Results 61 to 70 of about 195,478 (295)

Eye-movements in implicit artificial grammar learning [PDF]

open access: yes, 2017
Artificial grammar learning (AGL) has been probed with forced-choice behavioral tests (active tests). Recent attempts to probe the outcomes of learning (implicitly acquired knowledge) with eye-movement responses (passive tests) have shown null results ...
Folia, Vasiliki   +3 more
core   +1 more source

Syntactic and Logophoric Anaphora Under the Perspective of Experimental Syntax

open access: yesEducation and Linguistics Research, 2023
In order to avoid repetition of noun phrases in a sentence the use of anaphora is present in most languages. In English, for example, Reinhart and Reuland (1993) pointed out that syntactic anaphora, besides natural, is guided by c-command (Chomsky, 1981) and related to syntactic factors, and logophoric anaphora is guided by extra-syntactic information.
Flávia G. Calaça de Souza   +2 more
openaire   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

open access: yesAdvanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu   +3 more
wiley   +1 more source

How Important is Syntactic Parsing Accuracy? An Empirical Evaluation on Rule-Based Sentiment Analysis

open access: yes, 2017
Syntactic parsing, the process of obtaining the internal structure of sentences in natural languages, is a crucial task for artificial intelligence applications that need to extract meaning from natural language text or speech.
Alonso-Alonso, Iago   +2 more
core   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

open access: yesAdvanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Stimulation of development of notion about syntax in pre-school children [PDF]

open access: yesZbornik Instituta za pedagoška istraživanja, 2009
This paper presents a part of the research the goal of which was to study the notion about syntax as one of the meta-linguistic abilities that contributes to adoption of reading. Research comprised two hundred children of pre-school age, divided into two
Nikolić Mirjana
doaj   +1 more source

Speed–Accuracy Trade-Off Modeling and Its Interface with Experimental Syntax

open access: yes, 2023
AbstractJudgements have been key to theory building in linguistics, yet judgements are inherently susceptible to a tradeoff between the speed and accuracy with which they are made. This chapter highlights insights gained by using the speed-accuracy tradeoff (SAT) technique to model this tradeoff.
Foraker, S., Cunnings, I., Martin, A.
openaire   +2 more sources

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

open access: yesAdvanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He   +2 more
wiley   +1 more source

The Vampire and the FOOL

open access: yes, 2015
This paper presents new features recently implemented in the theorem prover Vampire, namely support for first-order logic with a first class boolean sort (FOOL) and polymorphic arrays.
Barrett C.   +10 more
core   +2 more sources

OntoLogX: Ontology‐Guided Knowledge Graph Extraction From Cybersecurity Logs With Large Language Models

open access: yesAdvanced Intelligent Systems, EarlyView.
OntoLogX is an autonomous AI agent that uses large language models to transform unstructured cyber security logs into ontology grounded knowledge graphs. By integrating retrieval augmented generation, iterative correction, and a light‐weight log ontology, OntoLogX produces semantically consistent intelligence that links raw log events to MITRE ATT & CK
Luca Cotti   +4 more
wiley   +1 more source

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