Results 111 to 120 of about 98,573 (298)

GPT no iekšpuses: ko var iesākt ar GPT? Matemātiķa skatījums. Mans skatījums. [PDF]

open access: yes, 2023
Aplūkojam vienu no AI language model rīkiem, ChatGPT, ko matemātiķis var gūt no šādām AI sistēmām. Apskatām sarunas ar GPT, apskatām rekomendācijas, kādas dod gan pats GPT, gan ko izsecinām no prakses, GPT lietojot.
Zeps, Dainis
core  

Reversible, Chemically Gated FRET via Ligand‐Activated Acceptors

open access: yesAdvanced Science, EarlyView.
Fluorogen binding turns the compact FAST tag into a tunable FRET acceptor, with ligand chemistry programming spectral overlap and excited‐state lifetimes. Fluorescence‐lifetime imaging reads out energy transfer through the shortened donor lifetime, while simply adding or washing out the dye switches FRET on and off, reversibly mapping the supramodular ...
Nivedita Singh   +7 more
wiley   +1 more source

Object Counting with GPT-4o and GPT-5: A Comparative Study

open access: yes2026 IEEE 24th World Symposium on Applied Machine Intelligence and Informatics (SAMI)
Zero-shot object counting attempts to estimate the number of object instances belonging to novel categories that the vision model performing the counting has never encountered during training. Existing methods typically require large amount of annotated data and often require visual exemplars to guide the counting process.
Richard Füzesséry   +3 more
openaire   +2 more sources

Long-Term Growth Driven by a Sequence of General Purpose Technologies [PDF]

open access: yes
We present a Schumpterian model of endogenous growth with General Purpose Technologies (GPTs) that captures two important historical stylized facts: First, from the beginning of mankind until today GPTs are arriving at an increasing frequency and, second,
Daniel Schiess, Roger Wehrli
core  

Towards a Compositional Framework for Describing Human Phenotypes

open access: yesAdvanced Science, EarlyView.
The Phenotype Assembly Method (PhenoAM) decomposes phenotype variables into measurable Features and typed Qualifiers, enabling standardized, machine‐readable Phenome Data Elements (PhenoDEs) that preserve measurement context. Applied in the International Human Phenome Project (IHPP), the framework yields 58 371 PhenoDEs and supports component‐level ...
Wanting Hu   +11 more
wiley   +1 more source

Customised GPTs for Lexicography

open access: yesLexikos
About a year and a half ago, lexicographers realised that the enthusiasm they had when using ChatGPT-3.5 for English lexicography, could not be carried over to other languages, not even big ones like Portuguese. A year ago, the lexicographic community was made aware that ChatGPT-3.5 could not be used at all for small languages, and especially not for ...
openaire   +4 more sources

GPT-4/4V's performance on the Japanese National Medical Licensing Examination

open access: yes
Recent advances in Artificial Intelligence (AI) are changing the medical world, and AI will likely replace many of the actions performed by medical professionals.
Yuki Sumi (18423646)   +1 more
core   +1 more source

MAPA: A Semantic Network Framework for Functional Module Discovery and Interpretation in Multi‐Omics Data

open access: yesAdvanced Science, EarlyView.
MAPA transforms complex multi‐omics data into biologically coherent functional modules by integrating pathway information with molecular interaction networks. Retrieval‐augmented large language models then generate structured, literature‐informed interpretations.
Yifei Ge   +13 more
wiley   +1 more source

Neuron‐Derived Vesicular circMagi1 Restrains Vascular Repair After Ischemic Stroke by Promoting TRIM65‐Mediated ANXA2 Degradation

open access: yesAdvanced Science, EarlyView.
After ischemic stroke, injured neurons transfer circMagi1 to endothelial cells through extracellular vesicles. Within endothelial cells, circMagi1 binds ANXA2 and enhances its engagement with TRIM65, promoting ANXA2 ubiquitination and proteasomal degradation to constrain angiogenic repair.
Youkun Bi   +16 more
wiley   +1 more source

In harmony with gpt-oss

open access: yesCoRR
No one has independently reproduced OpenAI's published scores for gpt-oss-20b with tools, because the original paper discloses neither the tools nor the agent harness. We reverse-engineered the model's in-distribution tools: when prompted without tool definitions, gpt-oss still calls tools from its training distribution with high statistical confidence
openaire   +2 more sources

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