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Paper Citation Record · LEDGER

Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2502.10708.

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

pith.paper-citation-record.v1
2502.10708 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:55:13.053267Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T08:55:34.905780Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
  • unresolved0
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  • 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 bb69ad67-38b4-4c0e-ab5b-4bdd2da84213 · inbound

Shaping the Safety Boundaries: Understanding and Defending Against Jailbreaks in Large Language Models cites this paper.

Shaping the Safety Boundaries: Understanding and Defending Against Jailbreaks in Large Language Models Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-11T05:55:13.053267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:55:13.053267Z digest=sha256:69966455c18de63651599e611e81caa04fb99b12f052ee7d95b6bcedd719c8e8

Observation 40f7b71a-8b76-4081-b6b0-4035a0eb7e2e · inbound

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices cites this paper.

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 105

Resolution
verified exact
arxiv_id, observed 2026-05-23T01:05:16.236011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-23T01:03:26.037233Z digest=sha256:ecd2a8ac9cd880fe9f6f2c848ea3c0747769c567db9bcda54618d3d76d5e1a25

Observation 72687450-45bb-4fad-819c-71493aae0c64 · inbound

Audio Jailbreak: An Open Comprehensive Benchmark for Jailbreaking Large Audio-Language Models cites this paper.

Audio Jailbreak: An Open Comprehensive Benchmark for Jailbreaking Large Audio-Language Models Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T15:23:02.924153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:23:02.924153Z digest=sha256:fde4fcddc571df149cb9d20d6f4cf148c08a47470f336ea9225bfc778900194c

Observation 18cf9e13-2742-42c9-9a05-9ab24f2ecaab · inbound

Cross-Lingual Pitfalls: Automatic Probing Cross-Lingual Weakness of Multilingual Large Language Models cites this paper.

Cross-Lingual Pitfalls: Automatic Probing Cross-Lingual Weakness of Multilingual Large Language Models Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 2023

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unresolved
no resolver link, observed 2026-08-07T14:31:34.143825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:34.143825Z digest=sha256:c8fe9b3640c968bcd28d9e624a0bd9927cbfcfb17f6d67077a8f8af2bc8687c1

Observation 144b460c-365a-4c3b-9346-af7033c27931 · inbound

SocialMaze: A Benchmark for Evaluating Social Reasoning in Large Language Models cites this paper.

SocialMaze: A Benchmark for Evaluating Social Reasoning in Large Language Models Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T12:45:12.924587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:12.924587Z digest=sha256:1d57b2c4500bd5893b8f8fe569d9ce927c68691a6af16e1dff486e4b0f8c347a

Observation 9a1ee0da-0ed8-4edb-a4ac-6b193ac44ecb · inbound

Collaborative Editable Model cites this paper.

Collaborative Editable Model Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:12.949425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:12.949425Z digest=sha256:f255de436c365d1ae2798bb32347b7dc699b08e25cb839b786d587b035b8adf6

Observation b8a6369f-52d2-4c1d-93dd-00a13b8c7f6d · inbound

Seeing is Fixing: Cross-Modal Reasoning with Multimodal LLMs for Visual Software Issue Fixing cites this paper.

Seeing is Fixing: Cross-Modal Reasoning with Multimodal LLMs for Visual Software Issue Fixing Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T23:49:32.332793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:32.332793Z digest=sha256:609df2078158eb19cfd0ff3f9be01ea393b52f49f31f338be9d3d081b6c6ccb1

Observation dd80d6f0-6ab8-432c-942f-0714c5cabcde · inbound

BLOCKS: Blockchain-supported Cross-Silo Knowledge Sharing for Efficient LLM Services cites this paper.

BLOCKS: Blockchain-supported Cross-Silo Knowledge Sharing for Efficient LLM Services Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T22:40:38.180832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:40:38.180832Z digest=sha256:0e6645585eea91c9ed1432809912aee34c98d74e6dd4206d9c435dc3c084deca

Observation f9befa8c-1af5-4128-b840-69f88aeafb2f · inbound

RELRaE: LLM-Based Relationship Extraction, Labelling, Refinement, and Evaluation cites this paper.

RELRaE: LLM-Based Relationship Extraction, Labelling, Refinement, and Evaluation Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T20:05:22.078666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:05:22.078666Z digest=sha256:2a43df4827d2994da89e221af31b5e9c2f2881dec6fc547286bdd79541074dd8

Observation 601678b7-47f3-47dc-9f68-49b2d0449fc2 · inbound

Flipping Knowledge Distillation: Leveraging Small Models' Expertise to Enhance LLMs in Text Matching cites this paper.

Flipping Knowledge Distillation: Leveraging Small Models' Expertise to Enhance LLMs in Text Matching Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T19:29:08.727188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:29:08.727188Z digest=sha256:864962f360ef8db02d4f98ac5b1419cd72fd1b3e23edb075ece559e06a834f47

Observation def440c5-0b84-42d2-9ad3-35846673aa3d · inbound

Knowledge Conceptualization Impacts RAG Efficacy cites this paper.

Knowledge Conceptualization Impacts RAG Efficacy Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T18:01:20.307802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:01:20.307802Z digest=sha256:6d8cde7b55e68ba1fb75a2c1186e6c8156e5a26345cf4636790ea1044b290e77

Observation 8392c25d-76c2-415e-b8dc-732779528e0a · inbound

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

CEQuest: Benchmarking Large Language Models for Construction Estimation Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-05T17:35:53.280877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:35:53.280877Z digest=sha256:367dc3d1a5373a6442b3e79b6d155bc18220bb12c10d7f1971f1ac74c263fc7e

Observation bbdd4f3a-f142-4ead-a466-ae1f4859f75d · inbound

Gene-R1: Reasoning with Data-Augmented Lightweight LLMs for Gene Set Analysis cites this paper.

Gene-R1: Reasoning with Data-Augmented Lightweight LLMs for Gene Set Analysis Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-04T18:48:58.299011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T18:48:58.299011Z digest=sha256:ab104680b3955af9df7f7860f9e676e8de593c5d050b11d743a60944a9a7c735

Observation 361e2e8f-4445-4fea-9cd5-cd3f3ad08711 · inbound

G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledge cites this paper.

G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledge Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-18T13:26:25.018930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-18T13:23:30.218806Z digest=sha256:2dc56d85b5620390d9e88abc491a3f7a7aa45c6384dc8f1c78d74f8c3b0fd2bd

Observation 53e812b2-3912-4758-9bae-5a7c0218b105 · inbound

KnowPilot: Your Knowledge-Driven Copilot for Domain Tasks cites this paper.

KnowPilot: Your Knowledge-Driven Copilot for Domain Tasks Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T06:16:20.738560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-10T06:15:44.360621Z digest=sha256:d0bb082b989d89e9aa25e90bde22d97052175a616dfcdd04150a8096b773dc3a

Observation c02b3029-7b67-49ba-8ba4-35cb9453ce89 · inbound

TeleCom-Bench: How Far Are Large Language Models from Industrial Telecommunication Applications? cites this paper.

TeleCom-Bench: How Far Are Large Language Models from Industrial Telecommunication Applications? Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-20T11:28:14.647147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T11:23:34.256279Z digest=sha256:2b31c709d70e29c0e4565bd5b2a3af80dae9a95fa981f8f5edb1196b70e43ef6

Observation db881255-cc4f-49f5-9fb7-f7ecc85f321a · inbound

Less is More: Lightweight Prompt Compression for Question Answering Applications on Edge Devices cites this paper.

Less is More: Lightweight Prompt Compression for Question Answering Applications on Edge Devices Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-01T08:55:34.907283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T08:49:28.538659Z digest=sha256:46ec2a353e20768e4a68a3cc29335932bcea1a0994074cfad85221b86ff88c52

Observation 397eec3c-e6ea-4db7-ad12-e637502c36e8 · inbound

Global Logic and Local Search: Dual-Stream Multimodal In-Context Learning for Verifiable Industrial Anomaly Detection cites this paper.

Global Logic and Local Search: Dual-Stream Multimodal In-Context Learning for Verifiable Industrial Anomaly Detection Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 33

Resolution
unresolved
no resolver link, observed 2026-07-11T23:45:43.436443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T23:45:43.436443Z digest=sha256:0c39a4d8ad3d8af7531c0ddee659b437e06aa16e7003d7d6047bfec461a1f9a7

Observation e0f9f805-0ffc-4737-9139-e1434ced13db · inbound

Inside the Unfair Judge: A Mechanistic Interpretability Account of LLM-as-Judge Bias cites this paper.

Inside the Unfair Judge: A Mechanistic Interpretability Account of LLM-as-Judge Bias Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 187

Resolution
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no resolver link, observed 2026-07-14T02:33:34.084111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T02:33:34.084111Z digest=sha256:bc16175a4efebae389653ec06bfb64a02744dc92e796f356f95e125837b87c54

Observation a6017c3a-23d3-43f2-b275-bbeb92226ca0 · inbound

AdaptAgent: A Multi-agent, Domain-Guided Reasoning Framework for Code Adaptation cites this paper.

AdaptAgent: A Multi-agent, Domain-Guided Reasoning Framework for Code Adaptation Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T23:51:01.068941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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