Paper Citation Record · LEDGER

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

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 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 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T06:02:49.226289Z

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
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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 2026-08-22T06:32:14.747728+00:00.

Observation 4ccd94f2-71d0-40b4-9a6c-c400eed6ac19 · inbound

LP Data Pipeline: Lightweight, Purpose-driven Data Pipeline for Large Language Models cites this paper.

LP Data Pipeline: Lightweight, Purpose-driven Data Pipeline for Large Language Models Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-12T18:45:47.392578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a768fa4c-da8b-42c4-aeb1-15b30fea1a81 · inbound

KBAlign: Efficient Self Adaptation on Specific Knowledge Bases cites this paper.

KBAlign: Efficient Self Adaptation on Specific Knowledge Bases Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T14:59:24.149994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fd6b54d-a56b-4e35-8f36-205bd6f3cf0d · inbound

GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models cites this paper.

GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T20:37:54.102557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34cea7fb-7256-4fcf-b85d-18a88b041acd · inbound

Large Action Models: From Inception to Implementation cites this paper.

Large Action Models: From Inception to Implementation Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T16:29:56.755164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cc9bc4b-72a8-4f25-aaa2-9d2145491a4f · inbound

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs cites this paper.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.724468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5105474f-e8a6-483c-aee5-f50ed0c5cbf7 · inbound

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation cites this paper.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T12:01:21.978252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d76e108-f1c6-4a25-9ba1-67b0981618dc · inbound

SKETCH: Structured Knowledge Enhanced Text Comprehension for Holistic Retrieval cites this paper.

SKETCH: Structured Knowledge Enhanced Text Comprehension for Holistic Retrieval Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T11:28:33.016246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8872d27-abca-4f45-b4f8-ae9ff4c9e345 · inbound

TelcoLM: collecting data, adapting, and benchmarking language models for the telecommunication domain cites this paper.

TelcoLM: collecting data, adapting, and benchmarking language models for the telecommunication domain Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-11T11:04:15.963903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-22T06:32:14.747728+00:00.

Observation 9b8507f2-c867-46bb-9469-fb1311509b2e · inbound

Keep the General, Inject the Specific: Structured Dialogue Fine-Tuning for Knowledge Injection without Catastrophic Forgetting cites this paper.

Keep the General, Inject the Specific: Structured Dialogue Fine-Tuning for Knowledge Injection without Catastrophic Forgetting Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T06:02:49.226289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa04519e-da7a-4462-a4af-2deac9471502 · inbound

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components cites this paper.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T04:19:22.441506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7cf7c00-5dcc-4a0b-8325-727bebc11747 · inbound

QualBench: Benchmarking Chinese LLMs with Localized Professional Qualifications for Vertical Domain Evaluation cites this paper.

QualBench: Benchmarking Chinese LLMs with Localized Professional Qualifications for Vertical Domain Evaluation Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T23:13:24.541133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c74c7c6f-c939-48c0-bfdf-d2b153a3a739 · inbound

Climate-Eval: A Comprehensive Benchmark for NLP Tasks Related to Climate Change cites this paper.

Climate-Eval: A Comprehensive Benchmark for NLP Tasks Related to Climate Change Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:30:57.055435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07f22b50-38cd-4d74-b028-fedd73d7d9f0 · inbound

Toward Structured Knowledge Reasoning: Contrastive Retrieval-Augmented Generation on Experience cites this paper.

Toward Structured Knowledge Reasoning: Contrastive Retrieval-Augmented Generation on Experience Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:00.072917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68fe4451-1240-4366-9fb6-9dceedb520bf · inbound

Augmenting Large Language Models with Static Code Analysis for Automated Code Quality Improvements cites this paper.

Augmenting Large Language Models with Static Code Analysis for Automated Code Quality Improvements Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T04:35:42.242871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f4a9525-6f46-4271-b4d2-2ad548cdefbe · inbound

Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration cites this paper.

Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-06T21:16:14.827958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb67bebb-139d-4d2f-8ac2-c97d3d20b2a9 · inbound

LLMREI: Automating Requirements Elicitation Interviews with LLMs cites this paper.

LLMREI: Automating Requirements Elicitation Interviews with LLMs Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T20:29:37.603927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04d20d00-20b0-4354-9353-3fbaaef04056 · inbound

ReCatcher: Towards LLMs Regression Testing for Code Generation cites this paper.

ReCatcher: Towards LLMs Regression Testing for Code Generation Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-15T17:57:05.853006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+00:00.