Paper Citation Record · LEDGER

Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2305.18703.

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

pith.paper-citation-record.v1
2305.18703 v7

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:35:52.568215Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:59:45.779105Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6c0485c1-5411-4a64-9d0c-7b3f975c48c3 · inbound

TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis cites this paper.

TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:45:47.251992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 184a05a6-ce39-4de3-a6d7-7ea86e36d090 · inbound

ToolRL: Reward is All Tool Learning Needs cites this paper.

ToolRL: Reward is All Tool Learning Needs Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T00:26:48.463020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 65a93e41-561f-4e21-995e-8228f4c1181d · inbound

CEQuest: Benchmarking Large Language Models for Construction Estimation cites this paper.

CEQuest: Benchmarking Large Language Models for Construction Estimation Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T17:35:52.568215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fb7fc6e-0058-4170-a58e-dcf0cac12872 · inbound

When LLM Meets Time Series: Can LLMs Perform Multi-Step Time Series Reasoning and Inference cites this paper.

When LLM Meets Time Series: Can LLMs Perform Multi-Step Time Series Reasoning and Inference Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 68

Resolution: malformed identifier; no resolver link, observed 2026-08-05T12:12:58.719845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd28b8a0-db7b-4b1d-b923-f16c791e68fa · inbound

Towards EnergyGPT: A Large Language Model Specialized for the Energy Sector cites this paper.

Towards EnergyGPT: A Large Language Model Specialized for the Energy Sector Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-18T17:42:47.468538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5149924f-fcd3-4197-8606-6ef63b4dee0f · inbound

Knowledge-Driven Hallucination in Large Language Models: An Empirical Study on Process Modeling cites this paper.

Knowledge-Driven Hallucination in Large Language Models: An Empirical Study on Process Modeling Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T15:36:34.369546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 824feac5-8824-41bc-9ce7-6584d481f8cb · inbound

Improving Topic Modeling of Social Media Short Texts with Rephrasing: A Case Study of COVID-19 Related Tweets cites this paper.

Improving Topic Modeling of Social Media Short Texts with Rephrasing: A Case Study of COVID-19 Related Tweets Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T08:57:43.925440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bd59a5a-5a19-47f5-a233-4515bb6ccb71 · inbound

Assessment of RAG and Fine-Tuning for Industrial Question-Answering-Applications cites this paper.

Assessment of RAG and Fine-Tuning for Industrial Question-Answering-Applications Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:41:23.763662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation cdd68f79-c6d1-4346-ac3e-a31e399a3836 · inbound

Predicate Importance Estimation and Decoupled Rationale-Score Distillation for Entity Alignment cites this paper.

Predicate Importance Estimation and Decoupled Rationale-Score Distillation for Entity Alignment Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 43

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T10:59:45.780655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2f89fae9-e503-478c-aa47-ee69987a6a6d · inbound

When AI Reviews Its Own Code: Recursive Self-Training Collapse in Code LLMs cites this paper.

When AI Reviews Its Own Code: Recursive Self-Training Collapse in Code LLMs Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 70

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T15:25:48.321490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.