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Paper Citation Record · LEDGER

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design

As of 8 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2507.16226.

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

pith.paper-citation-record.v1
2507.16226 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:18:33.226462Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

26 of 26 outbound references displayed

  • verified exact1
  • verified fuzzy13
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 38fe39e5-87c5-40bf-8a60-c00e38e2c130 · outbound

This paper cites Overview on signing and whitelisting for intel® software guard extensions (intel® sgx) enclaves,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Overview on signing and whitelisting for intel® software guard extensions (intel® sgx) enclaves,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:37.892637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:18:29.455944Z digest=sha256:a3f5e4785456582c3ccfffc4e0bce4e1c491d1566d05ce1969c26aa96ab18007

Observation 56bca6af-600b-465c-9789-522389a8acd6 · outbound

This paper cites Privacy-Preserving Inference in Machine Learning Services Using Trusted Execution Environments.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Privacy-Preserving Inference in Machine Learning Services Using Trusted Execution Environments

Reference 2

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verified exact
local_arxiv, observed 2026-08-06T15:18:33.989902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:18:29.577471Z digest=sha256:99f9866c73ebeb424904422ee95b462923e6874b423aa4317102764f7722e43a

Observation 4c90974c-f4e9-4ad9-a18f-f850be9adbf5 · outbound

This paper cites {SOTER}: Guarding black-box inference for general neural networks at the edge,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design {SOTER}: Guarding black-box inference for general neural networks at the edge,

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-06T15:18:37.664099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:18:29.646954Z digest=sha256:c02e81f03bb9e495b743d8e005e2f43233018a5577f50841d4f97fbe96f1dc91

Observation c0f80270-9edc-467c-9847-829faf49a82c · outbound

This paper cites Shad- ownet: A secure and efficient on-device model inference system for convolutional neural networks,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Shad- ownet: A secure and efficient on-device model inference system for convolutional neural networks,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-06T15:18:37.511282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:18:29.716753Z digest=sha256:78a30b49b5d8abaae7009aedea9bd7ec99f2a9beb46a4b0953afde5f937d2893

Observation c4cb6ffe-cee9-4fc7-b794-8d6e356ea60a · outbound

This paper cites Intel® trust domain extensions,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Intel® trust domain extensions,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-06T15:18:37.301055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:18:29.795507Z digest=sha256:71c1f93bcf91462b62632c0c07287db2b61e276e00edd3df625d4e2930b8425b

Observation 7878f728-7106-4c56-990e-58c55b281ffe · outbound

This paper cites Language Models are Few-Shot Learners.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Language Models are Few-Shot Learners

Reference 6

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unresolved
no resolver link, observed 2026-08-06T15:18:29.861202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:29.861202Z digest=sha256:9fe50d693607323e9197537eccb37a1f1429327fbc7de345b7e4a3cc791c452d

Observation e41ebf95-f6ec-41d3-8cec-eadbc390f311 · outbound

This paper cites Introducing gemini: Our most capable ai model,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Introducing gemini: Our most capable ai model,

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-06T15:18:37.121749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:18:29.957931Z digest=sha256:b6515d62c90ac6bd33384eb85d22b132b00b200596dc086e66cb9c37ce86e327

Observation 9f0f936d-5f9d-4590-8b5f-1faf9d33819e · outbound

This paper cites Understanding oversubscribed memory management for deep learning training,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Understanding oversubscribed memory management for deep learning training,

Reference 8

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unresolved
no resolver link, observed 2026-08-06T15:18:30.100236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:30.100236Z digest=sha256:ecc7d3a1a3dd9b5a3fe947e8abc13b5a2fbdf0c8dd98e5e5f5cc6fac93e8eddf

Observation 39edf039-1237-448c-9dfb-2f963898d2ef · outbound

This paper cites Llm4sechw: Leveraging domain-specific large language model for hardware debug- ging,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Llm4sechw: Leveraging domain-specific large language model for hardware debug- ging,

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T15:18:30.229333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:30.229333Z digest=sha256:b206d1a519b73359fcbe14cac46fb4bb03a0ed481554b716d7198c2a0e798ab1

Observation 9de40d77-faf0-47a7-9960-427e64357163 · outbound

This paper cites Socurellm: An llm-driven approach for large-scale system-on-chip security verification and policy generation,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Socurellm: An llm-driven approach for large-scale system-on-chip security verification and policy generation,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:36.863473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:18:30.437055Z digest=sha256:13addd4b85e82c04789375435d03e25e818894cd636b87fe9d0dbccc57849287

Observation 62bdaa85-f27c-4898-ae50-4be6b6ddbab9 · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T15:18:30.606838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:30.606838Z digest=sha256:9b3020c7d701002e0a307646b056b842c8ea38acc1e991b97475fcc62ef53c52

Observation a7f2e570-9cd1-4c70-991f-6cb7a909252f · outbound

This paper cites Evaluating the Performance of the DeepSeek Model in Confidential Computing Environment.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Evaluating the Performance of the DeepSeek Model in Confidential Computing Environment

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T15:18:30.753891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:30.753891Z digest=sha256:f6ed7b6d164ab003cab6e2900fa37f6d6d5587a00b735fe35caf0f57f5439c90

Observation 8b78001d-34f2-4163-81af-f98d8d449ef7 · outbound

This paper cites Amd memory encryption: Sev, sme, and sev-es,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Amd memory encryption: Sev, sme, and sev-es,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:36.559807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:18:30.959440Z digest=sha256:e2e27ee8870e926ba556c942ebf9cf3033bac4e495458a4ed5de016b59e9e55e

Observation 36715200-f50d-42db-bdc8-73ae07b54d0b · outbound

This paper cites Building a secure system using trustzone technology,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Building a secure system using trustzone technology,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:36.116743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:18:31.114548Z digest=sha256:17fd381acfdaf868576cd500f431df78d67eb13a4fec24bcfb1ebd610e87eff5

Observation bc893fd0-7d4f-4a99-b11d-bf318f8694dc · outbound

This paper cites Drgpum: Guiding memory optimization for gpu-accelerated applications,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Drgpum: Guiding memory optimization for gpu-accelerated applications,

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T15:18:31.465912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:31.465912Z digest=sha256:c7d35de4c31686b93eb1c2c682f754de14df3e89b33734273e8d4bd05a6deacc

Observation 721b3e9e-48cc-492d-b227-31bb7cbf5f9b · outbound

This paper cites Exploring parallel implemen- tation of sphincs+ using advanced vector extensions (avx) sets,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Exploring parallel implemen- tation of sphincs+ using advanced vector extensions (avx) sets,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:35.406566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:18:31.642475Z digest=sha256:2b5bf4c417ec4174a72f102f87573ab7ae287a485a786cf7d99040469a29ff11

Observation a655a722-cc93-4882-a2ba-e97cabebe391 · outbound

This paper cites Forest: Access-aware gpu uvm management,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Forest: Access-aware gpu uvm management,

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T15:18:31.789878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:31.789878Z digest=sha256:ea1efd34239129f697f533923e7b7fb3a0e74a886334014cd4c60c6b5237209c

Observation e4c26fad-3f22-42ff-bae9-868526e280bf · outbound

This paper cites Marvel: Multi-agent rtl vulnerability extraction using large language models,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Marvel: Multi-agent rtl vulnerability extraction using large language models,

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T15:18:31.951883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:31.951883Z digest=sha256:3671c107df875ee2169a1376d8a0dbbc66af0e99a107790dde22b79456d7b1ec

Observation ae678ca3-2e87-471e-9d3f-5e95a97c04b1 · outbound

This paper cites Spiced: Syntactical bug and trojan pattern identification in a/ms circuits using llm-enhanced detection,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Spiced: Syntactical bug and trojan pattern identification in a/ms circuits using llm-enhanced detection,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:35.106587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:18:32.123975Z digest=sha256:774e81383d05c3e1bc3b374bfe661c1b70a73d64f90da1b171f6414b32275aa0

Observation 22748f23-c89c-4c16-93ae-7d383587576e · outbound

This paper cites ThreatLens: LLM-guided Threat Modeling and Test Plan Generation for Hardware Security Verification.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design ThreatLens: LLM-guided Threat Modeling and Test Plan Generation for Hardware Security Verification

Reference 20

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unresolved
no resolver link, observed 2026-08-06T15:18:32.308082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:32.308082Z digest=sha256:f65807cc5d5cda9595c241cdab8aac8dc086f3f738589c20e86314cd1a4519d3

Observation 9cb330cc-8432-48f2-84b3-27be1ed27123 · outbound

This paper cites Is ChatGPT a General-Purpose Natural Language Processing Task Solver?.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Is ChatGPT a General-Purpose Natural Language Processing Task Solver?

Reference 21

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unresolved
no resolver link, observed 2026-08-06T15:18:32.454770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:32.454770Z digest=sha256:17cd38c2a0bc77d19ba64204ebb573908607c526e76efb4bd2934e013fc6ad03

Observation 19111194-d89d-4754-ad24-cd56f3781925 · outbound

This paper cites Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERT.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERT

Reference 22

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no resolver link, observed 2026-08-06T15:18:32.670079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:32.670079Z digest=sha256:fcb553cfec851d606f287f63bfe96c25bae5cd96e2c43f6b8800f9764013cd50

Observation 1b5ba101-d8cc-43c2-a9ff-0d02cc4c72df · outbound

This paper cites A Survey of Large Language Models.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design A Survey of Large Language Models

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T15:18:32.860151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:18:32.860151Z digest=sha256:bff3cdb0a9f61e5f8249af2ec1ccb67b381ef1ce9b625b2621db3939b32c4084

Observation dff96290-8dfa-493e-8663-7e667da419c8 · outbound

This paper cites A generalize hardware debugging approach for large language models semi-synthetic, datasets,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design A generalize hardware debugging approach for large language models semi-synthetic, datasets,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:34.715000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:18:33.007298Z digest=sha256:f6059539f4d88fc61cce17b7ddaa98e95e343d6dfec993ce701c3efa0b25d043

Observation 5b160add-63d5-4da3-a973-5a7436074378 · outbound

This paper cites The case for 4-bit precision: k- bit inference scaling laws,.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design The case for 4-bit precision: k- bit inference scaling laws,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:34.368103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:18:33.226462Z digest=sha256:2d399bf8f2b0cec0dd40b2f479e69a38391818d551077ed40a99c4bf89511d0b

Observation e03e6319-a7ed-4031-80e3-354adece1a1a · outbound

This paper cites Available: https://documentation-service.arm.com/static/ 5f212796500e883ab8e74531.

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design Available: https://documentation-service.arm.com/static/ 5f212796500e883ab8e74531

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:18:35.734803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:18:31.301136Z digest=sha256:8a0fddd299def697e3a75712383407504a32738c7e8c20a12ea26b6ad4e20de5

Pith citing papers

No inbound Pith citation observations are available.