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Paper Citation Record · LEDGER

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines

As of 14 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2607.22448.

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

pith.paper-citation-record.v1
2607.22448 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T04:48:29.517100Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

36 of 36 outbound references displayed

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External citation measurements

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Outbound references

Observation 1b66f1b4-8149-4222-9f5a-b0ea0b90ab38 · outbound

This paper cites Governance Decay: How Context Compaction Silently Erases Safety Constraints in Long-Horizon LLM Agents.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines Governance Decay: How Context Compaction Silently Erases Safety Constraints in Long-Horizon LLM Agents

Reference 3

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source=pdf_text observed=2026-08-01T04:48:24.447778Z digest=sha256:95571a0b9956fe75b66400761584ebd51d75aa230ae92027d08a09e09885bc9d

Observation d94b8a1d-452a-4467-9e86-eebb06849901 · outbound

This paper cites What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents

Reference 4

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source=pdf_text observed=2026-08-01T04:48:24.634586Z digest=sha256:46e25843f592672828bb997c683af545e9bc3614fd69a64d1f4e70ebdf4c2202

Observation 3695d2b6-c4c0-407c-85f7-31c54f826ee3 · outbound

This paper cites arXiv:2510.21118.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines arXiv:2510.21118

Reference 5

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source=pdf_text observed=2026-08-01T04:48:24.811629Z digest=sha256:a337a3061a97a5c0aed98c1bace3a3bbe09d214025b41a8cd706b17cea4990f4

Observation b6ef42b4-7c7a-4575-abd9-e85853e3f303 · outbound

This paper cites arXiv:2510.05381.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines arXiv:2510.05381

Reference 6

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source=pdf_text observed=2026-08-01T04:48:25.001400Z digest=sha256:973497b70c3cc3fca3036c880d686aca35b233f22694c603c6a8fc1a9e295708

Observation 15fffd33-73d3-4656-8fc1-4708bf4a229f · outbound

This paper cites Not All Needles Are Found: How Fact Distribution and Don't Make It Up Prompts Shape Retrieval, Reasoning, and Hallucination in Long-Context LLMs.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines Not All Needles Are Found: How Fact Distribution and Don't Make It Up Prompts Shape Retrieval, Reasoning, and Hallucination in Long-Context LLMs

Reference 7

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source=pdf_text observed=2026-08-01T04:48:25.173042Z digest=sha256:e781a8c4efbd8084c9ac572103ef97edbe72618e682f5cbeca7fa3eb576bd49b

Observation cd00f3b9-b00c-441c-b84a-193d9f70dca5 · outbound

This paper cites MCP-Zero: Active Tool Discovery for Autonomous LLM Agents.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines MCP-Zero: Active Tool Discovery for Autonomous LLM Agents

Reference 8

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source=pdf_text observed=2026-08-01T04:48:25.307321Z digest=sha256:67c8d24014387d7af058a59f2695f98849ddfe4e7f6aa727de4ac078ab8726bb

Observation a59e5056-6e47-427c-8fc1-752dc9c97b93 · outbound

This paper cites arXiv:2510.13334.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines arXiv:2510.13334

Reference 9

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source=pdf_text observed=2026-08-01T04:48:25.505950Z digest=sha256:1c65155876a90dbfcf842e6ffb2c428f26535581ab6d4daa75dec6f955c5eed6

Observation 160a5f3e-09e3-4697-85a8-f619824a3ba0 · outbound

This paper cites arXiv:2511.13900.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines arXiv:2511.13900

Reference 10

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source=pdf_text observed=2026-08-01T04:48:25.653273Z digest=sha256:1dc5f1ea0bf55dd865d6d5a4270cae7d53b937c1b7a1cf6058b70993a307e7fd

Observation 9083c6e8-9d14-4ffd-bc41-6af6a7bd09a9 · outbound

This paper cites arXiv:2512.02445.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines arXiv:2512.02445

Reference 11

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source=pdf_text observed=2026-08-01T04:48:25.798116Z digest=sha256:22b9eb65810959bb9aab7a39f1fcb3c98ec79882bff0dcad4f1e35a3bcfc5bd7

Observation 25e4e9b4-a835-4285-82e4-b6516ef55a2b · outbound

This paper cites RULER: What's the Real Context Size of Your Long-Context Language Models?.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines RULER: What's the Real Context Size of Your Long-Context Language Models?

Reference 13

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source=pdf_text observed=2026-08-01T04:48:26.098141Z digest=sha256:be72842e66fba4d90d12451316aa5659bb119a955f9462e4f8341af733f445e2

Observation 2e164274-7ba8-4922-b313-2fcb51727a87 · outbound

This paper cites From Context-Aware to Conflict-Aware: Generalizing Contrastive Decoding for Knowledge Conflict in LLMs.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines From Context-Aware to Conflict-Aware: Generalizing Contrastive Decoding for Knowledge Conflict in LLMs

Reference 14

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source=pdf_text observed=2026-08-01T04:48:26.279397Z digest=sha256:2da8f202c5d8a7689b8506f5f993da55784e508a71d5c33dd417bfffa2bb81c8

Observation 65b713a6-f248-4ac7-85fa-6ddcae79cfeb · outbound

This paper cites When Summaries Distort Decisions: Information Fidelity in LLM-Compressed Financial Analysis.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines When Summaries Distort Decisions: Information Fidelity in LLM-Compressed Financial Analysis

Reference 15

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source=pdf_text observed=2026-08-01T04:48:26.389644Z digest=sha256:4ab859088a8b62d44735d78e73871106bb3ae9fe05c6ed0921ad8db4d264e1c7

Observation 95b8362e-7bda-4fa3-97a6-70d21818ffdd · outbound

This paper cites Evaluating Quantized Large Language Models.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines Evaluating Quantized Large Language Models

Reference 16

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source=pdf_text observed=2026-08-01T04:48:26.573189Z digest=sha256:f85d38f473561717330f7c3a17a09c3cff75fa94cb8308140714c400601901ea

Observation 881ff980-e98d-4b97-a9c8-8046ec27c3da · outbound

This paper cites CompactionRL: Reinforcement Learning with Context Compaction for Long-Horizon Agents.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines CompactionRL: Reinforcement Learning with Context Compaction for Long-Horizon Agents

Reference 17

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source=pdf_text observed=2026-08-01T04:48:26.776852Z digest=sha256:6791303ac9f81d6f9fa6d41f2c267f03db13695c001fc8361f5b4f6d79c12621

Observation 25e91874-cdb6-4784-a869-841968aa6bdb · outbound

This paper cites Classifier Context Rot: Monitor Performance Degrades with Context Length.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines Classifier Context Rot: Monitor Performance Degrades with Context Length

Reference 19

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source=pdf_text observed=2026-08-01T04:48:27.161442Z digest=sha256:5a66f3187024112c16606d295552a3a56bfe5d8b2a620e248387c39a5e28bf43

Observation ea4ef6a8-e0dc-4dfc-80b3-f29819e5ee6c · outbound

This paper cites https://microsoft.github.io/mcscatblog/posts/mcp-resources-as- tool-inputs/.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines https://microsoft.github.io/mcscatblog/posts/mcp-resources-as- tool-inputs/

Reference 20

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source=pdf_text observed=2026-08-01T04:48:27.298708Z digest=sha256:69091939752653011610955a1902e120b10a3e2567773ed482e7b518e377e048

Observation 6be85427-c3b4-414b-8998-b3301b7383e5 · outbound

This paper cites NoLiMa: Long-Context Evaluation Beyond Literal Matching.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines NoLiMa: Long-Context Evaluation Beyond Literal Matching

Reference 21

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source=pdf_text observed=2026-08-01T04:48:27.492158Z digest=sha256:505ed85edc1eb7c5595782ca82877d23900503d85f40de067e1b1c1a5892a5d9

Observation 98846f99-646c-4c46-97f9-66746a2a34c8 · outbound

This paper cites https://www.morphllm.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines https://www.morphllm

Reference 22

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source=pdf_text observed=2026-08-01T04:48:27.620125Z digest=sha256:6473ae71af04ecc7787295672639f1a8f83e55fecaf12be8b202a9c0961e17b5

Observation 1d311557-1096-41fd-8937-d4c3141f5e63 · outbound

This paper cites KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks

Reference 23

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source=pdf_text observed=2026-08-01T04:48:27.791567Z digest=sha256:38a904744783bf395ea2247d5fc48c2f061595ce977ddc99da9c427329198124

Observation 89d86e0e-406a-4133-a194-6267475a057c · outbound

This paper cites arXiv:2512.21127.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines arXiv:2512.21127

Reference 24

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source=pdf_text observed=2026-08-01T04:48:27.952535Z digest=sha256:4212616fc0e2cd8356b7623faee2cd136ed8c26b401876447c6ce1058d05a56b

Observation 037dc381-7807-4f10-9ee1-de13c37c0736 · outbound

This paper cites A Taxonomy of Runtime Faults in Model Context Protocol Servers.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines A Taxonomy of Runtime Faults in Model Context Protocol Servers

Reference 25

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source=pdf_text observed=2026-08-01T04:48:28.114636Z digest=sha256:02cb937cc5032c824cc2d0867a5eb71f432a1ef1f1b038018269ce76286474b0

Observation 2529a630-a054-4aaf-a59f-34431d441fbb · outbound

This paper cites arXiv:2602.20040.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines arXiv:2602.20040

Reference 26

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source=pdf_text observed=2026-08-01T04:48:28.304162Z digest=sha256:840b989291be65cf0ddb2d547271d82014322f2ec7ce62bb670ce3d0b6dbf1f0

Observation 7ffb7d88-c2ea-4955-9b8a-27caba332538 · outbound

This paper cites FaithLens: Detecting and Explaining Faithfulness Hallucination.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines FaithLens: Detecting and Explaining Faithfulness Hallucination

Reference 28

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source=pdf_text observed=2026-08-01T04:48:28.553835Z digest=sha256:c3a3a2fc2e306639f93e3451f9f769c23a80c9f5c37f90c3ff63e1b33425215f

Observation c4a900fc-d70e-4171-8316-1db6c93abeaa · outbound

This paper cites ConflictBank: A Benchmark for Evaluating the Influence of Knowledge Conflicts in LLM.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines ConflictBank: A Benchmark for Evaluating the Influence of Knowledge Conflicts in LLM

Reference 29

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source=pdf_text observed=2026-08-01T04:48:28.680538Z digest=sha256:cdbc1a54df2442bed39e462547c31729fae411c9c6422e5405317e49d1bbbfb3

Observation 4715e1fb-673e-45ae-b90e-ab7c22b5a32f · outbound

This paper cites Task Matters: Knowledge Requirements Shape LLM Responses to Context-Memory Conflict.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines Task Matters: Knowledge Requirements Shape LLM Responses to Context-Memory Conflict

Reference 30

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source=pdf_text observed=2026-08-01T04:48:28.839800Z digest=sha256:9a49bf07217baf272aa3f065d9adc13af9a060328c013b28626e64b296cfd2db

Observation 20f0ffda-c0f2-42d2-a2fa-a09155946efe · outbound

This paper cites arXiv:2603.05637.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines arXiv:2603.05637

Reference 31

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source=pdf_text observed=2026-08-01T04:48:28.958292Z digest=sha256:5b5554d15d9d569fb671d26e76bbfa494b755118eb42c8983f596163a24952ba

Observation 09b1ee20-1304-4508-91b9-7c3ad2d358d2 · outbound

This paper cites Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models

Reference 32

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source=pdf_text observed=2026-08-01T04:48:29.103768Z digest=sha256:1ee7720e083517ca20864f6f7b4f18b4752ad74e0d3734f132b5e7c8171e497a

Observation 79fbcce1-4956-4d0b-886c-85a00bae893b · outbound

This paper cites Diagnosing and Mitigating Context Rot in Long-horizon Search.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines Diagnosing and Mitigating Context Rot in Long-horizon Search

Reference 33

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source=pdf_text observed=2026-08-01T04:48:29.223226Z digest=sha256:f7b9b3555e97887d1a1492e0b3998b60887f1ecf0a3b62f598e166168e004f95

Observation 9d987d81-ae4f-4513-b2c1-b9af990ec56f · outbound

This paper cites FaithfulRAG: Fact-Level Conflict Modeling for Context-Faithful Retrieval-Augmented Generation.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines FaithfulRAG: Fact-Level Conflict Modeling for Context-Faithful Retrieval-Augmented Generation

Reference 34

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source=pdf_text observed=2026-08-01T04:48:29.303043Z digest=sha256:fae66b2c7d3a9e63027d8f174bed122e8948332b0c6fbf0972e21a46d96c1f8d

Observation 62a9804a-a428-4246-988f-f67628a57fed · outbound

This paper cites $\infty$Bench: Extending Long Context Evaluation Beyond 100K Tokens.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines $\infty$Bench: Extending Long Context Evaluation Beyond 100K Tokens

Reference 35

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source=pdf_text observed=2026-08-01T04:48:29.418599Z digest=sha256:49593a765642073e4c481defc720d6cced71846cb4f440d3bd3e45298b8cf3cc

Observation 1aab1f1a-ac96-4089-bf2e-619d377325a9 · outbound

This paper cites InProceedings of the 63rd Annual Meeting of the As- sociation for Computational Linguistics (Volume 1: Long Papers), 12479–12491.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines InProceedings of the 63rd Annual Meeting of the As- sociation for Computational Linguistics (Volume 1: Long Papers), 12479–12491

Reference 36

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source=pdf_text observed=2026-08-01T04:48:29.517100Z digest=sha256:8fc3698a67e2b994196f8e53aceb42caeea1ea970bf624b21d1142051826c8c0

Observation 7538eeeb-c80e-4543-b6c3-b78a72685bf6 · outbound

This paper cites Entity-Based Knowledge Conflicts in Question Answering.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines Entity-Based Knowledge Conflicts in Question Answering

Reference 2021

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source=pdf_text observed=2026-08-01T04:48:26.949476Z digest=sha256:b83becc5ed56ad13486fe35b061b93295fbe5cb35c833ac1676f83569c351d50

Observation a73509b9-a994-4a2d-949f-1d09b3dd2a69 · outbound

This paper cites Extrinsically-Focused Evaluation of Omissions in Medical Summarization.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines Extrinsically-Focused Evaluation of Omissions in Medical Summarization

Reference 2023

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source=pdf_text observed=2026-08-01T04:48:28.422465Z digest=sha256:5ba50085f057aed48e9bd91c88912b69a3789a0034e7d32ba9dad45e6ef7881c

Observation 6ac5d3aa-ed7d-4947-bbca-b783de3c136c · outbound

This paper cites KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization

Reference 2024

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source=pdf_text observed=2026-08-01T04:48:25.926385Z digest=sha256:c41e92094cc5957f2ba1d33e5d4d8d35e4c4232895e4a2a742a77177897a9102

Observation 87b3f9af-dea2-4822-be96-dcbebb29d3fc · outbound

This paper cites arXiv:2510.18691.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines arXiv:2510.18691

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-01T04:48:24.188930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T04:48:24.188930Z digest=sha256:41185ea3152c41a2b905fa20654223d46f72f0c50ab7f97175a582bf40c70cd9

Observation a069d1c1-8a4e-4a02-8dce-1fc7e3f782aa · outbound

This paper cites CARE: A Conformal Safety Layer for Medical Summarization.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines CARE: A Conformal Safety Layer for Medical Summarization

Reference 2026

Resolution
unresolved
no resolver link, observed 2026-08-01T04:48:24.313006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T04:48:24.313006Z digest=sha256:fd6f24463b92ca2d1bc65acb3a023c9e9ab4c261615762b95b81f94b99f6e520

Pith citing papers

No inbound Pith citation observations are available.