Results 61 to 70 of about 250,329 (273)

Deep Semantics-Enhanced Neural Code Search

Electronics
Code search uses natural language queries to retrieve code snippets from a vast database, identifying those that are semantically similar to the query. This enables developers to reuse code and enhance software development efficiency. Most existing code search algorithms focus on capturing semantic and structural features by learning from both text and
Ying Yin, Longfei Ma, Yuqi Gong, Yucen Shi, Fazal Wahab, Yuhai Zhao   +5 more
openaire   +1 more source

PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science

Advanced Engineering Materials, EarlyView.
Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley   +1 more source

USING MACHINE LEARNING METHODS IN SOFTWARE CLONE DETECTION

Безопасность информационных технологий
The article is devoted to the analysis of methods for determining the similarity of software code fragments, particularly at the level of binary representations.
Nikita A. Gribkov, Denis V. Ivanov
doaj   +1 more source

BEDetector: A Two-Channel Encoding Method to Detect Vulnerabilities Based on Binary Similarity

IEEE Access, 2021
Applying neural network technology to binary similarity detection has become a promising search topic, and vulnerability detection is an important application field of binary similarity detection. When embedding binary code into matrix by neural network,
Lu Yu, Yuliang Lu, Yi Shen, Hui Huang, Kailong Zhu   +4 more
doaj   +1 more source

Semantic Search for NIC Codes

International Journal of Advanced Research in Science, Communication and Technology
Correct industry classification from textual business descriptions is important for regulatory enforcement, taxation, and policy decisions. Manual classification is time-consuming and leads to errors because of differences in terminologies and contexts. This work introduces a semantic search method utilizing BERT-based Natural Language Processing (NLP)
null Prof. Pritesh Patil, null Akash Varde, null Vijay Hissal, null Yash Inamdar   +3 more
openaire   +1 more source

CSRS

Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension, 2022
Developers often search and reuse existing code snippets in the process of software development. Code search aims to retrieve relevant code snippets from a codebase according to natural language queries entered by the developer. Up to now, researchers have already proposed information retrieval (IR) based methods and deep learning (DL) based methods ...
Cheng, Yi, Kuang, Li
openaire   +2 more sources

Mapping the Cerebral Organoid Landscape: A Systematic Review of Preclinical 3D Models in Neuroscience

Advanced Healthcare Materials, EarlyView.
Cerebral organoids are transforming brain research, yet the field remains fragmented. This comprehensive systematic review maps 738 studies published between 2014 and 2024 to uncover trends, gaps, and opportunities across neuroscience. Introducing OrganoidMap—an interactive, open‐access platform to explore and compare models—this work enables ...
Anna Wolfram, Vanessa Arnold, Maik Wolfram‐Schauerte, Anastassiya Moskalchuk, Caroline Trust, Marie Vontz, Mona Scheurenbrand, Vijayasarathy Sampath‐Kumar, Sogand Ahari, Carlos Romero‐Nieto, Lisa Sevenich   +10 more
wiley   +1 more source

Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback

Advanced Robotics Research, EarlyView.
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat, Ali Umut Kaypak, Prashanth Krishnamurthy, Ramesh Karri, Farshad Khorrami   +4 more
wiley   +1 more source

Deep Semantic Ranking Based Hashing for Multi-Label Image Retrieval

, 2015
With the rapid growth of web images, hashing has received increasing interests in large scale image retrieval. Research efforts have been devoted to learning compact binary codes that preserve semantic similarity based on labels.
Huang, Yongzhen, Tan, Tieniu, Wang, Liang, Zhao, Fang   +3 more
core   +1 more source

High‐Fidelity Synthetic Data Replicates Clinical Prediction Performance in a Million‐Patient Diabetes Cohort

Advanced Science, EarlyView.
This study generates high‐fidelity synthetic longitudinal records for a million‐patient diabetes cohort, successfully replicating clinical predictive performance. However, deeper analysis reveals algorithmic biases and trajectory inconsistencies that escape standard quality metrics. These findings challenge current validation norms, demonstrating why a
Francisco Ortuño, Víctor M. de la Oliva Roque, Javier‐Ignacio Ramirez‐Lopez, David P. Kreil, Joaquín Dopazo, Carlos Loucera   +5 more
wiley   +1 more source