Results 101 to 110 of about 273,176 (296)
Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents
Advanced Intelligent Discovery, EarlyView.This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer +3 more
wiley +1 more source
Propuesta de explotación de un corpus electrónico ad hoc en la clase de traducción especializada
Káñina, 2017 Tras comprobar una bajada drástica en la calidad de las traducciones de los alumnos que se enfrentaban por primera vez a la asignatura de Introducción a la traducción especializada, se decidió llevar a cabo un experimento con el objetivo de evaluar ...
Lucila María Pérez Fernández
doaj +1 more source
LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?
Advanced 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
A comparable corpus-based study on stylistic features in translated English tourism texts [PDF]
, 2017 2015-2016 > Academic research: refereed > Publication in refereed journalVersion of ...
Li, D, Tang, F
core
Corpus Distillation for Effective Fuzzing: A Comparative Evaluation
, 2019 Mutation-based fuzzing typically uses an initial set of non-crashing seed inputs (a corpus) from which to generate new inputs by mutation. A corpus of potential seeds will often contain thousands of similar inputs. This lack of diversity can lead to wasted fuzzing effort by exhaustive mutation from all available seeds.
Herrera, Adrian +7 more
openaire +2 more sources
Lexique(s) et corpus en perspective comparative. Présentation
Studia Romanica Posnaniensia, 2023 Lexique(s) et corpus en perspective comparative ...
Agnieszka Kaliska +2 more
openaire +1 more source
When Biology Meets Medicine: A Perspective on Foundation Models
Advanced 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
Compiling Specialised Comparable Corpora. Should we always trust (Semi-)automatic Compilation Tools?
Linguamática, 2016 Decisions at the outset of compiling a comparable corpus are of crucial importance for how the corpus is to be built and analysed later on. Several variables and external criteria are usually followed when building a corpus but little is been said ...
Hernani Costa +3 more
doaj
InformationThe goal of relation extraction is to recognize head and tail entities in a document and determine a relation between them. While a lot of progress was made in solving automated relation extraction in widely used languages such as English, the use of ...
Timotej Knez +2 more
doaj +1 more source
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
Advanced 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