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 …

Two analytic traditions characterize fMRI language research. One relies on averaging activations
across individuals. This approach has limitations: because of inter-individual variability …

Automated fact checking is becoming increasingly vital as both truthful and fallacious information
accumulate online. Research on fact checking has benefited from large-scale datasets …

Pre-trained Transformer-based neural architectures have consistently achieved state-of-the-art
performance in the Natural Language Inference (NLI) task. Since NLI examples …

SentSpace is a modular framework for streamlined evaluation of text. SentSpacecharacterizes
textual input using diverse lexical, syntactic, and semantic features derivedfrom corpora …

Multilingual language models achieve impressive zero-shot accuracies in many languages
in complex tasks such as Natural Language Inference (NLI). Examples in NLI (and …

Automatic fact-checking is crucial for recognizing misinformation spreading on the internet.
Most existing fact-checkers break down the process into several subtasks, one of which …

In this paper, we study reconfiguration systems for proper graph colorings modified by single-vertex
recolorings. Applying a general construction of Ghrist and Peterson [15] to the graph …

Neural models excel at extracting statistical patterns from large amounts of data, but struggle
to learn patterns or reason about language from only a few examples. In this paper, we ask: …

We propose a new system for the transcription of Sanskrit text written using the Devanagari
orthography, into the International Phonetic Alphabet, and supplement it with free and open-…