Results 91 to 100 of about 6,924 (296)

From Label‐Free Multiphoton Imaging to Pathological Reports: A Vision‐Language Breast Cancer Margin Pathological Diagnosis System

open access: yesAdvanced Science, EarlyView.
MarginPath is a novel vision‐language system that automates breast cancer margin assessment using a single label‐free multiphoton microscopy image. By integrating tumor‐associated collagen signatures with virtual H&E imaging, it generates accurate margin heatmaps and comprehensive diagnostic reports.
Shu Wang   +15 more
wiley   +1 more source

The CoNLL 2007 shared task on dependency parsing

open access: yes, 2007
The Conference on Computational Natural Language Learning features a shared task, in which participants train and test their learning systems on the same data sets.
McDonald, Ryan   +6 more
core  

Evaluating evaluation measures [PDF]

open access: yes, 2007
This paper presents a thorough examination of the validity of three evaluation measures on parser output. We assess parser performance of an unlexicalised probabilistic parser trained on two German treebanks with different annotation schemes and evaluate
Rehbein, Ines, van Genabith, Josef
core  

Biaffine Dependency and Semantic Graph Parsing for EnhancedUniversal Dependencies

open access: yes, 2021
This paper presents the system used in our submission to the extit{IWPT 2021 Shared Task}. This year the official evaluation metrics was ELAS, therefore dependency parsing might have been avoided as well as other pipeline stages like POS tagging and ...
Maria Simi   +2 more
core   +1 more source

How Advanced Artificial Intelligence Technologies Shape Drug–Drug and Drug–Target Interaction Modeling

open access: yesAdvanced Science, EarlyView.
This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley   +1 more source

Resistant Peanut Genotype Reprograms Rhizosphere Metabolism to Enhance Bacterial Wilt Suppression

open access: yesAdvanced Science, EarlyView.
The resistant peanut genotype selectively recruits beneficial bacteria, which coincides with the activation of salicylic acid (SA)‐dependent systemic acquired resistance (SAR) against Ralstonia solanacearum. Keystone rhizosphere metabolites are positively correlated with both beneficial microbiome assembly and SAR gene expression.
Rui Ren   +20 more
wiley   +1 more source

Robust Dependency Parsing of Spontaneous Japanese Spoken Language [PDF]

open access: yes, 2005
Spontaneously spoken Japanese includes a lot of grammatically ill-formed linguistic phenomena such as fillers, hesitations, inversions, and so on, which do not appear in written language.
Ohno, Tomohiro   +3 more
core  

Enhanced Named Entity Recognition through Joint Dependency Parsing

open access: yes, 2023
Named entity recognition (NER) is the task of identifying and classifying named entities from texts. NER can benefit from linguistic dependency information, yet existing NER models can only utilize such information on datasets where dependency ...
Wang, Z   +4 more
core   +1 more source

Optimizing Dependency Parsing Throughput

open access: yesProceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 2015
Dependency parsing is considered a key technology for improving information extraction tasks. Research indicates that dependency parsers spend more than 95% of their total runtime on feature computations. Based on this insight, this paper investigates the potential of improving parsing throughput by designing feature representations which are optimized
Albert Weichselbraun, Norman Süsstrunk
openaire   +1 more source

Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design

open access: yesAdvanced Science, EarlyView.
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram   +4 more
wiley   +1 more source

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