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Paper Citation Record · LEDGER

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches

As of 9 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 2 inbound Pith citation observations for arXiv:2506.13171.

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

pith.paper-citation-record.v1
2506.13171 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:40:18.124911Z

measured 37 of 37 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:48:44.102637Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

35 of 35 outbound references displayed

  • verified exact4
  • verified fuzzy25
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation cde15dc7-afad-4ce9-bd68-da90421b794e · outbound

This paper cites Engineering automotive software,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Engineering automotive software,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:23.565015Z

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=2026-08-07T00:40:14.685705Z digest=sha256:555694e1d255b223d16bc452c2b14ab795031de72185d3d812873d590e9287c9

Observation c261f7ed-e03b-4019-8886-03c14e4da4c8 · outbound

This paper cites Automotive software engineering: A systematic mapping study,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Automotive software engineering: A systematic mapping study,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:23.412710Z

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=2026-08-07T00:40:14.905313Z digest=sha256:28555ef1e5fea107e1e40e2768f4a80f22605f34b06009fe801ebc0d5eabe676

Observation c763f503-2d4c-4b1d-adaf-39ea5b543ac2 · outbound

This paper cites Large language models for software engineering: Survey and open problems,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Large language models for software engineering: Survey and open problems,

Reference 3

Resolution
verified exact
raw_fallback, observed 2026-08-07T00:40:18.963286Z

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=2026-08-07T00:40:14.984113Z digest=sha256:df34a150d39d0f264dbfb5b1101cab4cf51ee2b33111b179b0e50893088f41da

Observation 95f4196b-6761-4f9d-a826-9baff32b5554 · outbound

This paper cites PlantUML.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches PlantUML

Reference 4

Resolution
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raw_fallback, observed 2026-08-07T00:40:23.281519Z

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=2026-08-07T00:40:15.074494Z digest=sha256:4f3616130ab59ddb8dbe7b802ff57354ee4cc959f0ec07f630db4e1353853b2b

Observation 4fff9cc1-6864-4462-b587-a623f88c8cd1 · outbound

This paper cites Limitations of ChatGPT in conceptual modeling: insights from experiments in metamodeling,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Limitations of ChatGPT in conceptual modeling: insights from experiments in metamodeling,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:23.152125Z

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=2026-08-07T00:40:15.176457Z digest=sha256:50caaed1f6be1a700dcfa6257e656f0dd9e03823faab34bb43fd1966cadd1c35

Observation 8b0e9c48-e397-442c-9b60-f64546ca5d5f · outbound

This paper cites On the use of large language models in model-driven engineering,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches On the use of large language models in model-driven engineering,

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:15.263092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:40:15.263092Z digest=sha256:50b51886e019a8597e80dd71ded485254ea4186f50062d8f1feeb3da46047ac6

Observation bec014e6-4b46-4444-a3de-0ec78d14a112 · outbound

This paper cites Unified Modeling Language (UML) Specification Version 2.5.1.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Unified Modeling Language (UML) Specification Version 2.5.1

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:23.026635Z

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=2026-08-07T00:40:15.357749Z digest=sha256:e3f2af74218ec3bb02525ab02132143d518c2c08e2d9ddfbd52cea9f29b1d283

Observation 9ca15034-d846-4eac-9f00-54461677ed60 · outbound

This paper cites Eclipse Modeling Framework (EMF).

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Eclipse Modeling Framework (EMF)

Reference 8

Resolution
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raw_fallback, observed 2026-08-07T00:40:22.896248Z

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=2026-08-07T00:40:15.472179Z digest=sha256:412b0d3dffdf8c3fc1eb83c100cffdde1052b2b7400573b0aa4897228d269ab5

Observation 21eaaa12-193d-4da7-bcd5-1debde96bc05 · outbound

This paper cites AUTOSAR (Automotive Open System Architecture).

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches AUTOSAR (Automotive Open System Architecture)

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:22.749363Z

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=2026-08-07T00:40:15.555062Z digest=sha256:b58403a73a09ce1b75411f433feddea923e21839ecdb615b93817bdf303c6008

Observation 30ce6583-b8c2-4484-95fd-09afa02f4228 · outbound

This paper cites Model-based automotive software development,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Model-based automotive software development,

Reference 10

Resolution
verified exact
doi, observed 2026-08-07T00:40:18.272763Z

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=2026-08-07T00:40:15.627844Z digest=sha256:a86648f57592419bf73718364e5786a7382a24498a26379b787ea069f38375d0

Observation 5b0945cb-0df7-4c63-a9cc-dadd25c913b6 · outbound

This paper cites Understanding the landscape of software modelling assistants for MDSE tools: A systematic mapping,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Understanding the landscape of software modelling assistants for MDSE tools: A systematic mapping,

Reference 11

Resolution
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raw_fallback, observed 2026-08-07T00:40:22.584562Z

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=2026-08-07T00:40:15.722720Z digest=sha256:38591ae3ea3479f3998dae518c44333f2376a641264c0eb8d098b6c375befa79

Observation ffe4bc7b-5f3f-48d7-bdb9-acb5ae9bd8c3 · outbound

This paper cites Table meets LLM: Can large language models understand structured table data? A benchmark and empirical study,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Table meets LLM: Can large language models understand structured table data? A benchmark and empirical study,

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:15.840986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:40:15.840986Z digest=sha256:c189c2bf5788122c34d044419d17833d62b23daf1fbe436c0ae02efe5717e18f

Observation 08c9a42c-ad50-4ccf-973b-580acef23638 · outbound

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

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:15.968249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:40:15.968249Z digest=sha256:5de93e88f27615e96c448dabf632eb16554dd88400ffb5def42191e9622ca9d6

Observation 2694eddc-5745-493b-9ca3-27444b05636a · outbound

This paper cites Cognitive architectures for language agents,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Cognitive architectures for language agents,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:22.417240Z

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=2026-08-07T00:40:16.072906Z digest=sha256:69f626be7db593dc66e1c29f9fa3843a45dd4f4586b1443509d60833d62e18ff

Observation c817a890-d9ca-4c47-bd18-629f1741ae41 · outbound

This paper cites ART: Automatic multi-step reasoning and tool-use for large language models.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches ART: Automatic multi-step reasoning and tool-use for large language models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:16.334501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:40:16.334501Z digest=sha256:eb3d5fc265d13855d46e839cf9af232e64db2eca007e91e201afd18abe64b4ec

Observation edb653ed-54d3-4286-aa21-b419e5d738f3 · outbound

This paper cites Model Context Protocol.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Model Context Protocol

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:22.261089Z

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=2026-08-07T00:40:16.423559Z digest=sha256:e3d1d116493da29804741d69224723fb7d1e40fbc54d858cb89f2a78a41240a3

Observation 6cc7447e-1985-4267-91a7-9db5562c7e86 · outbound

This paper cites Agent2Agent Protocol (A2A).

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Agent2Agent Protocol (A2A)

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:22.132241Z

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=2026-08-07T00:40:16.532394Z digest=sha256:681f9ceef44677c0466e1e3c55b12cf482f2824a05a23698a00e697e3ca57f44

Observation 50e7d20e-f3b8-40a8-84e6-7e769253f5cf · outbound

This paper cites Chain-of-Thought prompting elicits reasoning in large language models,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Chain-of-Thought prompting elicits reasoning in large language models,

Reference 18

Resolution
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raw_fallback, observed 2026-08-07T00:40:21.907607Z

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=2026-08-07T00:40:16.641891Z digest=sha256:6d3da7def0c87f35746d0b90babae14038d09cdddf73c5a7773413a52b184253

Observation 1d2714b1-b034-4f20-abc8-6b8e4fe72400 · outbound

This paper cites Self-consistency improves chain of thought reasoning in language models,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Self-consistency improves chain of thought reasoning in language models,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:21.609770Z

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=2026-08-07T00:40:16.734685Z digest=sha256:f6439ecfbf674910a7a26c9c9f199256c6c8fe335aff42730c458995be48be18

Observation f8bae612-fd2c-42fd-a30f-a6947a4c3e02 · outbound

This paper cites Evaluating open-domain question answering in the era of large language models,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Evaluating open-domain question answering in the era of large language models,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:21.391733Z

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=2026-08-07T00:40:16.847452Z digest=sha256:ba3895b4c9c4f955bacd3a0106733eb8a6a53f714edac5baf28a56a71575d42c

Observation 16ce2b65-9fc1-43b3-9ab4-ace68cdd3794 · outbound

This paper cites Evaluation of Semantic Answer Similarity Metrics.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Evaluation of Semantic Answer Similarity Metrics

Reference 21

Resolution
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local_arxiv, observed 2026-08-07T00:40:18.636102Z

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=2026-08-07T00:40:16.940980Z digest=sha256:7dbe6887e4f9717ca340fa97f708f3ab9d210503f4c9e90ad783b2d0fd7eabc2

Observation 1a0d2f36-7f99-4b90-863c-425c93e235a5 · outbound

This paper cites Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering

Reference 22

Resolution
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no resolver link, observed 2026-08-07T00:40:17.022076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:40:17.022076Z digest=sha256:836599362f6c0d9a6b352b70974fc62167838ab785b9eaee3e3c56f7ee0fd857

Observation 995812b6-cf97-4c91-b984-1a49ffa1d9af · outbound

This paper cites Reference-guided verdict: LLMs-as- Judges in automatic evaluation of free-form text,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Reference-guided verdict: LLMs-as- Judges in automatic evaluation of free-form text,

Reference 23

Resolution
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no resolver link, observed 2026-08-07T00:40:17.111330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:40:17.111330Z digest=sha256:8ee60a6d166fe6c05af1b36f43fabfdfd968030268139f1f99a04f65a797a462

Observation c3553c49-5a9a-4a98-99a0-c80f86c2c141 · outbound

This paper cites Mermaid.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Mermaid

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:21.232888Z

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=2026-08-07T00:40:17.217889Z digest=sha256:00c8f43e03dc3cabd53253bb5993c4392c1311b1b381bb0ccbc4e1cffd4ef1c3

Observation ba4459fd-710b-44aa-8e9f-27919714f6fb · outbound

This paper cites ReAct: Synergizing reasoning and acting in language models,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches ReAct: Synergizing reasoning and acting in language models,

Reference 25

Resolution
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raw_fallback, observed 2026-08-07T00:40:21.099136Z

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=2026-08-07T00:40:17.330367Z digest=sha256:d0d2725d49a05a5e98e324188d9dd344cddc709435d904cad715a9ad58940449

Observation e96ab375-537b-4c33-bd33-72bb5b06823e · outbound

This paper cites SWE-agent: Agent-computer interfaces enable automated software engineering,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches SWE-agent: Agent-computer interfaces enable automated software engineering,

Reference 26

Resolution
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raw_fallback, observed 2026-08-07T00:40:20.933405Z

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=2026-08-07T00:40:17.437482Z digest=sha256:0f7b97feb1e22770f63b36f0d1aaf61e37a44641c2de8b515243207554dfcabe

Observation a2f46adf-038b-4913-b9fb-1f4df128301d · outbound

This paper cites INCHRON’s am2inc Ecore model.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches INCHRON’s am2inc Ecore model

Reference 27

Resolution
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raw_fallback, observed 2026-08-07T00:40:20.807172Z

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=2026-08-07T00:40:17.517106Z digest=sha256:1c03dd876043023b4429ccc0c74a06e69926daed2b0f32fe009d3fc6bfeb693e

Observation 91b5f639-edbc-4810-ab8e-a3099f1485cc · outbound

This paper cites Eclipse APP4MC.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Eclipse APP4MC

Reference 28

Resolution
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raw_fallback, observed 2026-08-07T00:40:20.720751Z

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=2026-08-07T00:40:17.600266Z digest=sha256:91a1fe89d9f88fe2d6389c8f754f1ea3df02a351b494378b92c9089319160d0b

Observation 082538c8-b140-4b02-a26d-f3d13443d509 · outbound

This paper cites chronSUITE from INCHRON.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches chronSUITE from INCHRON

Reference 29

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raw_fallback, observed 2026-08-07T00:40:20.559946Z

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=2026-08-07T00:40:17.689139Z digest=sha256:56c6e609a936aed89012402532930b39bfe036dfba511d94c774211ae24cf5d1

Observation f1c72ff5-a585-4672-a4b5-b42d1f00b4d3 · outbound

This paper cites INCHRON’s APP4MC / Amalthea Importer.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches INCHRON’s APP4MC / Amalthea Importer

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:20.249452Z

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=2026-08-07T00:40:17.800900Z digest=sha256:73ca10cdf9f6206cbf4d3a22b142887e2e17dc756b028f239791dd2b5dc6740e

Observation 97a22225-48fa-4661-be77-fb5b26e1e9cb · outbound

This paper cites Factuality of large language models: A survey,.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Factuality of large language models: A survey,

Reference 31

Resolution
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raw_fallback, observed 2026-08-07T00:40:19.959837Z

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=2026-08-07T00:40:17.909679Z digest=sha256:82eff5ae0c467c9ecc5d5a8a838205fba16bd7c933bca61b9029085c9fdc07b9

Observation 3717f797-c231-4050-8010-23c251e6a9ad · outbound

This paper cites LangSmith Hub Prompt: Evaluation for RAG answer accuracy vs a reference.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches LangSmith Hub Prompt: Evaluation for RAG answer accuracy vs a reference

Reference 32

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raw_fallback, observed 2026-08-07T00:40:19.661229Z

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=2026-08-07T00:40:18.021644Z digest=sha256:34f7f057c557e0ab8530f954a9b50aac0c113f4d337b0c158510f1363ce7aba0

Observation 0037b909-c6bb-405d-a01b-ce901124f795 · outbound

This paper cites Available: https://docs.ragas.io/en/v0.2.15/.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Available: https://docs.ragas.io/en/v0.2.15/

Reference 33

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raw_fallback, observed 2026-08-07T00:40:19.462975Z

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=2026-08-07T00:40:18.124911Z digest=sha256:795cefc79f0b09e30b34a9695f4df0e95581335f93d5a1f483154565d5e5624c

Observation cba06c68-aaaa-419d-bc24-d802f6fc51d2 · outbound

This paper cites Available: https://ieeexplore.ieee.org/document/4142919.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Available: https://ieeexplore.ieee.org/document/4142919

Reference 2007

Resolution
verified exact
raw_fallback, observed 2026-08-07T00:40:19.179203Z

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=2026-08-07T00:40:14.793334Z digest=sha256:22e11613a3227853e0aa743b68e6fd955c7464d82ab83848548e152f2af56f64

Observation 5021d1b5-6085-4f80-9997-fe1c1a105f9b · outbound

This paper cites Available: https://openreview.net/forum?id=1i6ZCvflQJ.

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches Available: https://openreview.net/forum?id=1i6ZCvflQJ

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:22.349026Z

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=2026-08-07T00:40:16.187283Z digest=sha256:139b1c22be196c126a95b18f546b4dafcca485613bab4bf292c4f9634704b721

Pith citing papers

Observation 980c0941-1199-4641-9980-2f5c023f9b13 · inbound

Survey of GenAI for Automotive Software Development: From Requirements to Executable Code cites this paper.

Survey of GenAI for Automotive Software Development: From Requirements to Executable Code Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:44.102637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:44.102637Z digest=sha256:daee85f56bbc81d9c685db60f593326441de56bfa5628576d5de04f0bb6af1d7

Observation dafc0761-edef-4987-a7b6-0d0fa16a5e8d · inbound

Large Language Models for Fault Localization: An Empirical Study cites this paper.

Large Language Models for Fault Localization: An Empirical Study Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-04T08:28:24.869080Z

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=arxiv_source observed=2026-08-04T08:26:06.951210Z digest=sha256:e443e821743a8895bb004d4a3343b0a5b2ee7c245cc4411dc627966144abe6e5