Generating a Low-code Complete Workflow via Task Decomposition and RAG | Paper Citation Record

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This paper cites On the opportunities and risks of foundation models,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG On the opportunities and risks of foundation models,

Reference 1

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Observation 4dd78202-aec5-4174-bc0f-372d67e52f14 · outbound

This paper cites Towards Uncovering How Large Language Model Works: An Explainability Perspective.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Towards Uncovering How Large Language Model Works: An Explainability Perspective

Reference 2

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This paper cites How does machine learning change software development practices?.

Generating a Low-code Complete Workflow via Task Decomposition and RAG How does machine learning change software development practices?

Reference 3

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This paper cites Design patterns for ai-based systems: A multivocal literature review and pattern repository,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Design patterns for ai-based systems: A multivocal literature review and pattern repository,

Reference 4

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This paper cites Architectural design decisions for the machine learning workflow,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Architectural design decisions for the machine learning workflow,

Reference 5

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Observation 9b76e7f2-b9d1-44a2-a297-b35595e043e4 · outbound

This paper cites A taxonomy of software engineering challenges for machine learning systems: An empirical investigation,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG A taxonomy of software engineering challenges for machine learning systems: An empirical investigation,

Reference 6

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Observation 69b0a164-7ada-458c-b306-dcc90a4301f0 · outbound

This paper cites Software engineering for machine learning: A case study,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Software engineering for machine learning: A case study,

Reference 7

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This paper cites A Survey on Large Language Models for Code Generation.

Generating a Low-code Complete Workflow via Task Decomposition and RAG A Survey on Large Language Models for Code Generation

Reference 8

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This paper cites Studying software engineering patterns for designing machine learning systems,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Studying software engineering patterns for designing machine learning systems,

Reference 9

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This paper cites Software engineering for ai-based systems: A survey,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Software engineering for ai-based systems: A survey,

Reference 10

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Observation 6c69ad4a-a8a2-4cae-9a3e-07f06cb81d41 · outbound

This paper cites Archi- tectural decisions in ai-based systems: An ontological view,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Archi- tectural decisions in ai-based systems: An ontological view,

Reference 11

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Observation 1daee827-ca6d-4867-99fd-6401eeb6a47e · outbound

This paper cites Adapting Software Architectures to Machine Learning Challenges ,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Adapting Software Architectures to Machine Learning Challenges ,

Reference 12

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This paper cites Architecture decisions in ai-based systems development: An empirical study,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Architecture decisions in ai-based systems development: An empirical study,

Reference 13

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This paper cites Rethinking software engineering in the era of foundation models: A curated catalogue of challenges in the development of trustworthy fmware,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Rethinking software engineering in the era of foundation models: A curated catalogue of challenges in the development of trustworthy fmware,

Reference 14

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This paper cites Requirements and reference architecture for mlops:insights from industry,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Requirements and reference architecture for mlops:insights from industry,

Reference 16

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This paper cites Iso/iec 25010:2023 systems and software engineering — systems and software quality requirements and evaluation (square) — product quality model,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Iso/iec 25010:2023 systems and software engineering — systems and software quality requirements and evaluation (square) — product quality model,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.314610Z

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Observation b421d270-05b4-46cc-a08e-5c86be50ae59 · outbound

This paper cites Speech-Copilot: Leveraging Large Language Models for Speech Processing via Task Decomposition, Modularization, and Program Generation.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Speech-Copilot: Leveraging Large Language Models for Speech Processing via Task Decomposition, Modularization, and Program Generation

Reference 18

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This paper cites Finding the Right Moment: Human-Assisted Trailer Creation via Task Composition.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Finding the Right Moment: Human-Assisted Trailer Creation via Task Composition

Reference 19

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Observation fd8eef1e-2aac-414d-bd71-2afc41a2ec4b · outbound

This paper cites Learning abstract visual reasoning via task decomposition: A case study in raven progressive matrices,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Learning abstract visual reasoning via task decomposition: A case study in raven progressive matrices,

Reference 20

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Observation 3d5e21e3-218b-4802-b6ec-926d950295c7 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 21

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This paper cites Reducing hallucination in structured outputs via retrieval-augmented generation,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Reducing hallucination in structured outputs via retrieval-augmented generation,

Reference 22

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This paper cites KnowledGPT: Enhancing Large Language Models with Retrieval and Storage Access on Knowledge Bases.

Generating a Low-code Complete Workflow via Task Decomposition and RAG KnowledGPT: Enhancing Large Language Models with Retrieval and Storage Access on Knowledge Bases

Reference 23

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This paper cites Search-in-the-Chain: Interactively Enhancing Large Language Models with Search for Knowledge-intensive Tasks.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Search-in-the-Chain: Interactively Enhancing Large Language Models with Search for Knowledge-intensive Tasks

Reference 24

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Observation 97de0060-b8b1-4c9c-81a9-507d43dfeac8 · outbound

This paper cites Guidelines for conducting and reporting case study research in software engineering,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Guidelines for conducting and reporting case study research in software engineering,

Reference 25

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This paper cites A taxon- omy of foundation model based systems through the lens of software architecture,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG A taxon- omy of foundation model based systems through the lens of software architecture,

Reference 26

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This paper cites Toward responsible ai in the era of generative ai: A reference architecture for designing foundation model-based systems,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Toward responsible ai in the era of generative ai: A reference architecture for designing foundation model-based systems,

Reference 27

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This paper cites RAFT: Adapting language model to domain specific RAG,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG RAFT: Adapting language model to domain specific RAG,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.281960Z

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This paper cites Low-code LLM: Graphical user interface over large language models,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Low-code LLM: Graphical user interface over large language models,

Reference 29

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This paper cites Gamma, R.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Gamma, R

Reference 30

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This paper cites TaskGen: A Task-Based, Memory-Infused Agentic Framework using StrictJSON.

Generating a Low-code Complete Workflow via Task Decomposition and RAG TaskGen: A Task-Based, Memory-Infused Agentic Framework using StrictJSON

Reference 31

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Generating a Low-code Complete Workflow via Task Decomposition and RAG A jailbroken genai model can cause substantial harm: Genai-powered applications are vulnerable to promptwares,

Reference 32

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Generating a Low-code Complete Workflow via Task Decomposition and RAG The Dark Side of Function Calling: Pathways to Jailbreaking Large Language Models

Reference 33

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This paper cites Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval,

Reference 34

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This paper cites Seven failure points when engineering a retrieval augmented generation system,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Seven failure points when engineering a retrieval augmented generation system,

Reference 35

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This paper cites JMLR: Joint Medical LLM and Retrieval Training for Enhancing Reasoning and Professional Question Answering Capability.

Generating a Low-code Complete Workflow via Task Decomposition and RAG JMLR: Joint Medical LLM and Retrieval Training for Enhancing Reasoning and Professional Question Answering Capability

Reference 36

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Generating a Low-code Complete Workflow via Task Decomposition and RAG Toolformer: language models can teach themselves to use tools,

Reference 37

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This paper cites Large dual encoders are generalizable retrievers,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Large dual encoders are generalizable retrievers,

Reference 38

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This paper cites Dimensionality reduction by learning an invariant mapping,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Dimensionality reduction by learning an invariant mapping,

Reference 39

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This paper cites SimCSE: Simple contrastive learning of sentence embeddings,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG SimCSE: Simple contrastive learning of sentence embeddings,

Reference 40

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This paper cites A learning algorithm for continually running fully recurrent neural networks,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG A learning algorithm for continually running fully recurrent neural networks,

Reference 41

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This paper cites The Challenges of Evaluating LLM Applications: An Analysis of Automated, Human, and LLM-Based Approaches.

Generating a Low-code Complete Workflow via Task Decomposition and RAG The Challenges of Evaluating LLM Applications: An Analysis of Automated, Human, and LLM-Based Approaches

Reference 42

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Generating a Low-code Complete Workflow via Task Decomposition and RAG G-eval: NLG evaluation using gpt-4 with better human alignment,

Reference 43

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Generating a Low-code Complete Workflow via Task Decomposition and RAG Simple fast algorithms for the editing distance between trees and related problems,

Reference 44

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This paper cites Quantifying the Capabilities of LLMs across Scale and Precision.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Quantifying the Capabilities of LLMs across Scale and Precision

Reference 45

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This paper cites Data labeling: An empirical investigation into industrial challenges and mit- igation strategies,.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Data labeling: An empirical investigation into industrial challenges and mit- igation strategies,

Reference 46

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This paper cites Available: https://doi.ieeecomputersociety.org/10.1109/ SANER53432.2022.00029.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Available: https://doi.ieeecomputersociety.org/10.1109/ SANER53432.2022.00029

Reference 163

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This paper cites Available: https://crfm.stanford.edu/assets/report.pdf.

Generating a Low-code Complete Workflow via Task Decomposition and RAG Available: https://crfm.stanford.edu/assets/report.pdf

Reference 2021

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