Results 101 to 110 of about 22,074,380 (291)

CLRe: A Synergistic Dual‐Engine Framework for One‐Step Retrosynthesis Prediction

Advanced Science, EarlyView.
CLRe uses a contrastive difficulty score to order pretrained seq2seq fine‐tuning for retrosynthesis. Reaction embeddings define the ranking score, and a cumulative easy‐to‐hard schedule expands from the easiest subset to the full training set while earlier examples remain active.
Tianhao Su, Xitao Wang, Musen Li, Guanhua Qin, Shunbo Hu, Tong‐Yi Zhang   +5 more
wiley   +1 more source

Principles of Large Language Models (LLM)

Journal of Numerical and Applied Mathematics
This paper explores the operational principles of large language models (LLMs), focusing in particular on the mechanism of next-token generation within the process of autoregressive modeling. It outlines the theoretical foundations of neural language models, the transformer architecture with its self-attention mechanism, and the roles of tokenization ...
openaire   +1 more source

Recommender Systems in the Era of Large Language Models (LLMs)

IEEE Transactions on Knowledge and Data Engineering
With the prosperity of e-commerce and web applications, Recommender Systems (RecSys) have become an important component of our daily life, providing personalized suggestions that cater to user preferences. While Deep Neural Networks (DNNs) have made significant advancements in enhancing recommender systems by modeling user-item interactions and ...
Zihuai Zhao, Wenqi Fan, Jiatong Li, Yunqing Liu, Xiaowei Mei, Yiqi Wang, Zhen Wen, Fei Wang, Xiangyu Zhao, Jiliang Tang, Qing Li   +10 more
openaire   +4 more sources

CoSP: Reconfigurable Metamaterial Inverse Design via Contrastive Pretrained Large Language Model

Advanced Science, EarlyView.
In this work, CoSP (contrastive multi‐state pretrain), an intelligent inverse design method for reconfigurable metamaterials based on a contrastive pretrained large language model, is proposed. Numerical experiments demonstrate that CoSP can design reconfigurable metamaterial structures for multi‐state, multi‐band optical responses, showing great ...
Shujie Yang, Yuqi Zhang, Xuzhe Zhao, Yansong Tang, Kaichen Dong   +4 more
wiley   +1 more source

You believe your LLM is not delusional? Think again! a study of LLM hallucination on foundation models under perturbation

Discover Data
Large Language Model (LLM) has recently become almost a household term because of its wide range of applications and immense popularity. However, hallucination in LLMs is a critical issue as it affects the quality of an LLM’s response, reduces user trust
Anirban Saha, Binay Gupta, Anirban Chatterjee, Kunal Banerjee   +3 more
doaj   +1 more source

Vision-language large learning model, GPT4V, accurately classifies the Boston Bowel Preparation Scale score

BMJ Open Gastroenterology
Introduction Large learning models (LLMs) such as GPT are advanced artificial intelligence (AI) models. Originally developed for natural language processing, they have been adapted for multi-modal tasks with vision-language input. One clinically relevant
Yuhe Ke, Chee Kiat Tan, Yu Bin Tan, Daniel Yan Zheng Lim, Jonas Ren Yi Ho, Sushmitha Carkarine, Tian Wei Valerie Chew, Jen Hong Tan, Ting Fang Tan, Kabilan Elangovan, Le Quan, Li Yuan Jin, Jasmine Chiat Ling Ong, Gerald Gui Ren Sng, Joshua Yi Min Tung, Damien Tan   +15 more
doaj   +1 more source

Feasibility Study of a Large Language Model (LLM) [PDF]

Tato diplomová práce se zabývá studií proveditelnosti velkého jazykového modelu (LLM) srovnatelného s GPT-4, nejmodernějším modelem vyvinutým společností OpenAI. Práce analyzuje technické požadavky, finanční aspekty, etické otázky a praktické aplikace, s
Samuel Seidel
core  

Neuromorphic Devices and Computing for Sensing, Memory, and Control

Advanced Science, EarlyView.
This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu, Nicholas Schaffer, Xiao Yang   +2 more
wiley   +1 more source

Tool Selection by Large Language Model (LLM) Agents [PDF]

Current large language model (LLM) agents rely on a tightly coupled, single-step tool selection mechanism that fails to distinguish between tool capabilities and implementations, reducing flexibility when multiple tools offer similar functions.
Jagannath, Kishore
core   +1 more source

Analytical justification of a protocol of assessing large language models for use in educational systems

Вестник Университета гражданской защиты МЧС Беларуси
Purpose. To analyze known issues related to the quality of large language models (LLMs), architectural solutions aimed at improving the quality, and integrating models into electronic systems, including educational systems, and existing LLM assessment ...
Andrey V. Surikov, Natal'ya V. Zaynudinova, Dmitriy N. Yashenya, Violetta V. Zholnerchik   +3 more
doaj   +1 more source