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Found 7 papers, 1 papers with code
XCOMPS: A Multilingual Benchmark of Conceptual Minimal Pairs
We introduce XCOMPS in this work, a multilingual conceptual minimal pair dataset covering 17 languages.
Large Language Models as Neurolinguistic Subjects: Identifying Internal Representations for Form and Meaning
This study investigates the linguistic understanding of Large Language Models (LLMs) regarding signifier (form) and signified (meaning) by distinguishing two LLM evaluation paradigms: psycholinguistic and neurolinguistic.
Remote Sensing-Based Assessment of Economic Development
The goal of our project is to use satellite data (including nighttime light data and remote sensing images) to give us some statistical estimation of the economic development level of a selected area (Singapore).
Decoding Probing: Revealing Internal Linguistic Structures in Neural Language Models using Minimal Pairs
4) For Transformer-based models, both embeddings and attentions capture grammatical features but show distinct patterns.
Survey on deep learning in multimodal medical imaging for cancer detection
Finally, we discuss the current scope of work and provide directions for the future development of multimodal cancer detection.
Do self-supervised speech and language models extract similar representations as human brain?
Speech and language models trained through self-supervised learning (SSL) demonstrate strong alignment with brain activity during speech and language perception.
