Human Language
Human language research aims to understand how humans process, produce, and learn language, focusing on both its cognitive and computational aspects. Current research heavily utilizes large language models (LLMs) and vision-language models (VLMs), applying them to tasks like word sense disambiguation, cross-modal reasoning, and the analysis of language in diverse contexts such as online communities and medical images. These advancements are improving machine translation, text-to-speech synthesis, and other applications while also providing new tools for investigating fundamental questions about human cognition and language acquisition.
Papers
Can Machines Imitate Humans? Integrative Turing Tests for Vision and Language Demonstrate a Narrowing Gap
Mengmi Zhang, Giorgia Dellaferrera, Ankur Sikarwar, Caishun Chen, Marcelo Armendariz, Noga Mudrik, Prachi Agrawal, Spandan Madan, Mranmay Shetty, Andrei Barbu, Haochen Yang, Tanishq Kumar, Shui'Er Han, Aman Raj Singh, Meghna Sadwani, Stella Dellaferrera, Michele Pizzochero, Brandon Tang, Yew Soon Ong, Hanspeter Pfister, Gabriel Kreiman
On the Typicality of Musical Sequences
Mathias Rose Bjare, Stefan Lattner