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Paper Citation Record · LEDGER

A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 42 inbound Pith citation observations for arXiv:2504.15585.

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

pith.paper-citation-record.v1
2504.15585 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 42 of 42 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:47:06.486187Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 17b4c414-b8f2-4f89-9b36-58b936c31ebc · inbound

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models cites this paper.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 49

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no resolver link, observed 2026-08-07T05:47:06.486187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.486187Z digest=sha256:76938d83aee0fa0f7d5de736baf099a6a564949d804fca95279332c8daf32a64

Observation 1cd39cb2-ad4d-4097-9cd9-44ea269ef0ba · inbound

We Should Identify and Mitigate Third-Party Safety Risks in MCP-Powered Agent Systems cites this paper.

We Should Identify and Mitigate Third-Party Safety Risks in MCP-Powered Agent Systems A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 78

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no resolver link, observed 2026-08-07T00:32:36.685699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:32:36.685699Z digest=sha256:3853d8b81d22dcf85d5307db050f2620354921303bccf2819aa7f2197cf40aba

Observation b438ebc6-52ae-409a-a544-a4776270ec1a · inbound

SafeMobile: Chain-level Jailbreak Detection and Automated Evaluation for Multimodal Mobile Agents cites this paper.

SafeMobile: Chain-level Jailbreak Detection and Automated Evaluation for Multimodal Mobile Agents A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 7

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no resolver link, observed 2026-08-06T21:11:18.191017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:11:18.191017Z digest=sha256:67f6e8a70a50eb81bc5c5c72a0d46092fb3f0107fe07447267c103da376fca4c

Observation 0562f6cf-ecf1-410b-972a-4bcbb3489d07 · inbound

Introducing the Swiss Food Knowledge Graph: AI for Context-Aware Nutrition Recommendation cites this paper.

Introducing the Swiss Food Knowledge Graph: AI for Context-Aware Nutrition Recommendation A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 71

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no resolver link, observed 2026-08-06T17:43:16.320326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:43:16.320326Z digest=sha256:774653a79b15aa724b4274e89db9bcbbade12c37feae2d3dd72419a31964e3a7

Observation fa829d15-d2e1-4545-80f0-6e13031e4a64 · inbound

Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges cites this paper.

Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 283

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no resolver link, observed 2026-08-06T15:06:48.912765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:06:48.912765Z digest=sha256:bf7c1332705167075c37caade3dbcff7dd18f532ba8d3c64f77ee3f6f9521f50

Observation f9a1bb5b-5315-4926-bd23-7882987630c2 · inbound

Graph-Augmented Large Language Model Agents: Current Progress and Future Prospects cites this paper.

Graph-Augmented Large Language Model Agents: Current Progress and Future Prospects A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 53

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no resolver link, observed 2026-08-06T12:52:01.469405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:52:01.469405Z digest=sha256:18aca27232590ec046a02b0e722465c18289e5d706afc6e331124123914804f3

Observation f81e63ee-310a-4b40-a780-cc2cec28daae · inbound

Adaptive Backtracking for Privacy Protection in Large Language Models cites this paper.

Adaptive Backtracking for Privacy Protection in Large Language Models A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 7

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no resolver link, observed 2026-08-05T23:04:08.645670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:04:08.645670Z digest=sha256:1d10547263a8ad26d073868e6b66eb91cb103a6d875fc2e6988794d12579bd94

Observation 8360dd42-bfa8-4b80-8ac4-5808aa6baa3c · inbound

A Comprehensive Survey on Trustworthiness in Reasoning with Large Language Models cites this paper.

A Comprehensive Survey on Trustworthiness in Reasoning with Large Language Models A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 4

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no resolver link, observed 2026-08-05T10:38:58.402887Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:38:58.402887Z digest=sha256:6b1dbe43809ff79c94b64fcd2d415dcd406306406329fd062b3a4524454f141b

Observation 6dcbcab6-57cf-46f6-b4f6-c7ef91578aa5 · inbound

KubeGuard: LLM-Assisted Kubernetes Hardening via Configuration Files and Runtime Logs Analysis cites this paper.

KubeGuard: LLM-Assisted Kubernetes Hardening via Configuration Files and Runtime Logs Analysis A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 95

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no resolver link, observed 2026-08-05T10:21:47.149354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:21:47.149354Z digest=sha256:99fe3a902dcfb820f8557f526a664e7578ca056b493928a44e6c88dcda9b601b

Observation 627e0278-77d1-45ca-b4ff-497df50cc0d9 · inbound

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial cites this paper.

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 175

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no resolver link, observed 2026-08-05T04:50:32.170105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T04:50:32.170105Z digest=sha256:ce81babacadf9d340ad79e6385dc245a91364756e39939ea95cd8fcd3f3a29ce

Observation 5687e63f-1cfc-491f-8ddc-4cba96ebfa15 · inbound

Uncovering Vulnerabilities of LLM-Assisted Cyber Threat Intelligence cites this paper.

Uncovering Vulnerabilities of LLM-Assisted Cyber Threat Intelligence A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 22

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no resolver link, observed 2026-08-04T14:42:50.674982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:42:50.674982Z digest=sha256:65f6c9d45a0aaeae69d9e20bea9bc15c0a63716f20afcc0db5162a37d0a8c56f

Observation 3004583b-014b-4f1f-a1fb-04940e398556 · inbound

Agentic Services Computing cites this paper.

Agentic Services Computing A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 178

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no resolver link, observed 2026-08-04T14:41:50.921051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:41:50.921051Z digest=sha256:b67dab5b53c328b6451ba7d6d56df15afc598a013a398790d6a88f8dd63255e7

Observation 2fa5d3d6-f2b3-4950-8354-f4c2c0d9357f · inbound

AgenticEval: Toward Agentic and Self-Evolving Safety Evaluation of Large Language Models cites this paper.

AgenticEval: Toward Agentic and Self-Evolving Safety Evaluation of Large Language Models A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 12

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arxiv_id, observed 2026-05-18T12:36:22.463634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T12:35:01.443896Z digest=sha256:2465e3959d4150660763dfcba9331d390fca9f5ceb769b022b61c838fd5303b9

Observation 0ccd089e-dbac-49e9-896e-a4b7c58c5b3e · inbound

Check Yourself Before You Wreck Yourself: Selectively Quitting Improves LLM Agent Safety cites this paper.

Check Yourself Before You Wreck Yourself: Selectively Quitting Improves LLM Agent Safety A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 15

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no resolver link, observed 2026-08-04T09:15:21.818144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T09:15:21.818144Z digest=sha256:ae0b42ce008459fd82d820f089c3a91972175a25245a1f8f8fcd2fc224282512

Observation 1f81fcd7-473e-4ead-8dca-e4c2f59e4af5 · inbound

Securing Multi-Agent Systems Against Corruptions via Node Contribution Backpropagation cites this paper.

Securing Multi-Agent Systems Against Corruptions via Node Contribution Backpropagation A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 21

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no resolver link, observed 2026-08-04T08:44:56.504049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:44:56.504049Z digest=sha256:fd307370b475a4163bdf620c2a82ec2dcd97e9bf40737d064f0b6a693e5bc2a1

Observation 8990c204-c015-4c3a-bd3e-0608db533c45 · inbound

Evolve the Method, Not the Prompts: Evolutionary Synthesis of Jailbreak Attacks on LLMs cites this paper.

Evolve the Method, Not the Prompts: Evolutionary Synthesis of Jailbreak Attacks on LLMs A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 47

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arxiv_id, observed 2026-05-21T19:00:30.397180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T18:58:53.183734Z digest=sha256:14758e03f5d6b2c38516d4e6496adc86063c9a67e2c248d2f736a8f7c185fe77

Observation 432e8ebe-e187-4091-93ad-ae6b1c7facf7 · inbound

The Alignment Curse: Modality Alignment Supercharges Audio Attacks via Text Transfer cites this paper.

The Alignment Curse: Modality Alignment Supercharges Audio Attacks via Text Transfer A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 19

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no resolver link, observed 2026-08-03T06:23:43.757957Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:23:43.757957Z digest=sha256:00163f3a32a744851dee22a7488af80da4090c807279f09e2b5007c1703cfe7c

Observation 746a367d-6d75-4b97-850f-e419c3b57eb1 · inbound

ProbeLLM: Automating Principled Diagnosis of LLM Failures cites this paper.

ProbeLLM: Automating Principled Diagnosis of LLM Failures A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 2019

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no resolver link, observed 2026-08-02T23:43:07.687190Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:43:07.687190Z digest=sha256:e2fdb92ae4c5e29ccf8623b7931f738d9c644472a87be4b03504f7a1036bf127

Observation 4125b05d-325a-465f-9376-34ee1f85469b · inbound

The Salami Slicing Threat: Exploiting Cumulative Risks in LLM Systems cites this paper.

The Salami Slicing Threat: Exploiting Cumulative Risks in LLM Systems A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 1

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arxiv_id, observed 2026-05-11T09:16:04.234442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T16:07:31.602378Z digest=sha256:ba5f2de33a6fd8af29b0c131050de39621350a090b2a4bf6c8d357b4981c7e76

Observation e74ea2e4-43ec-46d2-ac23-36da4267756b · inbound

BiasIG: Benchmarking Multi-dimensional Social Biases in Text-to-Image Models cites this paper.

BiasIG: Benchmarking Multi-dimensional Social Biases in Text-to-Image Models A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 17

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arxiv_id, observed 2026-05-11T10:21:00.645817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T15:33:15.025940Z digest=sha256:4adec25fc4862fcddeda983b9691d52614b9a271d4cce74710c8eed88d5e030e

Observation 1e41d869-3c91-4f07-b6bc-d6471d446470 · inbound

LLM-Based Multi-Agent Systems for Code Generation: A Multi-Vocal Literature Review cites this paper.

LLM-Based Multi-Agent Systems for Code Generation: A Multi-Vocal Literature Review A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 63

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arxiv_id, observed 2026-05-15T19:56:33.814418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T19:52:49.324500Z digest=sha256:15b56336e5346339032efb427dca31b0e1182537b56141f7e47135ea819e5aff

Observation 93e9fd91-8f12-4b4d-acc2-50be6e16a428 · inbound

ProjLens: Unveiling the Role of Projectors in Multimodal Model Safety cites this paper.

ProjLens: Unveiling the Role of Projectors in Multimodal Model Safety A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 178

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arxiv_id, observed 2026-05-11T12:46:05.697693Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-10T03:00:34.862711Z digest=sha256:24b8fdd4d216d7742152c6d1fc6f96d78ab5bc189d7b4765be3b19091a9eb295

Observation 9297d37a-a513-4dcd-8b8d-0d9f71da619c · inbound

TwinGate: Stateful Defense against Decompositional Jailbreaks in Untraceable Traffic via Asymmetric Contrastive Learning cites this paper.

TwinGate: Stateful Defense against Decompositional Jailbreaks in Untraceable Traffic via Asymmetric Contrastive Learning A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 27

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arxiv_id, observed 2026-05-12T10:26:29.219146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-07T06:12:37.845017Z digest=sha256:471ef1cb4416e72631b658049feaa1de3e3eb6372e608cb2db201b5bf09e9102

Observation 5b14aa25-c446-4733-8b09-f9ad1b3e762e · inbound

Disentangling Intent from Role: Adversarial Self-Play for Persona-Invariant Safety Alignment cites this paper.

Disentangling Intent from Role: Adversarial Self-Play for Persona-Invariant Safety Alignment A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 10

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arxiv_id, observed 2026-05-11T16:21:07.319493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-09T17:24:54.796037Z digest=sha256:7c954312bc2ba46b80eb9f14fb40cbc5766cda8cc5f80dfe0b1c62e56a490fcc

Observation 0536dfdb-3e49-4208-97fc-b63d716f6d09 · inbound

Explaining and Breaking the Safety-Helpfulness Ceiling via Preference Dimensional Expansion cites this paper.

Explaining and Breaking the Safety-Helpfulness Ceiling via Preference Dimensional Expansion A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 7

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arxiv_id, observed 2026-05-13T01:07:00.563071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-13T01:03:10.263663Z digest=sha256:8dd2ee794c70e619e26c106b2db25390422e201d1596f5eeb0cb20ce25b214bc

Observation 0eb13ae8-32e2-4dc7-8a0b-27627098488d · inbound

Explaining and Breaking the Safety-Helpfulness Ceiling via Preference Dimensional Expansion cites this paper.

Explaining and Breaking the Safety-Helpfulness Ceiling via Preference Dimensional Expansion A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 7

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verified exact
arxiv_id, observed 2026-05-14T21:12:58.976961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-14T21:12:06.989077Z digest=sha256:656c902eb71b573121dcea38727dd765e2fea9a8648b4ccc059646246d742663

Observation a6dfaaca-478c-4429-bd9a-077cbb8d879f · inbound

BackFlush: Knowledge-Free Backdoor Detection and Elimination with Watermark Preservation in Large Language Models cites this paper.

BackFlush: Knowledge-Free Backdoor Detection and Elimination with Watermark Preservation in Large Language Models A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 9

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verified exact
arxiv_id, observed 2026-05-14T21:02:58.891963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-14T21:01:10.756844Z digest=sha256:99567b857d23945363f7ba574b3ba1272aea4509bbfb20101a1829b06c5ca9a4

Observation 9a3344e2-5e67-4e03-bc5a-0669f6456152 · inbound

Taxonomy and Consistency Analysis of Safety Benchmarks for AI Agents cites this paper.

Taxonomy and Consistency Analysis of Safety Benchmarks for AI Agents A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 52

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arxiv_id, observed 2026-05-21T01:43:56.850450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-21T01:42:55.693115Z digest=sha256:62fdd1909a51d18a57ab9acf40d006e1c4d6f5557f442f2f7740d4e96d389f09

Observation 1ebf339c-e46d-4d65-addf-a2d9d2dc71a7 · inbound

A Survey of Large Audio Language Models: Generalization, Trustworthiness, and Outlook cites this paper.

A Survey of Large Audio Language Models: Generalization, Trustworthiness, and Outlook A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 21

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arxiv_id, observed 2026-05-21T07:39:49.124688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T07:38:23.099479Z digest=sha256:35d3cb563b331b5b964c1f3e503122f151027698180a2b403cbb46066ca2b3e2

Observation 49e329d1-315d-45f4-a7b7-b335c0985d17 · inbound

Trusted Weights, Treacherous Optimizations? Optimization-Triggered Backdoor Attacks on LLMs cites this paper.

Trusted Weights, Treacherous Optimizations? Optimization-Triggered Backdoor Attacks on LLMs A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 26

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verified exact
arxiv_id, observed 2026-05-21T04:49:35.654769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T04:45:35.079192Z digest=sha256:7cddf70b042390331039bb0d89bad1ce63ea67c9145f067327e15bbd77c3f05e

Observation 063b7fbf-a09c-4ef6-82f4-5e3ceab79311 · inbound

Detecting Unfaithful Chain-of-Thought via Circuit-Guided Internal-External Discrepancy cites this paper.

Detecting Unfaithful Chain-of-Thought via Circuit-Guided Internal-External Discrepancy A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 43

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verified exact
arxiv_id, observed 2026-06-29T21:53:59.521103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-29T21:47:17.894881Z digest=sha256:4f5b861171891315fc1901e08f0d04e3fd29ac6e72bdd529b104d3a03fbef82a

Observation a1cdd3b8-337d-4c90-95a3-6dd4ab19b69b · inbound

Aligned but Fragile: Enhancing LLM Safety Robustness via Zeroth-Order Optimization cites this paper.

Aligned but Fragile: Enhancing LLM Safety Robustness via Zeroth-Order Optimization A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 27

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arxiv_id, observed 2026-06-29T07:43:13.502152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-29T07:41:03.219581Z digest=sha256:927819116271e223842eddc0f168a6d1e70c656ce5de6433905d1883f8c5eae3

Observation df30c543-00b4-46cf-9de7-8d4e668bdb15 · inbound

POIROT: Interrogating Agents for Failure Detection in Multi-Agent Systems cites this paper.

POIROT: Interrogating Agents for Failure Detection in Multi-Agent Systems A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 13

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metadata mismatch
arxiv_id, observed 2026-07-01T23:06:19.985654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T14:44:21.487169Z digest=sha256:87fd8c088e2e6564ed25d4b027ff8562983e95f123c2fd533da7037659b73801

Observation aaa70230-6616-4e55-ad12-b59207d03a12 · inbound

Safe Embodied AI for Long-horizon Tasks: A Cross-layer Analysis of Robotic Manipulation cites this paper.

Safe Embodied AI for Long-horizon Tasks: A Cross-layer Analysis of Robotic Manipulation A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T12:56:56.715862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-28T01:46:36.081851Z digest=sha256:7deaa4e4b25bc7769902f98dc571371f409630fdb100590aa9dcabf75e06a900

Observation 090f64dc-976d-4b53-b52f-a84b53fc51b1 · inbound

Toward Secure LLM Agents: Threat Surfaces, Attacks, Defenses, and Evaluation cites this paper.

Toward Secure LLM Agents: Threat Surfaces, Attacks, Defenses, and Evaluation A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 182

Resolution
verified exact
arxiv_id, observed 2026-06-27T13:20:56.866720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T12:55:22.831264Z digest=sha256:9f6c9371d5f19d0d0bc7f62ef252ebce48979407dbb0b5bc7917af41de7260eb

Observation 7b03d879-f0ea-47f2-8cf2-a175c1c308fc · inbound

SAIGuard: Communication-State Simulation for Proactive Defense of LLM Multi-Agent Systems cites this paper.

SAIGuard: Communication-State Simulation for Proactive Defense of LLM Multi-Agent Systems A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T13:28:18.834488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-27T08:04:15.004591Z digest=sha256:43180ffa348d998ada48a22971297b0e69e3d08e23f1d53e501a4dbbf69eff49

Observation ef2b4891-04f4-4c96-a460-7e69a64d9593 · inbound

PolicyAlign: Direct Policy-Based Safety Alignment for Large Language Models cites this paper.

PolicyAlign: Direct Policy-Based Safety Alignment for Large Language Models A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T19:40:06.706686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-25T21:09:19.727723Z digest=sha256:bb40b26a84708183b04bc1e5d41aed60887fa179c0573cb36cbcb0b2a3310768

Observation b1fc6796-572d-4c6b-b90d-f88057d94645 · inbound

Reducing Conversational Escalation in Large Language Model Dialogue with Nonviolent Communication Constraints cites this paper.

Reducing Conversational Escalation in Large Language Model Dialogue with Nonviolent Communication Constraints A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T08:05:31.326711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-07-01T07:56:07.948696Z digest=sha256:687511294ee0624e5bb6a4fe13c344a957c9afddbb6c918f236e365c2c1cd76b

Observation 44eabc72-7363-4262-a7ca-ec27128cfdb2 · inbound

Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors cites this paper.

Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-06-30T08:04:28.739091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T07:47:18.350953Z digest=sha256:ce4d1eee66d8a013677453335b20af431ba4c2e3a3aaeb804f5391ff8d65604e

Observation baf5f170-7c2e-4782-985c-c1ae06ee600f · inbound

Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors cites this paper.

Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-04T04:39:06.922277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T04:39:06.922277Z digest=sha256:ae48a5fdd9b0b6a181fc229a6fbc3db0f44e93f22946c68f8ba4785a13bae2e9

Observation 6fc0892e-e9c5-4435-a09e-b5039a8bd066 · inbound

Temporary Authority, Permanent Effects: Commit-Time Authorization for LLM Agents cites this paper.

Temporary Authority, Permanent Effects: Commit-Time Authorization for LLM Agents A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 59

Resolution
unresolved
no resolver link, observed 2026-07-14T11:21:48.935912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T11:21:48.935912Z digest=sha256:ceccf21985336807820ff6b951bc4f5d3d659dc32ebfffe031e788d1b4f9e78b

Observation 9f185a3e-dd8e-4ffa-9144-a44a7613bf20 · inbound

Persistent Sparse Autoencoders: Learning Feature Timescales in Language Models cites this paper.

Persistent Sparse Autoencoders: Learning Feature Timescales in Language Models A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 185

Resolution
unresolved
no resolver link, observed 2026-08-01T19:02:48.799933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T19:02:48.799933Z digest=sha256:99dfc71003b3edc5cf5c5283418e01f9d474f5b85c98a20c45cc24fd23dfb478