Pith. sign in

Paper Citation Record · LEDGER

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows

As of 8 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2505.24189.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.24189 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:35:41.203682Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-01T08:35:09.009897Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-01T08:35:33.356509Z

Reference resolution

37 of 37 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved35
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ba2d45a9-4ec7-42e9-bba4-14d12e25f98c · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:35:44.430821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:35:37.455607Z digest=sha256:0b9d9b246ff2475c423f196bceec5cdec79374c5a885889bd2e824a554f8af7d

Observation 42bc32e2-d175-4656-9b5b-39a9cb2a2a58 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:37.504930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:37.504930Z digest=sha256:f30222d010197c81bd836b01cab2d58de1871f73c9f824f97cd142e663a01433

Observation c2e14a16-a46b-41d1-b68f-2a773e2a5e3e · outbound

This paper cites A Comparative Study of DSL Code Generation: Fine-Tuning vs. Optimized Retrieval Augmentation.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows A Comparative Study of DSL Code Generation: Fine-Tuning vs. Optimized Retrieval Augmentation

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:37.600795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:37.600795Z digest=sha256:089dacc9edeafe6da041b0f53069f6656c21878bac76659ccbba4ba084a17d51

Observation adefc349-54b2-457b-be3d-3d130c82a7bd · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:35:44.267091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:35:37.673120Z digest=sha256:12e86a5273672deb57f7930abaabb3f5b7973e78427ea6647076cf2422158cf5

Observation 64e4d296-24e4-4132-9ae4-6384efc634cf · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:37.756772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:37.756772Z digest=sha256:c21330fcd58974b01859ed55e7135e9f33f9a644dd395c5beba293899dbe5f25

Observation 8e9f3df8-d368-4066-88ec-81201e426251 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:35:44.079719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:35:37.875800Z digest=sha256:fb314b2297c1ddd7e3011bd61caed17e8381f2bfda083541d62d6ca02ab753c5

Observation 2d46eabd-331f-4cd3-b2d3-1b4cadffa48e · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:37.976050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:37.976050Z digest=sha256:2edcc160bb070e34bf72f9f068e59aa8f1949bee478e933d7a199bd9d3d40fd8

Observation 04881b05-875b-46b1-b652-0e3e14c25525 · outbound

This paper cites WorkflowLLM: Enhancing Workflow Orchestration Capability of Large Language Models.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows WorkflowLLM: Enhancing Workflow Orchestration Capability of Large Language Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:38.089411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:38.089411Z digest=sha256:42fb02b7acab989deb02b4c56944d770fe890ca8f74dd3e777df6e1e3c15412c

Observation 66627976-1742-42b7-ad21-b0c7600c57c0 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 9

Resolution
malformed identifier
no resolver link, observed 2026-08-07T12:35:38.173132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:38.173132Z digest=sha256:f95513c6fb2e5ef158f146a3179aee8193930009c7cabd4164bc57ce568d1ad8

Observation ac938a1b-0ef8-4123-a916-50ac517c107d · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:35:43.845904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:35:38.279360Z digest=sha256:20defd6de45be490752c2b166cb6474ba8b025e4995e474f22253bf87ed1f6f5

Observation c1e2b950-b8e1-49b9-9c9d-05e62463abb0 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:38.366550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:38.366550Z digest=sha256:7530838c52129d1c3f79d13b72bfe9b95015f795de21605dbb170ed68575728b

Observation 852bf42d-d77e-4f06-8cd6-b9914ff0452a · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:35:43.661488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:35:38.436692Z digest=sha256:7f444993b8e93493bac20fc0fb93f37ffa7f84451a4f9385da9b01c32d32bfee

Observation 6fbf444f-3f01-4b1f-887f-5f1e397d4984 · outbound

This paper cites The Llama 3 Herd of Models.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows The Llama 3 Herd of Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:38.676536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:38.676536Z digest=sha256:a9297faf2af70c013565c6cc57fe96537d83df6bb0bf2864550fd45656e1486e

Observation e9abd729-8e50-480f-9c58-56c3971b1358 · outbound

This paper cites Don't Stop Pretraining: Adapt Language Models to Domains and Tasks.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Don't Stop Pretraining: Adapt Language Models to Domains and Tasks

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:38.753446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:38.753446Z digest=sha256:55650fbbe6592db4a6747e5741ba4ee4dda1f3fd36bcb56faae64f7c2308993a

Observation 0e6344fc-d5f2-4bc6-968c-612874c76271 · outbound

This paper cites GPT-4o System Card.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows GPT-4o System Card

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:38.842074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:38.842074Z digest=sha256:f5bef48b7ae7d9966cb07d65d70032bc6c5f3856e98cce24ac356a00447bb967

Observation c62b6164-29aa-4039-ac79-623659b0d797 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:38.941668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:38.941668Z digest=sha256:e74093e9c2f516c79ea7f89abfdb375fffac90c0ef288fb6355534fb5fa30590

Observation 31adaea4-bd54-47a5-af60-0207707596e4 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:39.013836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:39.013836Z digest=sha256:ec60564e56aeb353098412c149c65f395d28dfc07669589b44c1a7ad8ec98243

Observation 6b5e9157-282e-42bf-807d-557b651387ab · outbound

This paper cites AutoFlow: Automated Workflow Generation for Large Language Model Agents.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows AutoFlow: Automated Workflow Generation for Large Language Model Agents

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:39.165268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:39.165268Z digest=sha256:57388e03b15f5476f24cf8d8825bfc43b27a920262dd47e76b63fef1cb1d4593

Observation a463c4a6-9614-445a-acb8-2acc423180a5 · outbound

This paper cites StarCoder: may the source be with you!.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows StarCoder: may the source be with you!

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:39.088955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:39.088955Z digest=sha256:0e022005468d7a0cd4c90b8b297427ef954e009d157ce04814d49fc8d63907a2

Observation 3d4f5f7b-d66c-4c65-8fc0-fd7f9cf4c80f · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:35:43.435499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:35:39.323709Z digest=sha256:7a52b19765d8d391ccdcd000629afe1965b91815ffa38b538908ed8bf1e26a0b

Observation 02387a1c-3708-4acd-980f-c1d8aa56affc · outbound

This paper cites The Natural Language Decathlon: Multitask Learning as Question Answering.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows The Natural Language Decathlon: Multitask Learning as Question Answering

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:39.244905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:39.244905Z digest=sha256:c636b65dc82cc297acfca5483e8bc335e281500a179d644f3ca056b7b2b75a0c

Observation df71b3aa-6c3e-413e-b2ca-d894d9def650 · outbound

This paper cites YaRN: Efficient Context Window Extension of Large Language Models.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows YaRN: Efficient Context Window Extension of Large Language Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:39.495723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:39.495723Z digest=sha256:4de73feb4722176ee3affc639c52588f2f7f47d5fb146c880a7b7a6547264532

Observation d98d5a24-3c01-4448-8458-2c96c6387a58 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:35:43.247227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:35:39.418523Z digest=sha256:50e6376a64364ef788500f49ed7a5b95e854b629a40611d47d3d54ecccaa9c06

Observation 409111bf-cc7c-42ee-93f2-031875f5a454 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 24

Resolution
verified exact
doi, observed 2026-08-07T12:35:41.516190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:35:39.784713Z digest=sha256:86e41678895a6048debf981cc9138c668f4120ff548fc45faeab6907450da820

Observation e8624581-d4be-49d0-877c-890e736b61e6 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:39.606640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:39.606640Z digest=sha256:5343a0d40049a40e4dd702b8f3f20ba8e70b71535d0121a2470e30794db949b9

Observation 973fcbe3-9216-4f47-9fc8-18885a58dd69 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:35:43.003778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:35:40.097964Z digest=sha256:d202c1d8a1053c0d16136342ccf436cac7b003f2e8ec0034dbff5448a8e8f09a

Observation 134cc8c3-7a2e-4b2b-81b7-74e3d76f4607 · outbound

This paper cites Finetuned Language Models Are Zero-Shot Learners.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Finetuned Language Models Are Zero-Shot Learners

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:40.253677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:40.253677Z digest=sha256:7ef109c4d5dce2c54cda7bb0947d5f454edf6740b321ff6c22e3d5999f5cbbb9

Observation b0592d54-b49e-4a3e-af26-28a6af22ffb2 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:39.885351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:39.885351Z digest=sha256:a301e51a51d35e0bad9cc5556ccf76ddb2f6bf8890aee7773db20465d4fb95c2

Observation 1d99fcab-de16-4d93-afcc-96f4b24137a1 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 29

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:35:42.555222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:35:40.560163Z digest=sha256:13f49965ac2a9a49eef1f29948c25bb01dd8ce6a2cd94ae234ca6f3731f926a2

Observation 79643f7e-0529-42d9-b2bb-84a86dbfca99 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:40.757261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:40.757261Z digest=sha256:c67361b425a00fa923fb5fa08e631684cf2d87c6f02aaa7c4809ae9bb7202f70

Observation 0ad1272d-e1df-4f60-94bd-cfd0f9d5fe8c · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:35:42.303736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:35:41.094773Z digest=sha256:54ef003510ab903f86815796abb027c549e0576eeee638d2e31c0d3efeeba412

Observation 579321c8-b3a9-49f0-8824-459ab533d2c2 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:35:42.804455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:35:40.428359Z digest=sha256:a886d45dc0499d1021c0e83f645986e4859bb02a8523a365c3d8566f5d075ef9

Observation 6ec605de-17de-4ada-b54a-c80acafc34ba · outbound

This paper cites BloombergGPT: A Large Language Model for Finance.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows BloombergGPT: A Large Language Model for Finance

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:40.932184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:40.932184Z digest=sha256:9fe9056146df0153a3fdb2ef25fef4dd902a72db6ce1d7da73683edb7db98aee

Observation 3eab3175-6f16-4714-8969-209d7297eca9 · outbound

This paper cites an unresolved cited work.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Unresolved cited work

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:41.203682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:41.203682Z digest=sha256:2fa25f96e9780b1ec0f8f17a19d345a9668c9fd42a1f655db29e68c6bf686f94

Observation 15cd467c-d591-4b75-84bd-e25e2c8f1855 · outbound

This paper cites Multitask Prompted Training Enables Zero-Shot Task Generalization.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Multitask Prompted Training Enables Zero-Shot Task Generalization

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:39.690333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:39.690333Z digest=sha256:411a537b502a8f9e4ec9a25dba8d66dc370f56ea9be900e128c9032a08ef0174

Observation 86adc3de-44d1-4ca6-ad52-2692e44155ab · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Gemini: A Family of Highly Capable Multimodal Models

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:38.569371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:38.569371Z digest=sha256:d016db4991414a931bc2571b476b9905d4bbc447f26b7efb94337e4df29c3f7e

Observation a355583f-8fcf-44c6-96cb-79faed3040a2 · outbound

This paper cites Nejm Ai 1, 3 (2024), AIoa2300138.

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows Nejm Ai 1, 3 (2024), AIoa2300138

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:39.950766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:35:39.950766Z digest=sha256:f685767c5c90ff141c6c711793099fa17b7be1c0569a7e42404cba9836092eea

Pith citing papers

Observation 4e1d13f3-a8a7-486b-a2db-447076b230a8 · inbound

Quantifying Prior Dominance in RAG Systems cites this paper.

Quantifying Prior Dominance in RAG Systems Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-01T08:35:33.358120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-07-01T08:35:09.009897Z digest=sha256:029d1d7e63e0ab199138b040cd3777045452a5bcb6252ae2923b341226a9df59