Large language models (LLMs) with multimodal input capability have been demonstrated in various applications. Vision language models (VLMs), which were developed from LLMs, can process and learn both visual and textual data simultaneously, enabling them to generate descriptive text from images. This study explores the...
A. V. Ega, Dadang Gunawan, Abdul Halim et al.· Bulletin of Electrical Engin...· 0 citations
FAIR PERSONALIZATION & EXTERNAL VALIDITY AT THE LIMITCalibration Privilege, Exclusion Risk, Subgroup Uncertainty, Cross-Site Transfer, Device Heterogeneity, and Equitable Adaptive BCI Feng Cheng-en (33) x Starli Does personalization help people differently - or does it simply make access easier for the people who were...
Abstract
This article argues that the legal profession’s existing duties of competence, supervision, candour, confidentiality, and procedural fairness provide the necessary framework for integrating generative AI into legal practice, without requiring a wholly new regulatory paradigm. Narrowing its focus to transforme...
Context window capacity remains a central bottleneck for large language models (LLMs): enlarging the window does not guarantee that a model attends to the right information, and empirical work has shown systematic degradation when relevant content sits in the middle of a long context. Biological cognition faces an anal...
Syuaib Syuaib· Zenodo (CERN European Organi...· 0 citations
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Context window capacity remains a central bottleneck for large language models (LLMs): enlarging the window does not guarantee that a model attends to the right information, and empirical work has shown systematic degradation when relevant content sits in the middle of a long context. Biological cognition faces an anal...
Syuaib Syuaib· Zenodo (CERN European Organi...· 0 citations
New evidence from large language models and animal communication challenges human linguistic exceptionalism. Drawing on historical parallels between linguistics and evolutionary biology, this comment argues that new evidence from non-human linguistic behavior could transform humanity's relationship with the natural wor...
Gašper Beguš· Zenodo (CERN European Organi...· 0 citations
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/23071859. Authors of the review Name: Stephanie R. U, ORCID: https://orcid.org/0000-0002-6220-4661 Bio: Stephanie U is a PhD candidate whose work investigates the role of circadian...
Stephanie U, 2 other authors· Zenodo (CERN European Organi...· 0 citations
Generative Artificial Intelligence (AI), particularly Large Language Models (LLMs), has introduced new forms of interaction between humans and language technologies beyond automated text generation. This study aims to examine how generative AI transforms human language processes, cognitive activities, and meaning const...
Y. Dasman· International Journal of Int...· 0 citations
Abstract This research involved co-creating a systematic review analysis alongside the world’s smartest humanoid robot, Ami. The work involved a human-humanoid collaboration in understanding driving under the influence of drugs’ (DUIDs’) prevalence, implications and chemical analysis. The systematic review was conducte...
Sulaf A. Assi, Krista Grimza, Abdullah Al-Hamid et al.· Journal of Intelligent & Rob...· 0 citations
Observing what a large language model computes during autoregressive inference—online and without training probes—remains difficult. We introduce Lingtai, a training-free concept telemetry layer: at each generation step, residual states are projected onto a domain-specific bank of named concept anchors, constructed wit...
Jiangang Chen· Zenodo (CERN European Organi...· 0 citations
Observing what a large language model computes during autoregressive inference—online and without training probes—remains difficult. We introduce Lingtai, a training-free concept telemetry layer: at each generation step, residual states are projected onto a domain-specific bank of named concept anchors, constructed wit...
Jiangang Chen· Zenodo (CERN European Organi...· 0 citations
FAIR PERSONALIZATION & EXTERNAL VALIDITY AT THE LIMITCalibration Privilege, Exclusion Risk, Subgroup Uncertainty, Cross-Site Transfer, Device Heterogeneity, and Equitable Adaptive BCI Feng Cheng-en (33) x Starli Does personalization help people differently - or does it simply make access easier for the people who were...
