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23 papers · ranked by Valyu relevance

01
AarXiv2019
When Deep Learning Met Code Search
José Cambronero, Hongyu Li, Seohyun Kim, Koushik Sen + 1 more
'Satish Chandra'] There have been multiple recent proposals on using deep neural networks for code search using natural language. Common across these proposals is the idea of embedding code and natural language queries into real vectors and then using vector distance to approximate semantic correlation between code and…
88relevance
02
AarXiv2019
A Literature Study of Embeddings on Source Code
Zimin Chen, Martin Monperrus
Natural language processing has improved tremendously after the success of word embedding techniques such as word2vec. Recently, the same idea has been applied on source code with encouraging results. In this survey, we aim to collect and discuss the usage of word embedding techniques on programs and source code. The…
88relevance
03
AarXiv2023
TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree transformation
Zixiang Xian, Rubing Huang, Dave Towey, Chunrong Fang + 1 more
—Artificial intelligence (AI) has revolutionized software engineering (SE) by enhancing software development efficiency. The advent of pre-trained models (PTMs) leveraging transfer learning has significantly advanced AI for SE. However, existing PTMs that operate on individual code tokens suffer from several…
87relevance
04
AarXiv2021
BERT2Code: Can Pretrained Language Models be Leveraged for Code Search?
Abdullah Al Ishtiaq, Masum Hasan, Md. Mahim Anjum Haque, Kazi Sajeed Mehrab + 4 more
'Kazi Sajeed Mehrab' 'Tanveer Muttaqueen' 'Tahmid Hasan' 'Anindya Iqbal' 'Rifat Shahriyar'] Millions of repetitive code snippets are submitted to code repositories every day. To search from these large codebases using simple natural language queries would allow programmers to ideate, prototype, and develop easier and…
83relevance
05
AarXiv2 Dec 2020
CRaDLe: Deep Code Retrieval Based on Semantic Dependency Learning.
Wenchao Gu, Zongjie Li, Cuiyun Gao, Chaozheng Wang + 3 more
'Zenglin Xu' 'Michael R. Lyu'] Code retrieval is a common practice for programmers to reuse existing code snippets in the opensource repositories. Given a user query (i.e., a natural language description), code retrieval aims at searching the most relevant ones from a set of code snippets. The main challenge of…
79relevance
06
PPubMed11 Jun 2024
Semantic aware-based instruction embedding for binary code similarity detection Binary code similarity detection
Yuhao Jia, Zhicheng Yu, Zhen Hong, Asadullah Shaikh
Binary code similarity detection plays a crucial role in various applications within binary security, including vulnerability detection, malicious software analysis, etc. However, existing methods suffer from limited differentiation in binary embedding representations across different compilation environments, lacking…
76relevance
07
BbioRxiv27 Jun 2025
codonGPT: Reinforcement learning on a generative language model optimizes RNA sequences under biological constraints
Binita Rajbanshi, Anuj Guruacharya
Emerging generative models for biology focus on DNA, non-coding RNA, or proteins, ignoring information hidden in mRNA. Additionally, in protein engineering and mRNA therapeutics the design of mRNA sequences is still a challenge, lacking a clear framework. Here, we introduce and rigorously evaluate two novel methods: a…
76relevance
08
AarXiv6 Sep 2020
Self-Supervised Learning for Code Retrieval and Summarization through Semantic-Preserving Program Transformations
Nghi D. Q. Bui, Yijun Yu, Lingxiao Jiang
We propose Corder, a self-supervised contrastive learning framework for source code model. Corder is designed to alleviate the need of labeled data for code retrieval and code summarization tasks. The pre-trained model of Corder can be used in two ways: (1) it can produce vector representation of code which can be…
74relevance
09
PPubMed21 Mar 2025
CaLMPhosKAN: prediction of general phosphorylation sites in proteins via fusion of codon aware embeddings with amino acid aware embeddings and wavelet-based Kolmogorov–Arnold network
Pawel Pratyush, Callen Carrier, Suresh Pokharel, Hamid D Ismail + 3 more
The highly degenerate nature of codons leads to a surjective mapping from multiple codons to a single amino acid, with most amino acids being encoded by up to six different codons (see [btaf124-F1]). This indicates that a sequence represented at the codon level might contain as much, if not more, information than the…
73relevance
10
BbioRxiv15 Aug 2019
Using indication embeddings to represent patient health for drug safety studies
Rachel D. Melamed
The electronic health record is a rising resource for quantifying medical practice and discovering adverse effects of drugs. One of the challenges of applying these methods to health care data is the high dimensionality of the health record. Methods to discover effects of drugs in health data must account for tens of…
73relevance
11
PPubMed20 Nov 2024
Stylometry for real-world expert coders: a zero-shot approach
Andrea Gurioli, Maurizio Gabbrielli, Stefano Zacchiroli, Stefan Wagner
'Stefan Wagner'] Code stylometry is the application of stylometry techniques to determine the authorship of software source code snippets. It is used in the industry to address use cases like plagiarism detection, code audits, and code review assignments. Most works in the code stylometry literature use machine…
72relevance
12
PPubMed29 Apr 2022
Improving medical term embeddings using UMLS Metathesaurus
Ashis Kumar Chanda, Tian Bai, Ziyu Yang, Slobodan Vucetic
Background Health providers create Electronic Health Records (EHRs) to describe the conditions and procedures used to treat their patients. Medical notes entered by medical staff in the form of free text are a particularly insightful component of EHRs. There is a great interest in applying machine learning tools on…
71relevance
13
PPubMed12 Jan 2022
Comparison of different feature extraction methods for applicable automated ICD coding
Zhao Shuai, Diao Xiaolin, Yuan Jing, Huo Yanni + 3 more
'Wang Yuxin' 'Zhao Wei'] Background Automated ICD coding on medical texts via machine learning has been a hot topic. Related studies from medical field heavily relies on conventional bag-of-words (BoW) as the feature extraction method, and do not commonly use more complicated methods, such as word2vec (W2V) and large…
70relevance
14
PPubMed23 Jul 2019
Projection Word Embedding Model With Hybrid Sampling Training for Classifying ICD-10-CM Codes: Longitudinal Observational Study
Gunther Eysenbach, Yanshan Wang, David Mendes, Klerisson Paixao + 9 more
'Sujay Kakarmath' 'Chin Lin' 'Yu-Sheng Lou' 'Dung-Jang Tsai' 'Chia-Cheng Lee' 'Chia-Jung Hsu' 'Ding-Chung Wu' 'Mei-Chuen Wang' 'Wen-Hui Fang'] Background Most current state-of-the-art models for searching the International Classification of Diseases, Tenth Revision Clinical Modification (ICD-10-CM) codes use word…
70relevance
15
BbioRxiv3 Jul 2026
1 CodonBERT and ESM-2 Embedding Spaces Share an Evolutionarily Con-served Paired Geometry Encoding Synonymous Codon Information
Beiji Lu
Synonymous codons encode the same amino acid yet are used non-randomly across genomes, a phenomenon with well-documented functional consequences for translation efficiency and mRNA stability. Whether the information embedded in synonymous codon choice is recoverable from the internal representations of in-dependently…
66relevance
16
CchemRxiv15 Apr 2025
Comparative Analysis of Molecular Embeddings for Efficient Compound Similarity Search Using Vector Databases
Authors not listed
Compound similarity is fundamental to various cheminformatics analyses, particularly in the drug discovery industry, where the structure-activity principle is central to medicinal chemistry. Historically, binary fingerprints combined with Tanimoto and “Tanimoto-related metrics” (such as Dice, Sørensen–Dice, and…
64relevance
17
CchemRxiv10 Jan 2026
ConforFormer: representation for molecules through understanding of conformers
Authors not listed
Recent years have seen a growing interest in machine learning approaches for chemical tasks. The best existing methods focus on building base models that combine molecular graphs (“2D structures”) with atomic coordinates in 3D to predict molecular properties, typically through pre-training followed by fine-tuning on…
63relevance
18
PPubMed23 Jul 2022
Using word embeddings to investigate cultural biases Biases in word embeddings DURRHEIM et al.
Kevin Durrheim, Maria Schuld, Martin Mafunda, Sindisiwe Mazibuko
Word embeddings provide quantitative representations of word semantics and the associations between word meanings in text data, including in large repositories in media and social media archives. This article introduces social psychologists to word embedding research via a consideration of bias analysis, a topic of…
63relevance
19
CchemRxiv19 Jul 2024
"Amide - amine + alcohol = carboxylic acid." Chemical reactions as linear algebraic analogies in graph neural networks.
Amer El-Samman, Stijn De Baerdemacker
In deep learning methods, especially in the context of chemistry, there is an increasing urgency to uncover the hidden learning mechanisms often dubbed as ``black box." In this work, we show that graph models built on computational chemical data behave similar to natural language processing (NLP) models built on text…
61relevance
20
CchemRxiv2 Sep 2024
Developing Large Language Models for Quantum Chemistry Simulation Input Generation
Pieter Floris Jacobs, Robert Pollice
Scientists across domains are often challenged to master domain-specific languages (DSLs) for their research, which are merely a means to an end but are pervasive in fields like computational chemistry. Automated code generation promises to overcome this barrier, allowing researchers to focus on their core expertise.…
61relevance
21
CchemRxiv6 Nov 2024
Spectro: A multi-modal approach for molecule elucidation using IR and NMR data
Authors not listed
Molecular structure elucidation is a crucial but fundamentally challenging step in the characterization of materials given the large number of possible structures. Here, we introduce Spectro, an innovative multi-modal approach for molecular elucidation that combines $\CNMR$ and $\HNMR$ NMR data with IR. Spectro…
59relevance
22
BbioRxiv25 May 2020
Computer code comprehension shares neural resources with formal logical inference in the fronto-parietal network
Y. Liu, J. Kim, C. Wilson, M. Bedny
Despite the importance of programming to modern society, the cognitive and neural bases of code comprehension are largely unknown. Programming languages might ‘recycle’ neurocognitive mechanisms originally used for natural languages. Alternatively, comprehension of code could depend on fronto-parietal networks shared…
55relevance
23
CchemRxiv4 Oct 2024
From Clutter to Clarity: Emergent Neural Operators via Questionnaire Metrics
Authors not listed
Real-world datasets in chemical engineering and bioengineering processes--such as those from catalytic reactors, multiphase flows, polymerization reactors, bioreactors, and clinical trials--can often be unlabelled or disorganized, rendering the training of existing supervised learning models ineffective at learning the…
53relevance

Results for code embeddings

When Deep Learning Met Code Search

A Literature Study of Embeddings on Source Code

TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree transformation

BERT2Code: Can Pretrained Language Models be Leveraged for Code Search?

CRaDLe: Deep Code Retrieval Based on Semantic Dependency Learning.

Semantic aware-based instruction embedding for binary code similarity detection Binary code similarity detection

codonGPT: Reinforcement learning on a generative language model optimizes RNA sequences under biological constraints

Self-Supervised Learning for Code Retrieval and Summarization through Semantic-Preserving Program Transformations

CaLMPhosKAN: prediction of general phosphorylation sites in proteins via fusion of codon aware embeddings with amino acid aware embeddings and wavelet-based Kolmogorov–Arnold network

Using indication embeddings to represent patient health for drug safety studies

Stylometry for real-world expert coders: a zero-shot approach

Improving medical term embeddings using UMLS Metathesaurus

Comparison of different feature extraction methods for applicable automated ICD coding

Projection Word Embedding Model With Hybrid Sampling Training for Classifying ICD-10-CM Codes: Longitudinal Observational Study

1 CodonBERT and ESM-2 Embedding Spaces Share an Evolutionarily Con-served Paired Geometry Encoding Synonymous Codon Information

Comparative Analysis of Molecular Embeddings for Efficient Compound Similarity Search Using Vector Databases

ConforFormer: representation for molecules through understanding of conformers

Using word embeddings to investigate cultural biases Biases in word embeddings DURRHEIM et al.

"Amide - amine + alcohol = carboxylic acid." Chemical reactions as linear algebraic analogies in graph neural networks.

Developing Large Language Models for Quantum Chemistry Simulation Input Generation

Spectro: A multi-modal approach for molecule elucidation using IR and NMR data

Computer code comprehension shares neural resources with formal logical inference in the fronto-parietal network

From Clutter to Clarity: Emergent Neural Operators via Questionnaire Metrics

When Deep Learning Met Code Search

A Literature Study of Embeddings on Source Code

TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree transformation

BERT2Code: Can Pretrained Language Models be Leveraged for Code Search?

CRaDLe: Deep Code Retrieval Based on Semantic Dependency Learning.

Semantic aware-based instruction embedding for binary code similarity detection Binary code similarity detection

codonGPT: Reinforcement learning on a generative language model optimizes RNA sequences under biological constraints

Self-Supervised Learning for Code Retrieval and Summarization through Semantic-Preserving Program Transformations

CaLMPhosKAN: prediction of general phosphorylation sites in proteins via fusion of codon aware embeddings with amino acid aware embeddings and wavelet-based Kolmogorov–Arnold network

Using indication embeddings to represent patient health for drug safety studies

Stylometry for real-world expert coders: a zero-shot approach

Improving medical term embeddings using UMLS Metathesaurus

Comparison of different feature extraction methods for applicable automated ICD coding

Projection Word Embedding Model With Hybrid Sampling Training for Classifying ICD-10-CM Codes: Longitudinal Observational Study

1 CodonBERT and ESM-2 Embedding Spaces Share an Evolutionarily Con-served Paired Geometry Encoding Synonymous Codon Information

Comparative Analysis of Molecular Embeddings for Efficient Compound Similarity Search Using Vector Databases

ConforFormer: representation for molecules through understanding of conformers

Using word embeddings to investigate cultural biases Biases in word embeddings DURRHEIM et al.

"Amide - amine + alcohol = carboxylic acid." Chemical reactions as linear algebraic analogies in graph neural networks.

Developing Large Language Models for Quantum Chemistry Simulation Input Generation

Spectro: A multi-modal approach for molecule elucidation using IR and NMR data

Computer code comprehension shares neural resources with formal logical inference in the fronto-parietal network

From Clutter to Clarity: Emergent Neural Operators via Questionnaire Metrics