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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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:14.685705Z digest=sha256:7e9c1b6a1c76ad3d1be622848ddbb60a816a1c48f9e59440be3c7f2ae127a9b7

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:14.905313Z digest=sha256:7daf0c10f2ca94046cfbdd76557c5e8e1036758effb2fb7f335250565cdd17a6

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:14.984113Z digest=sha256:22ec50b1a668c3d9bc993fdd1645d971babaaa291c49d1f524ee2de1ec8934b0

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
verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:15.074494Z digest=sha256:f0acd7d3cf032c96b6904a0de4f08d5178e03ca2190f4a86e0dd1445b38b7587

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:15.176457Z digest=sha256:52a6d05201db328b47c34a45185d10b46eac790565d6a65f8f510265ee600681

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:15.357749Z digest=sha256:224535b348809b162652554d29998bd8ab7fad65e5e6624989d1b989b1aeef78

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
verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:15.472179Z digest=sha256:715e305604eab84eb31ea587a6ce5cd02d229441252f7423ff979aab5d650661

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:15.555062Z digest=sha256:51cf5493f381b151d9eb1a43826f72782b83ebff917b7a1c6afe652a08dc6a2a

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:15.627844Z digest=sha256:9e1201fb85658bf8c60f6b0f7c3603c29c153988669803d0ad80a23d923fbcd8

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
verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:15.722720Z digest=sha256:6e843ad8e2bc8514b9bb1532052631979d8ec700bef2d0ee9dc2d9ac16b35504

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:16.072906Z digest=sha256:46cb966ad7002887e2956c894207112f0c716784436b02d0bb5b82042d56e245

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:16.423559Z digest=sha256:a82560f3c112d8c52e77cd028f0416274a24a06be9d28303b98b917b7b021ad7

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:16.532394Z digest=sha256:e293f0c6d864f706450d409fb9a68674b1d622579dfc134a3b4f5e2bc5c9340c

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:16.641891Z digest=sha256:8cf85f285699f672bca5c0657887ddf20ec662f828c8afeea5e5d8302dcf9288

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:16.734685Z digest=sha256:7b0f5836c1e336a4969c1cb62f94a74253bc57bf1e7767be7a58ba17fe1af14f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:16.847452Z digest=sha256:5816a35c3f75df3df6a03b41385befcce421c9316ed5c129c7acb471f2534957

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
verified exact
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:16.940980Z digest=sha256:79d7b9301b30a266ccd801ff61e430b00abfa3c59f7eeb1d3151eaa80a22efee

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:17.217889Z digest=sha256:246bac191d6f7ab45b8fc69aa0e2be51a677acd9e10186398add76a4b846d7a8

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
verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:17.330367Z digest=sha256:98f49714a2051529f5fed619d41461d3d5971c5d36bc0a82f4e210741f997d3c

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:17.437482Z digest=sha256:beac16d64363d269e2781da82d99352daa7afc2c82a4a153810d859bcd3f7e29

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
verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:17.517106Z digest=sha256:ba294ed45021dad952ff10147696e9d3748598a6863c8974e60123ba407e2177

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
verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:17.600266Z digest=sha256:af3d277d206bee6af967435be156d5cbe55af54180a8f67cc64125ac047d095a

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

Resolution
verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:17.689139Z digest=sha256:9bd836fb2c8593f01efce7309d82bbc02def7855708024d619791cebccffed2d

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:17.800900Z digest=sha256:0ceba9e3e23ab5ff2cb430f83cd2dacb2385d2bedbb13fa23e8ea754e5299358

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
verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:17.909679Z digest=sha256:89e36e9e2266a92c4a1fdce5e4e2fb264c3e9cb82e1e5e03ffd1e4ecfeafe901

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:18.021644Z digest=sha256:a9429f7a96e541a9f3d9e4ae5f5e7223dd47519eed47f240648402234a06951e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:18.124911Z digest=sha256:f13cc7d21caca1af2a991e1ed883173d530de045ddec1dd3dd7e696a1bb9d2a4

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:14.793334Z digest=sha256:3773335a0471a55c5e8d113374922ca6750935540ddf6f15b105331764605f9d

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:40:16.187283Z digest=sha256:e9c224fc4848627f983470aa5c04b77ecc9c76d4f8efa9454583187dd6ec570a

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-04T08:26:06.951210Z digest=sha256:ef78baa5e85cffc9e12c4e8f8046747e3a55ac9a29b0f56ce7cd989226b3e22d