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Tracking the perspectives of interacting language models
Large language models (LLMs) are capable of producing high quality information at
unprecedented rates. As these models continue to entrench themselves in society, the …
unprecedented rates. As these models continue to entrench themselves in society, the …
Investigating the application of graph theory features in hand movement directions decoding using EEG signals
In recent years, functional analysis of brain networks based on graph theory properties has
attracted considerable attention. This approach has usually been exploited for structural and …
attracted considerable attention. This approach has usually been exploited for structural and …
On the Feasibility of EEG-based Motor Intention Detection for Real-Time Robot Assistive Control
This paper explores the feasibility of employing EEG-based intention detection for real-time
robot assistive control. We focus on predicting and distinguishing motor intentions of left/right …
robot assistive control. We focus on predicting and distinguishing motor intentions of left/right …
Embedding-based statistical inference on generative models
The recent cohort of publicly available generative models can produce human expert level
content across a variety of topics and domains. Given a model in this cohort as a base …
content across a variety of topics and domains. Given a model in this cohort as a base …
Consistent estimation of generative model representations in the data kernel perspective space
Generative models, such as large language models and text-to-image diffusion models,
produce relevant information when presented a query. Different models may produce …
produce relevant information when presented a query. Different models may produce …
Approximately optimal domain adaptation with fisher's linear discriminant
We propose and study a data-driven method that can interpolate between a classical and a
modern approach to classification for a class of linear models. The class is the convex …
modern approach to classification for a class of linear models. The class is the convex …
Comparing Foundation Models using Data Kernels
Recent advances in self-supervised learning and neural network scaling have enabled the
creation of large models, known as foundation models, which can be easily adapted to a …
creation of large models, known as foundation models, which can be easily adapted to a …
A Noble EEG Classification Method Using Wavelet Scattering of Feature Extraction for Mental Attention State Detection
Y Zheng - 2024 China Automation Congress (CAC), 2024 - ieeexplore.ieee.org
The mental attention state directly affects an individual's learning ability. It is important for
teachers to understand a student's mental attention state in real teaching. Although many …
teachers to understand a student's mental attention state in real teaching. Although many …