Transformer models such as GPT generate human-like language and are predictive of human brain responses to language. Here, using functional-MRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict t ...
While largely neglected over decades during which adaptive immunity captured most of the attention, innate immune mechanisms have now become central to our understanding of immunology. Innate immunity provides the first barrier to infection in vertebrates, ...
The Dependent Object Type (DOT) calculus was designed to put Scala on a
sound basis, but while DOT relies on structural subtyping, Scala is a
fundamentally class-based language. This impedance mismatch means that a proof
of DOT soundness by itself is ...
Due to the increasing demands of today's fast-paced world, mental health concerns are on the rise, which necessitates innovative approaches to provide support to those in need. Open-domain conversational agents known as chatbots, offer a unique opportunit ...
Language has shaped human evolution and led to the desire to endow machines with language abilities. Recent advancements in natural language processing enable us to achieve this breakthrough in human-machine interaction. However, introducing conversational ...
Abstractive summarization has seen big improvements in recent years, mostly due to advances in neural language modeling, language model pretraining, and scaling models and datasets. While large language models generate summaries that are fluent, coherent, ...
The objective of this study was to evaluate the effect of Motor Imagery (MI) training on language comprehension. In line with literature suggesting an intimate relationship between the language and the motor system, we proposed that a MI-training could imp ...
One of the many purposes for which social robots are designed is education, and there have been many attempts to systematize their potential in this field. What these attempts have in common is the recognition that learning can be supported in a variety of ...
Term extraction is an information extraction task at the root of knowledge discovery platforms. Developing term extractors that are able to generalize across very diverse and potentially highly technical domains is challenging, as annotations for domains r ...
Despite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich languages like English. This work focuses on Persian language, one of the wid ...
Poor decisions and selfish behaviors give rise to seemingly intractable global problems, such as the lack of transparency in democratic processes, the spread of conspiracy theories, and the rise in greenhouse gas emissions. However, people are more predict ...
Subword modeling for zero-resource languages aims to learn low-level representations of speech audio without using transcriptions or other resources from the target language (such as text corpora or pronunciation dictionaries). A good representation should ...
In this paper, we trace the history of neural networks applied to natural language understanding tasks, and identify key contributions which the nature of language has made to the development of neural network architectures. We focus on the importance of v ...
This research occurred in a special context where Kazakhstan's recent decision to switch from Cyrillic to the Latin-based alphabet has resulted in challenges connected to teaching literacy, addressing a rare combination of research hypotheses and technical ...
Multimedia databases are growing rapidly in size in the digital age. To increase the value of these data and to enhance the user experience, there is a need to make these videos searchable through automatic indexing. Because people appearing and talking in ...
The relationship between the entropy of language and its complexity has been the subject of much speculation – some seeing the increase of linguistic entropy as a sign of linguistic complexification or interpreting entropy drop as a marker of greater regul ...
Industry is increasingly turning to reconfigurable architectures like FPGAs and CGRAs for improved performance and energy efficiency. Unfortunately, adoption of these architectures has been limited by their programming models. HDLs lack abstractions for pr ...
Have you ever wondered what is the secret sauce of Scala.js? What defines Scala.js, above all else, is the overarching will to make it cross-platform. A cross-platform language is both portable-most source code cross-compiles and behaves the same way on mu ...
Programming languages are increasingly compiled to multiple runtimes, each featuring their own rich structures such as their object model.
Furthermore, they need to interact with other languages targeting said runtimes.
A language targeting only one runtim ...
Designing digital circuits well is notoriously difficult. This difficulty stems in part from the very
many degrees of freedom inherent in circuit design, typically coupled with the need to satisfy
various constraints. In this thesis, we demonstrate how for ...
