Paper Citation Record · LEDGER

Large Language Models in the Travel Domain: An Industrial Experience

As of 7 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2507.22910.

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

pith.paper-citation-record.v1
2507.22910 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:18:58.156820Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

31 of 31 outbound references displayed

verified exact2
verified fuzzy20
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e0c10781-28ed-4d1c-bb3c-745ebc056a1b · outbound

This paper cites Online search engines and online travel agencies: A comparative approach,.

Large Language Models in the Travel Domain: An Industrial Experience Online search engines and online travel agencies: A comparative approach,

Reference 1

Resolution: verified exact; doi, observed 2026-08-06T16:18:58.454258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 06034c56-32ad-4482-b2c7-989aa70fe3fc · outbound

This paper cites Performance testing in open-source web projects: Adoption, maintenance, and a change taxonomy,.

Large Language Models in the Travel Domain: An Industrial Experience Performance testing in open-source web projects: Adoption, maintenance, and a change taxonomy,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:05.938837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 71cc8d2e-4ef4-40bf-9797-66dda2b7a242 · outbound

This paper cites Evaluating performance and resource consumption of rest frameworks and execution environments: Insights and guidelines for developers and companies,.

Large Language Models in the Travel Domain: An Industrial Experience Evaluating performance and resource consumption of rest frameworks and execution environments: Insights and guidelines for developers and companies,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:05.500403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d06ef606-6d6c-45a4-b74f-2525cc72e0e2 · outbound

This paper cites Tourbert: A pretrained language model for the tourism industry,.

Large Language Models in the Travel Domain: An Industrial Experience Tourbert: A pretrained language model for the tourism industry,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:05.060465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9daca0fd-a2b0-4f53-af0f-0a8aebda7a39 · outbound

This paper cites Large language models in software engineering: A focus on issue report classification and user acceptance test generation,.

Large Language Models in the Travel Domain: An Industrial Experience Large language models in software engineering: A focus on issue report classification and user acceptance test generation,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:04.632839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c803a851-0c90-418a-a3ee-7e305529dc36 · outbound

This paper cites Can large language models automatically generate gis reports?.

Large Language Models in the Travel Domain: An Industrial Experience Can large language models automatically generate gis reports?

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:04.188630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f385848f-e737-46c2-8e5c-6c8d7cfed9b4 · outbound

This paper cites QLoRA: Efficient Finetuning of Quantized LLMs.

Large Language Models in the Travel Domain: An Industrial Experience QLoRA: Efficient Finetuning of Quantized LLMs

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T16:18:54.735362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bda3bb8c-1e5e-4270-a473-14f06e66fd24 · outbound

This paper cites Starting a new rest api project? a performance benchmark of frameworks and execution environments.

Large Language Models in the Travel Domain: An Industrial Experience Starting a new rest api project? a performance benchmark of frameworks and execution environments

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:03.833984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 94ada7fd-a75e-49bd-9791-9ea8a9b5df9d · outbound

This paper cites E2e-loader: A tool to generate performance tests from end-to-end gui-level tests,.

Large Language Models in the Travel Domain: An Industrial Experience E2e-loader: A tool to generate performance tests from end-to-end gui-level tests,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:03.510923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 39aea0bd-bf9c-40bc-b0ac-48ee6f2bbd19 · outbound

This paper cites Indicators of website features in the user experience of e-tourism search and metasearch engines,.

Large Language Models in the Travel Domain: An Industrial Experience Indicators of website features in the user experience of e-tourism search and metasearch engines,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:03.151089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 144cff2a-b4db-4412-bb14-0f94c0312f57 · outbound

This paper cites An empirical analysis of data preprocessing for machine learning-based software cost estimation,.

Large Language Models in the Travel Domain: An Industrial Experience An empirical analysis of data preprocessing for machine learning-based software cost estimation,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:02.823149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 347abb15-ec3e-474c-a6f6-25ca88487de2 · outbound

This paper cites What is data preprocessing in ml?.

Large Language Models in the Travel Domain: An Industrial Experience What is data preprocessing in ml?

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:02.502898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 351a9951-bf7c-426c-aab4-ed993f5e1a9f · outbound

This paper cites A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions,.

Large Language Models in the Travel Domain: An Industrial Experience A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:01.879863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1ac3e2a1-8017-4b78-8d2e-06781fc58641 · outbound

This paper cites A visual-based toolkit to support mobility data analytics,.

Large Language Models in the Travel Domain: An Industrial Experience A visual-based toolkit to support mobility data analytics,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:01.613118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation afd87a8b-a3de-4d8b-85eb-7a0d5a717a3a · outbound

This paper cites Fine-tuning Large Language Models for Adaptive Machine Translation.

Large Language Models in the Travel Domain: An Industrial Experience Fine-tuning Large Language Models for Adaptive Machine Translation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T16:18:56.005060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4697c339-7632-48e9-8e58-9e3373267719 · outbound

This paper cites Evaluating large language models: Chatgpt-4, mistral 8x7b, and google gemini benchmarked against mmlu,.

Large Language Models in the Travel Domain: An Industrial Experience Evaluating large language models: Chatgpt-4, mistral 8x7b, and google gemini benchmarked against mmlu,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:01.389488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fbfb410a-89fd-43f9-9488-034bdc267225 · outbound

This paper cites Open llm leaderboard v2,.

Large Language Models in the Travel Domain: An Industrial Experience Open llm leaderboard v2,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:01.146300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4c2cd3cd-9df6-41e7-b2bb-fbba8cb3b953 · outbound

This paper cites Mistral 7B.

Large Language Models in the Travel Domain: An Industrial Experience Mistral 7B

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T16:18:56.507226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c065b70-7c43-4837-8e5e-4b6e994a97df · outbound

This paper cites A Survey of Large Language Models.

Large Language Models in the Travel Domain: An Industrial Experience A Survey of Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T16:18:56.624232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e744844-bdeb-460d-9779-e06b6a30a26f · outbound

This paper cites Prompt engineering for generative ai,.

Large Language Models in the Travel Domain: An Industrial Experience Prompt engineering for generative ai,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:00.879125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3b654eda-f977-4901-a21f-bd2b4cb940fa · outbound

This paper cites Mixtral of Experts.

Large Language Models in the Travel Domain: An Industrial Experience Mixtral of Experts

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T16:18:56.918776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3d5fbaa-9f60-40f0-9513-6ecb1ef8d8d4 · outbound

This paper cites Accelerate: Training and inference at scale made simple, efficient and adaptable.

Large Language Models in the Travel Domain: An Industrial Experience Accelerate: Training and inference at scale made simple, efficient and adaptable

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T16:18:57.066251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b796a1bc-25f2-421f-83af-3d48e7790795 · outbound

This paper cites Tokenizer,.

Large Language Models in the Travel Domain: An Industrial Experience Tokenizer,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:00.564859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5bec4798-4dcd-4acd-8c1b-b1f45212b1a0 · outbound

This paper cites An exploratory study on how non-determinism in large language models affects log parsing,.

Large Language Models in the Travel Domain: An Industrial Experience An exploratory study on how non-determinism in large language models affects log parsing,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:00.209475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4ef6134c-8871-460c-a6c0-339b36c44190 · outbound

This paper cites FineSurE: Fine-grained Summarization Evaluation using LLMs.

Large Language Models in the Travel Domain: An Industrial Experience FineSurE: Fine-grained Summarization Evaluation using LLMs

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T16:18:57.521246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 527391cd-1fbb-4b5d-aab9-f2c2f77ef910 · outbound

This paper cites Unveiling LLM Evaluation Focused on Metrics: Challenges and Solutions.

Large Language Models in the Travel Domain: An Industrial Experience Unveiling LLM Evaluation Focused on Metrics: Challenges and Solutions

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T16:18:57.637514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a596fcab-944e-4744-a7c8-81db9032476a · outbound

This paper cites CTourLLM: Enhancing LLMs with Chinese Tourism Knowledge.

Large Language Models in the Travel Domain: An Industrial Experience CTourLLM: Enhancing LLMs with Chinese Tourism Knowledge

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:18:59.122512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 70aa17bd-e6a7-4bf7-9ec0-d2c65c09402c · outbound

This paper cites A fine-tuned tourism-specific generative ai concept,.

Large Language Models in the Travel Domain: An Industrial Experience A fine-tuned tourism-specific generative ai concept,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:18:59.856532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ab4d8be1-558b-4d19-84e5-6e9d079dd7ad · outbound

This paper cites Chatgpt and the hospitality and tourism industry: an overview of current trends and future research directions,.

Large Language Models in the Travel Domain: An Industrial Experience Chatgpt and the hospitality and tourism industry: an overview of current trends and future research directions,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:18:59.517216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6507c860-ddde-46da-945a-c272bc2efeec · outbound

This paper cites Ai-powered chatgpt in the hospitality and tourism industry: benefits, challenges, theoretical framework, propositions and future research directions,.

Large Language Models in the Travel Domain: An Industrial Experience Ai-powered chatgpt in the hospitality and tourism industry: benefits, challenges, theoretical framework, propositions and future research directions,

Reference 30

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T16:18:58.743297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a36cad5b-6f4d-4138-a0cd-14165784c04f · outbound

This paper cites Available: https://serokell.io/blog/data-preprocessing.

Large Language Models in the Travel Domain: An Industrial Experience Available: https://serokell.io/blog/data-preprocessing

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:19:02.135164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.