Paper Citation Record · LEDGER

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language

As of 20 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2505.00989.

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

pith.paper-citation-record.v1
2505.00989 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:33:34.623815Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

verified exact0
verified fuzzy20
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 86888e5c-14cd-4019-9c7d-0b5a90ec291d · outbound

This paper cites Leveraging large language models for enhancing safety in maritime operations,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Leveraging large language models for enhancing safety in maritime operations,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:35.526956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b0b34ad0-1b66-418a-8b53-0f7013197a10 · outbound

This paper cites Popeye: A unified visual-language model for multi- source ship detection from remote sensing imagery,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Popeye: A unified visual-language model for multi- source ship detection from remote sensing imagery,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:35.462943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 74c4fd34-3895-42b9-8219-8b59db654d49 · outbound

This paper cites KUNPENG: An Embodied Large Model for Intelligent Maritime.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language KUNPENG: An Embodied Large Model for Intelligent Maritime

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T04:33:34.112436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 942cd9a3-e5e3-46cd-a64f-bd8755c11d86 · outbound

This paper cites Robust anomaly detection in unmanned ship systems based on large language models,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Robust anomaly detection in unmanned ship systems based on large language models,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:35.392073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6176e174-718d-47d8-9faf-91b079cb5767 · outbound

This paper cites Advancing its applications with llms: A survey on traffic manage- ment, transportation safety, and autonomous driving,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Advancing its applications with llms: A survey on traffic manage- ment, transportation safety, and autonomous driving,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:35.338696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 87b23bab-3e1d-4a4f-80c1-d4ef46cf83ff · outbound

This paper cites Research on the human-machine collaborative optimisation algorithm for intelligent traffic signal control systems,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Research on the human-machine collaborative optimisation algorithm for intelligent traffic signal control systems,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:35.326248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 54adf390-c05d-444b-ad12-ecc0191ab8bb · outbound

This paper cites Large lan- guage models (llms) as traffic control systems at urban intersections: A new paradigm,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Large lan- guage models (llms) as traffic control systems at urban intersections: A new paradigm,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:35.313832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5b2947e5-6698-45d0-9020-c8ec04e9294f · outbound

This paper cites Unist: A prompt-empowered universal model for urban spatio-temporal pre- diction,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Unist: A prompt-empowered universal model for urban spatio-temporal pre- diction,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:35.301877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1a3bc28e-a81b-4d1b-bfbf-57a32f91a17b · outbound

This paper cites Building transportation foundation model via generative graph transformer,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Building transportation foundation model via generative graph transformer,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:35.290240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6f6f4359-1e9e-44df-ba9d-9f9305e38019 · outbound

This paper cites Traffic Performance GPT (TP-GPT): Real-Time Data Informed Intelligent ChatBot for Transportation Surveillance and Management.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Traffic Performance GPT (TP-GPT): Real-Time Data Informed Intelligent ChatBot for Transportation Surveillance and Management

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T04:33:34.312186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a169fc56-c362-4cce-b2eb-9c2ebe89e038 · outbound

This paper cites Next-generation database interfaces: A survey of llm-based text-to-sql,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Next-generation database interfaces: A survey of llm-based text-to-sql,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T04:33:34.317452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cb0d648-f613-4ba8-8ef5-2c42931de57c · outbound

This paper cites Mac-sql: A multi-agent collaborative framework for text-to-sql,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Mac-sql: A multi-agent collaborative framework for text-to-sql,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:35.278395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 345ec0cd-022e-4f1a-b2c6-7b3936be648f · outbound

This paper cites Mcs-sql: Leveraging multiple prompts and multiple-choice selection for text-to-sql generation,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Mcs-sql: Leveraging multiple prompts and multiple-choice selection for text-to-sql generation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:35.167983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f7bc1393-37a1-4b62-be9c-9c7721eb4b55 · outbound

This paper cites Can llm already serve as a database interface? a big bench for large- scale database grounded text-to-sqls,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Can llm already serve as a database interface? a big bench for large- scale database grounded text-to-sqls,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:35.030560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 31eec2e7-e49a-4bf1-b125-8d67617410f5 · outbound

This paper cites Cllms: Consistency large language models,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Cllms: Consistency large language models,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:34.917384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 468cb5a9-27b2-432d-8072-09cddbe22f01 · outbound

This paper cites Codes: Towards building open-source language models for text-to- sql,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Codes: Towards building open-source language models for text-to- sql,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:34.906052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cd59bd4c-ac8f-4c39-b711-376fe8094f1e · outbound

This paper cites Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T04:33:34.390161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 534b9094-4921-4ed5-8f0b-ec78f2dd858a · outbound

This paper cites Spider: A large-scale human-labeled dataset for complex and cross- domain semantic parsing and text-to-sql task,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Spider: A large-scale human-labeled dataset for complex and cross- domain semantic parsing and text-to-sql task,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:34.894616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 606a9367-f4ae-4b70-af42-c0e2505bd57a · outbound

This paper cites Spider 2.0: Evaluating language models on real-world enterprise text-to-sql workflows,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Spider 2.0: Evaluating language models on real-world enterprise text-to-sql workflows,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:34.882396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 538a4705-e5e5-406b-b9d2-2dc6e5a381a9 · outbound

This paper cites Improving the domain adaptation of retrieval augmented generation (rag) models for open domain question answering,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Improving the domain adaptation of retrieval augmented generation (rag) models for open domain question answering,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:34.869697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation aae74cbc-55d5-4be0-b41f-eb2d399bcab2 · outbound

This paper cites An llm compiler for parallel function calling,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language An llm compiler for parallel function calling,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:34.858261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3effea4a-6682-4bd9-9845-b4992cfc3f50 · outbound

This paper cites Blendsql: A scalable dialect for unifying hybrid question answering in relational algebra,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Blendsql: A scalable dialect for unifying hybrid question answering in relational algebra,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:34.846439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c125741a-5c76-4d2f-8f34-21f12e5f3233 · outbound

This paper cites Rethinking the bounds of llm reasoning: Are multi-agent discussions the key?,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Rethinking the bounds of llm reasoning: Are multi-agent discussions the key?,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:34.835420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2b6b74cb-7e63-4ca4-91d6-c10413ba858d · outbound

This paper cites Semantic evaluation for text-to- sql with distilled test suites,.

VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language Semantic evaluation for text-to- sql with distilled test suites,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:33:34.823084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.