Results 81 to 90 of about 2,336,780 (253)

Limitations of Foundation Models in Energy Materials Simulations: A Case Study in Polyanion Sodium Cathode Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen   +5 more
wiley   +1 more source

Linguistic and computational advantages of bidirectional bottom-up parsing with top-down predictions

open access: yes, 1997
This paper compares two parsing strategies: bidirectional bottom-up parsing with top-down predictions (BBP) and standard chart parsing. We demonstrate that BBP is superior to classical chart parsers from a linguistic and computational points of view. The
Amores Carredano, José Gabriel De   +1 more
core   +1 more source

Bottom-Up/Top-Down Image Parsing with Attribute Grammar [PDF]

open access: yes, 2005
This paper studies a simple attribute graph grammar as a generative image representation for image parsing in a Bayesian framework. This grammar has one class of primitives as its terminal nodes - 3D planar rectangles projected on images, and six ...
Han, F, Zhu, S C
core  

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

open access: yesAdvanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler   +7 more
wiley   +1 more source

Developments of high-throughput quantitative top-down proteomics

open access: yes, 2021
The LC-MS techniques are commonly used to analyze intact proteoforms for top-down proteomics. To deepen the coverage of the intact human proteome, multidimensional separations are often applied prior to the MS analysis.
Yu, Dahang
core  

The Interoperability Challenge in DFT Workflows Across Implementations

open access: yesAdvanced Intelligent Discovery, EarlyView.
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen   +13 more
wiley   +1 more source

Dependency parsing resources for French: Converting acquired lexical functional grammar F-Structure annotations and parsing F-Structures directly [PDF]

open access: yes, 2009
Recent years have seen considerable success in the generation of automatically obtained wide-coverage deep grammars for natural language processing, given reliable and large CFG-like treebanks.
Schluter, Natalie, van Genabith, Josef
core   +2 more sources

A new top-down parsing algorithm for left-recursive DCGs [PDF]

open access: yes, 1993
In this paper we introduce a new parsing algorithm, called cancellation parsing. Deterministic cancellation parsing with lookahead k can handle the C(k) grammars, which include the LL(k) grammars and are contained in the LC(k) grammars.
openaire   +2 more sources

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

open access: yesAdvanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto   +5 more
wiley   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

open access: yesAdvanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath   +4 more
wiley   +1 more source

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