Results 111 to 120 of about 22,074,380 (291)

Universal Battery Capacity Degradation Forecasting Driven by Foundation Models Across Diverse Chemistries and Conditions

Advanced Science, EarlyView.
A unified time‐series forecasting framework learns transferable battery capacity‐degradation patterns from 20 heterogeneous datasets spanning chemistries, formats, temperatures, and cycling conditions. A single model delivers competitive predictions on both known and previously unseen datasets, while physics‐guided representation learning improves ...
Joey Chan, Huan Wang, Zhen Chen, Haoyu Pan, Wei Wu, Zirong Wang, Ershun Pan, Min Xie, Lifeng Xi   +8 more
wiley   +1 more source

Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model

In this study, we introduce CT-LLM, a 2B large language model (LLM) that illustrates a pivotal shift towards prioritizing the Chinese language in developing LLMs.
Luo, Xinchen, Cheng, Yuyang, Zhang, Ge, Liu, Jiaheng, Ma, Ziyang, Zhou, Guorui, Yuan, Ruibin, Chen, Wenhu, Gao, Songyang, Pan, Ding, Zheng, Tianyu, Yu, Zhouliang, Du, Xinrun, Qu, Xingwei   +13 more
core  

Electroforming‐Free, Self‐Rectifying Selector‐Only Memory With Diffusive Cu‐Ion Dynamics for Logic‐In‐Memory Computing

Advanced Science, EarlyView.
Electroforming‐free, self‐rectifying switching with polarity‐dependent threshold modulation is realized in selector‐only memory through Cu‐ion migration in a bilayer stacked dual functional materials. Ultrafast rupturing of Cu filament enables drift‐free operation with high stability.
Jae‐Kyeong Kim, Dae‐Seong Woo, Min‐Jong Han, Hong‐Gwang Seo, Gwang‐Ho Park, In‐Taek Woo, Jea‐Gun Park, Jinsub Park   +7 more
wiley   +1 more source

Evalita-LLM: Benchmarking Large Language Models on Italian

CoRR
We describe Evalita-LLM, a new benchmark designed to evaluate Large Language Models (LLMs) on Italian tasks. The distinguishing and innovative features of Evalita-LLM are the following: (i) all tasks are native Italian, avoiding issues of translating from Italian and potential cultural biases; (ii) in addition to well established multiple-choice tasks,
Bernardo Magnini, Roberto Zanoli, Michele Resta, Martin Cimmino, Paolo Albano, Marco Madeddu, Viviana Patti   +6 more
openaire   +3 more sources

Structural Divergence Between the Moltbook AI‐Agent Network and Human Social Networks

Advanced Science, EarlyView.
Analysis of the Moltbook AI‐agent network reveals a striking combination of familiar global scaling and distinct internal organization. Attention is highly concentrated, reciprocity is limited, connected triads are suppressed, and communities are strongly modular.
Wenpin Hou, Zhicheng Ji
wiley   +1 more source

Political-LLM: Large Language Models in Political Science

CoRR
In recent years, large language models (LLMs) have been widely adopted in political science tasks such as election prediction, sentiment analysis, policy impact assessment, and misinformation detection. Meanwhile, the need to systematically understand how LLMs can further revolutionize the field also becomes urgent.
Lincan Li, Jiaqi Li, Catherine Chen 0003, Fred Gui, Hongjia Yang, Chenxiao Yu, Zhengguang Wang, Jianing Cai, Junlong Aaron Zhou, Bolin Shen, Alex Qian, Weixin Chen, Zhongkai Xue, Lichao Sun 0001, Lifang He 0001, Hanjie Chen, Kaize Ding, Zijian Du, Fangzhou Mu, Jiaxin Pei, Jieyu Zhao 0001, Swabha Swayamdipta, Willie Neiswanger, Hua Wei 0001, Xiyang Hu, Shixiang Zhu, Tianlong Chen 0001, Yingzhou Lu, Yang Shi, Lianhui Qin, Tianfan Fu, Zhengzhong Tu, Yuzhe Yang 0005, Jaemin Yoo, Jiaheng Zhang, Ryan A. Rossi, Liang Zhan, Liang Zhao 0002, Emilio Ferrara, Yan Liu 0002, Furong Huang, Xiangliang Zhang 0001, Lawrence Rothenberg, Shuiwang Ji, Philip S. Yu, Yue Zhao 0016, Yushun Dong   +46 more
openaire   +3 more sources

Social opinions prediction utilizes fusing dynamics equation with LLM-based agents

Scientific Reports
In the context where social media emerges as a pivotal platform for social movements and shaping public opinion, accurately simulating and predicting the dynamics of user opinions is of significant importance.
Junchi Yao, Hongjie Zhang, Jie Ou, Dingyi Zuo, Zheng Yang, Zhicheng Dong   +5 more
doaj   +1 more source

Neuro-Symbolic Control with Large Language Models for Language-Guided Spatial Tasks

Science, Engineering and Technology
Although large language models (LLMs) have recently become effective tools for language-conditioned control in embodied systems, instability, slow convergence, and hallucinated actions continue to limit their direct application to continuous control.
Momina Liaqat Ali, Muhammad Abid, Muhammad Saqlain, Jose M. Merigo   +3 more
doaj   +1 more source

Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

REFLECTIONS FROM THE 2024 LARGE LANGUAGE MODEL (LLM) HACKATHON FOR APPLICATIONS IN MATERIALS SCIENCE AND CHEMISTRY Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry / George, Janine ...
Naik, Aakash, George, Janine, Ueltzen, Katharina   +2 more
core  

Towards a Compositional Framework for Describing Human Phenotypes

Advanced 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, Yunchao Ling, Xinyue Hu, Wei Chen, Rong Zhou, Xinhao Zhuang, Yanfeng Jiang, Jialu Zhao, Xingdong Chen, Jingchun Luo, Li Jin, Guoqing Zhang   +11 more
wiley   +1 more source