to adapt to new tasks quickly. Using this definition, we analyze state-of-the-art natural …

Mind the Gap: Assessing Temporal Generalization in Neural Language Models

2021 · arXiv (Cornell University)

Our world is open-ended, non-stationary, and constantly evolving; thus what we talk about and how we talk about it change over time. This inherent dynamic nature of language contrasts with the current static language modelling …

Teaching Machines to Read and Comprehend

2015 · arXiv (Cornell University)

Teaching machines to read natural language documents remains an elusive challenge. Machine reading systems can be tested on their ability to answer questions posed on the contents of documents that they have seen, but until …

Reasoning about Entailment with Neural Attention

2015 · arXiv (Cornell University)

While most approaches to automatically recognizing entailment relations have used classifiers employing hand engineered features derived from complex natural language processing pipelines, in practice their performance has been only slightly better than bag-of-word pair classifiers …

Dynamic Integration of Background Knowledge in Neural NLU Systems

2017 · arXiv (Cornell University)

Common-sense and background knowledge is required to understand natural language, but in most neural natural language understanding (NLU) systems, this knowledge must be acquired from training corpora during learning, and then it is static at …

The NarrativeQA Reading Comprehension Challenge

2018 · Transactions of the Association for Computational Linguistics

Reading comprehension (RC)—in contrast to information retrieval—requires integrating information and reasoning about events, entities, and their relations across a full document. Question answering is conventionally used to assess RC ability, in both artificial agents and …