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Paper Citation Record · LEDGER

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

As of 20 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 2026-08-19T06:32:44.657259+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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:35:37.455607Z digest=sha256:eda100532060af28b4e2382e1db8ccabb0d80d06ecf33db4afab624e3f8315fb

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=sha256:75719062ee8a20588dc34c6a6b1843f9b51e822c828ec5c4521b3c59482e3725

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:f414f1842e3802db236e87c426f5c4b5942ce0be5970c32af988acefa685c38c

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:35:37.673120Z digest=sha256:6e9bcac24f3ccd3e22797090511bfcece61fcd05e37b19ae5de428ab8ae6b4ea

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=sha256:2e709a5cb1d62c6c16ed9def4817189fb36a70f8f8cb6aa9e91aaea6eb22f8d1

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:35:37.875800Z digest=sha256:35f7dab450b05850c8e09c69b349ac2b218c5b96fda093e9713bde4ed1640a63

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:e781393f6bd90b875def6ff58310a9e0c59d943cbf78adc63dc9e65850ad71e7

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=sha256:3bd76b6c70ba90b64e0ace433b4ef13c1a2394c50968a47cd85a5e374e1a095f

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=sha256:28715099c6c9a49df6af98979c5fb35eb510dd108760150c74bc8dc2f5272106

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:35:38.279360Z digest=sha256:93b3b7fa0f95640ea7f33d92c21851d98619c81e1f77d7619c44db332d6adb73

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=sha256:9fd28e0a42821002954dd7f02d7766b1d253dab1753541407c1635c45f0417a3

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:35:38.436692Z digest=sha256:a2b602c54604e4f43c23508383db97127515365b09a8445477b8ea04699b9452

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:e3ce491883ebe02587c6127a3851b908aab9c2391c444cd4409059d566ce1a17

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:bedbcf176e63eff890e5e087a58f21e127e58be9a9379acbc230de53dd715d16

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=sha256:7a49390195e1d3281fb965b79856a1ffdeb5a49f4c796e96bfd66f8f2bae3f96

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=sha256:45cf3efd6abb1ed1c72d65388c69a8d9f758828293bc27ee5bbd69e5bb832681

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:ef98a2e4ddad0cf662511b5ffc5f59bddfe5fd72eee17d14c81e840055b5109e

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:c7c3ef3c0972b32de9fb747f53b9543cc55102c45786b9aff70e3f1cbbd90d4a

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=sha256:69767f5c0728373d2ecfed95a3b090c2fc66430930cdf887ff7052e667e562fe

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:35:39.323709Z digest=sha256:3a2142079b21be238201879123e4abd9bd7a7d4203107474c9186bbd419c0fd2

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:aaad267eb2b5048b2547aff4c579d3f790bfc33a67b3f0cf62e61fdf33ce4218

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:f9254504ea43898d489f4abb9a24c5510bf937a4d4f7cee84d59a4898f6b5683

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:35:39.418523Z digest=sha256:ad08cf23f5e0875981689a0b08abb8e7d99acb466c82449592b1c1ca037d1270

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:35:39.784713Z digest=sha256:48b65ed7724f0d13ef87433152323b2283dbf9ea82f2e466f5da0accce00f740

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=sha256:1efea74a84177a302c8654615071b0363502d6af000953050d33893ddd76b9ea

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:35:40.097964Z digest=sha256:88a0bdee2ecf5b2f7a13fc5f0447c8206c30143943a2b1f95a0fd97146b32114

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:e085149f9e1c7c329873bc7b9fc7ca79bb3caa130364bf311370c93491ee45f1

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:c2de082b9decd7a666b8b5508102e7444c2dafff3184bc91c5e2c588aea075de

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:35:40.560163Z digest=sha256:5107a13f64788e23fb13f605c094491b2ea074f8a3b76ff59e00d7696c57ac26

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:f21503e0d41bfedce618ca621c6fd261f7625895985fdaa21c30200540757fe4

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:35:41.094773Z digest=sha256:85658a3f868c12eb77df5c373a151498b242efa1e74cf1823b4a1ba58135a97c

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T12:35:40.428359Z digest=sha256:8f487071dabc38aa25d11e88459f5b36d5f11269b46a78512a7b0eba90f621fd

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:aef08076c4a02ab7c76443d2f998f95b435fbc5a413d2a194c579e027c23ca97

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=sha256:702b080a0c9f7fad90ac16bedb54f147215cc997cbe7f5a17d7d035036ab45b1

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=sha256:177837eca744485cded2a7c3d7d7dc840e56d3f3db6e7875442332e8fbf46b7e

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:b3456b698fe12d2ff06b41b6d2c0ff904a4fcbea7ca7319e27a8e8552a3d8be0

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=sha256:0b0f698b8436d393f00f429ce964af4cf5604002b338bbc410e273fc114484a1

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-07-01T08:35:09.009897Z digest=sha256:7f878900e44f2403df92688594eea7d84d2da6f13dd6d157ec181fec41c1e568