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

Observation 67450f68-1f96-4a49-925c-b9073b461709 · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.450924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.536209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8253f64-8d57-49e1-92ee-2188bdec2c6d · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.428781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9a992c20-3376-4f07-87ea-b2ba6a79bb66 · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.418130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 622fffec-8ae7-4067-9b6b-5e805d3883ab · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.406672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.396284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.555043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e70079c-126d-47db-b1c1-8f85ca2b04db · outbound

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.558824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f42da09b-23e5-47e6-8abe-0b22d89e867e · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.379102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 62305d82-21a2-4228-8885-dc03ca438c6a · outbound

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

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T05:37:40.368679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.358212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.347125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3301bc9e-e117-432d-b8c4-f6c13430b570 · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.336562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a6dc7f55-030c-4e37-bfe9-728d26edf73c · outbound

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.583185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69876a0f-3918-426a-a459-c4cc6281b78c · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.325891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3dcb7c27-9025-4dc9-b59a-d108a233b18f · outbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.596526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7926b85-3994-465a-8855-5a695156ca96 · outbound

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

Resolution: verified exact; local_arxiv, observed 2026-08-12T05:37:39.930295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

Resolution: verified exact; doi, observed 2026-08-12T05:37:39.751530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.608467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c0aacaf-fb4e-4058-918b-ba9bf8d1b950 · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.303971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9dd7a354-4ecb-40ad-9fec-d592cb3f390b · outbound

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.615909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fbb0e90-0585-4858-adb9-8f9d4f70e1b8 · outbound

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.619720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.623364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5005a44-1c14-409e-8c42-5bd43b2c0029 · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.292869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4cd8d8d1-eaae-43df-a9a7-46cedfbab349 · outbound

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

Resolution: malformed identifier; no resolver link, observed 2026-08-12T05:37:39.630405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d335f85a-008e-4e0d-b1e0-80b6bd605a96 · outbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e6d1dfa5-a3aa-44a0-9e44-aae64a4fb940 · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.271363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 877fa5f8-f68e-4fc4-9f04-c1e7aab3633b · outbound

This paper cites Gamma, R.

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

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.641096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1dcf28fa-5d24-40de-bdba-e645b668d6f6 · outbound

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

Resolution: verified exact; local_arxiv, observed 2026-08-12T05:37:39.810190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b8d9ee88-9dac-4f31-b71f-935418110fa2 · outbound

This paper cites A jailbroken genai model can cause substantial harm: Genai-powered applications are vulnerable to promptwares,.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.253859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9c6192d0-fec8-40e5-a268-7a50011c2efe · outbound

This paper cites The Dark Side of Function Calling: Pathways to Jailbreaking Large Language Models.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.652530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8baf7184-a44d-4d92-bd89-aff9a1157397 · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.242319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a6817d2a-c4db-4742-8732-cbc7684575c7 · outbound

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.660207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 891d92ce-2cfa-4d86-8243-2a7ea967cf9f · outbound

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.664617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6894d1b0-e7af-48a1-8ec7-bba43c9202cb · outbound

This paper cites Toolformer: language models can teach themselves to use tools,.

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

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.230271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 21aa4954-ae28-4d18-9c56-e8a727660c7f · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.219096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8ebac195-1674-401c-8b10-a0fec1a77d79 · outbound

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.675576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72e1dfdb-5a09-444b-a987-d41d3209c96e · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.200793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8cde2b0e-368d-461a-bd56-999ca09800de · outbound

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.684437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3dacc7a-4c46-40c4-ba19-14c6edfdc2c5 · outbound

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.688496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55a9698d-b9e2-4054-a28f-b8a184b26f31 · outbound

This paper cites G-eval: NLG evaluation using gpt-4 with better human alignment,.

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

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.692058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31a33b3a-2159-4c2e-bf72-ad4e01efaab9 · outbound

This paper cites Simple fast algorithms for the editing distance between trees and related problems,.

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.695361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 046e2736-a07d-46d5-9d1b-c229b49006a0 · outbound

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

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:39.699662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6e47542-6457-4c8e-88ea-6af4aa69bcfe · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.176530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dc285a63-8a38-4ba9-bc40-eb5bd1dde7c4 · outbound

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

Resolution: malformed identifier; no resolver link, observed 2026-08-12T05:37:39.575910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54d8ab2a-71ad-4f7b-81ad-814157a0ab3c · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:37:40.439678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers