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Paper Citation Record · LEDGER

Agent Safety Alignment via Reinforcement Learning

As of 21 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 5 inbound Pith citation observations for arXiv:2507.08270.

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

pith.paper-citation-record.v1
2507.08270 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:29:36.837135Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:23:23.093260Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T02:16:26.560954Z

Reference resolution

30 of 30 outbound references displayed

  • verified exact0
  • verified fuzzy13
  • unresolved16
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 180d6887-487a-4761-b359-a24be9ab44c2 · outbound

This paper cites Narasimhan, and Yuan Cao.

Agent Safety Alignment via Reinforcement Learning Narasimhan, and Yuan Cao

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-06T18:29:39.278568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T18:29:35.375189Z digest=sha256:f4057d4ad55a76b46e38e972bbe234c48e2aa20d01204fc94d60eef70ab2ea7e

Observation 9b8cfb93-2cd6-414b-bca4-c1d04723b526 · outbound

This paper cites AutoGPT: An open-source autonomous agent framework.

Agent Safety Alignment via Reinforcement Learning AutoGPT: An open-source autonomous agent framework

Reference 2

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raw_fallback, observed 2026-08-06T18:29:39.040807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T18:29:35.487365Z digest=sha256:3ec9235664c5e2be025cb8878ac32391ed1eab0205de753c6967e6ce3d6ede44

Observation 8c747e8a-2736-4a40-863c-48cef5300cb1 · outbound

This paper cites BabyAGI: Experimental self-building autonomous agent.

Agent Safety Alignment via Reinforcement Learning BabyAGI: Experimental self-building autonomous agent

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T18:29:35.542656Z digest=sha256:6db20d9b1d3a6b686a6eada22ec24a0234da436b8dbc6e299ccf02f53d59495d

Observation 30daa421-c6f6-4f62-871b-9fbce1301e31 · outbound

This paper cites AgentGPT: Configure and deploy autonomous ai agents.

Agent Safety Alignment via Reinforcement Learning AgentGPT: Configure and deploy autonomous ai agents

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T18:29:35.591544Z digest=sha256:c9203bd239b60b5d5a7146a0a5e33316f7642ec65432e8adafa682bbe23cd2f5

Observation 6d323b6e-662d-4c35-8a7b-b8dd7e2d3ac3 · outbound

This paper cites AI agents under threat: A survey of key security challenges and future pathways.

Agent Safety Alignment via Reinforcement Learning AI agents under threat: A survey of key security challenges and future pathways

Reference 5

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raw_fallback, observed 2026-08-06T18:29:38.493698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T18:29:35.624350Z digest=sha256:14c868a8ea1cbe298ba75e41b983302c6d55227e6802188a116bba45b259420b

Observation e903261e-c05d-428b-a610-f02e4534c4f9 · outbound

This paper cites Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents.

Agent Safety Alignment via Reinforcement Learning Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:29:35.685754Z digest=sha256:9d3a87b7bfafd600a3940f181e61e3febf6babeab87e6bdd0974402fe2470e74

Observation 277557af-1ef4-4596-8267-f1f6d14cfb36 · outbound

This paper cites Retool: Reinforcement learning for strategic tool use in llms, 2025.

Agent Safety Alignment via Reinforcement Learning Retool: Reinforcement learning for strategic tool use in llms, 2025

Reference 7

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raw_fallback, observed 2026-08-06T18:29:38.295437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T18:29:35.730506Z digest=sha256:0fb9f2154ac289faedbfafd4f03806d504646c66416e1e2ee365af042b436909

Observation 9064441a-04bc-4858-bf9f-bd04b31bf99b · outbound

This paper cites SEM: Reinforcement Learning for Search-Efficient Large Language Models.

Agent Safety Alignment via Reinforcement Learning SEM: Reinforcement Learning for Search-Efficient Large Language Models

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:29:35.794563Z digest=sha256:3ca75411095d3194d103cc00d7bb0e303585d8648813a4ecaa8bb2921879d271

Observation 11389ede-4427-4e8b-9513-85c8adb70359 · outbound

This paper cites Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training.

Agent Safety Alignment via Reinforcement Learning Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training

Reference 9

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source=pdf_text observed=2026-08-06T18:29:35.842058Z digest=sha256:d71872b0215b14bd39fdfbb0dd2ad30e823875e43788477c51b1c65669733ef5

Observation 9db288de-ae8a-40ce-922e-1f3dbc026ce4 · outbound

This paper cites Pan, Wen Zhang, Huajun Chen, Fan Yang, Zenan Zhou, and Weipeng Chen.

Agent Safety Alignment via Reinforcement Learning Pan, Wen Zhang, Huajun Chen, Fan Yang, Zenan Zhou, and Weipeng Chen

Reference 10

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raw_fallback, observed 2026-08-06T18:29:38.183883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T18:29:35.896986Z digest=sha256:6ba52b193350fb2035d6b57734822d3a64ac6f04269993feea6931c830750b34

Observation 81cbd57d-026c-4c08-b680-a2d98e1d6acf · outbound

This paper cites Agent security bench (ASB): formalizing and benchmarking attacks and defenses in llm-based agents.

Agent Safety Alignment via Reinforcement Learning Agent security bench (ASB): formalizing and benchmarking attacks and defenses in llm-based agents

Reference 11

Resolution
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raw_fallback, observed 2026-08-06T18:29:38.041081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T18:29:35.957481Z digest=sha256:328398fa587084c273ad5cd0351a23dd459ab30c6ea16effe082f308551357b4

Observation 29aeb465-7be8-4e24-a417-a491faef2aff · outbound

This paper cites Agent-SafetyBench: Evaluating the Safety of LLM Agents.

Agent Safety Alignment via Reinforcement Learning Agent-SafetyBench: Evaluating the Safety of LLM Agents

Reference 12

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T18:29:36.015210Z digest=sha256:aff77c46b1bf768f2c4c127491a539795cd0e1f7f1d16d206c8f1188bfe6e450

Observation f0ee323a-2ed7-4e0d-bd10-97e50f9bb5ae · outbound

This paper cites Think Twice Before You Act: Enhancing Agent Behavioral Safety with Thought Correction.

Agent Safety Alignment via Reinforcement Learning Think Twice Before You Act: Enhancing Agent Behavioral Safety with Thought Correction

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:29:36.076016Z digest=sha256:dcb943f7f2b77cabefef5187466d5d58c415944240f66a21acc265ed8cb4249d

Observation 810eec96-44f3-4628-8fde-c766f6a55667 · outbound

This paper cites AgentAlign: Navigating Safety Alignment in the Shift from Informative to Agentic Large Language Models.

Agent Safety Alignment via Reinforcement Learning AgentAlign: Navigating Safety Alignment in the Shift from Informative to Agentic Large Language Models

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:29:36.127202Z digest=sha256:2e8d444879e7c8f93bd2261f8d648ee8509518298f52029aba5cac76a1b35e19

Observation 80905211-b7a7-441a-a286-19e9f3ddb51a · outbound

This paper cites Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025.

Agent Safety Alignment via Reinforcement Learning Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025

Reference 15

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source=pdf_text observed=2026-08-06T18:29:36.164795Z digest=sha256:2026412200d0a9c8fa3da9cde633a6f0d6ef7cdb30d881ded3d8b086b96d8f25

Observation 17a08604-0c36-4cad-8775-c863bc923e5b · outbound

This paper cites Injecagent: Benchmarking indirect prompt injections in tool-integrated large language model agents.

Agent Safety Alignment via Reinforcement Learning Injecagent: Benchmarking indirect prompt injections in tool-integrated large language model agents

Reference 16

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raw_fallback, observed 2026-08-06T18:29:37.906726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T18:29:36.202956Z digest=sha256:26917eef9bb0ff5c383c853138235ab1f903ae0e6ffc06c0c8cd3bb73a956526

Observation e0617b99-43ab-43ee-ad94-10026b7b850b · outbound

This paper cites Patil, Huanzhi Mao, Charlie Cheng-Jie Ji, Fanjia Yan, Vishnu Suresh, Ion Stoica, and Joseph E.

Agent Safety Alignment via Reinforcement Learning Patil, Huanzhi Mao, Charlie Cheng-Jie Ji, Fanjia Yan, Vishnu Suresh, Ion Stoica, and Joseph E

Reference 17

Resolution
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raw_fallback, observed 2026-08-06T18:29:37.752821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T18:29:36.248215Z digest=sha256:b312b9f95666299ce5f0b82e85401e6d85d346f234c74c5f74b1bcc3bc20c32b

Observation b2d897fa-1c92-4adf-9b0a-edc24e9241d6 · outbound

This paper cites Large Language Model Agent: A Survey on Methodology, Applications and Challenges.

Agent Safety Alignment via Reinforcement Learning Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 18

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source=pdf_text observed=2026-08-06T18:29:36.302719Z digest=sha256:5eb70a567fc93a30c368d54442cfe08463eafa193dcdfa59770aa3f8f8172c26

Observation 6e81ee76-f028-4cc3-bc71-108bc49d7958 · outbound

This paper cites An In-depth Survey of Large Language Model-based Artificial Intelligence Agents.

Agent Safety Alignment via Reinforcement Learning An In-depth Survey of Large Language Model-based Artificial Intelligence Agents

Reference 19

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source=pdf_text observed=2026-08-06T18:29:36.361217Z digest=sha256:99db08ed89abb73d566c0c127a1bf632fbf978e9a27de88135926744920b4024

Observation f10aa2d4-cfbb-496c-82c6-09d82e7f1ce8 · outbound

This paper cites Sumers, Shunyu Yao, Karthik Narasimhan, and Thomas L.

Agent Safety Alignment via Reinforcement Learning Sumers, Shunyu Yao, Karthik Narasimhan, and Thomas L

Reference 20

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raw_fallback, observed 2026-08-06T18:29:37.597508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T18:29:36.410757Z digest=sha256:76085db64efa54fa830472fd7d53a9b3acb054b25801dabd676fa3a0b3b38e99

Observation a273817c-b321-431e-bd36-6a183d9853e9 · outbound

This paper cites AutoAgent: A Fully-Automated and Zero-Code Frame- work for LLM Agents, 2025.

Agent Safety Alignment via Reinforcement Learning AutoAgent: A Fully-Automated and Zero-Code Frame- work for LLM Agents, 2025

Reference 21

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raw_fallback, observed 2026-08-06T18:29:37.477865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T18:29:36.458385Z digest=sha256:a1c36a813a85e462e30187ef58f0acdfb07525983380a0d15c0d25d36f596fcc

Observation dad2e0b3-a7d9-4aea-8958-819993d89801 · outbound

This paper cites ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning.

Agent Safety Alignment via Reinforcement Learning ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning

Reference 23

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source=pdf_text observed=2026-08-06T18:29:36.509257Z digest=sha256:5438fde87fcc992ff107dc3c1f42136147abcd33d0488f529f1190ba6c305552

Observation 17698f00-7f3f-49a3-a4d3-fc47cef63484 · outbound

This paper cites Deepresearcher: Scaling deep research via reinforcement learning in real-world environments, 2025.

Agent Safety Alignment via Reinforcement Learning Deepresearcher: Scaling deep research via reinforcement learning in real-world environments, 2025

Reference 24

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source=pdf_text observed=2026-08-06T18:29:36.552229Z digest=sha256:15f99ffb0416ee2b2a23cfa2bd0e1a6b7b04c1e029f557526273e84255488ca9

Observation c292e407-2abc-4880-9c67-6926d025440e · outbound

This paper cites Beyond the Protocol: Unveiling Attack Vectors in the Model Context Protocol (MCP) Ecosystem.

Agent Safety Alignment via Reinforcement Learning Beyond the Protocol: Unveiling Attack Vectors in the Model Context Protocol (MCP) Ecosystem

Reference 25

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source=pdf_text observed=2026-08-06T18:29:36.599007Z digest=sha256:b9336da8c08e5403019bc0e9ff188095aada4ad7702f5fffa8e3c03a34dc1247

Observation af481968-d1c7-4ba9-aca5-a42cdc8392d5 · outbound

This paper cites Progent: Securing AI Agents with Privilege Control.

Agent Safety Alignment via Reinforcement Learning Progent: Securing AI Agents with Privilege Control

Reference 26

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source=pdf_text observed=2026-08-06T18:29:36.649473Z digest=sha256:b64e75e625b6a2f06e0b65d9e158d186c48997e9a8fe989533d2ee88c6c37892

Observation 3d8ff5a5-ea96-4e0b-91cb-22d95099f4d2 · outbound

This paper cites Fox in the Henhouse: Supply-Chain Backdoor Attacks Against Reinforcement Learning.

Agent Safety Alignment via Reinforcement Learning Fox in the Henhouse: Supply-Chain Backdoor Attacks Against Reinforcement Learning

Reference 27

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source=pdf_text observed=2026-08-06T18:29:36.704014Z digest=sha256:7e062b69e94e37766fcac5829793a43fb817e389e9193bb9afd17481fefea0be

Observation f0adbf1b-2904-4aa7-954c-6cf7b23e3bc7 · outbound

This paper cites A practical memory injection attack against LLM agents.

Agent Safety Alignment via Reinforcement Learning A practical memory injection attack against LLM agents

Reference 28

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no resolver link, observed 2026-08-06T18:29:36.746281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:29:36.746281Z digest=sha256:e03d267ce9bfcc90689c5cacc4aa0a4ab34be5e581752a5a6e5570e1648eeefa

Observation 17663713-ff13-49cf-816d-39dcd70da839 · outbound

This paper cites Agentpoison: Red- teaming LLM agents via poisoning memory or knowledge bases.

Agent Safety Alignment via Reinforcement Learning Agentpoison: Red- teaming LLM agents via poisoning memory or knowledge bases

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-06T18:29:37.380765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T18:29:36.793821Z digest=sha256:ab4d22696bc4c4a532b0aa5646940b89a9d5d89df5b5b9c114d5250411d6d72f

Observation 474d8d38-3066-4322-b55d-e140835d4b2f · outbound

This paper cites Safeagentbench: A benchmark for safe task planning of embodied LLM agents.

Agent Safety Alignment via Reinforcement Learning Safeagentbench: A benchmark for safe task planning of embodied LLM agents

Reference 30

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:29:36.837135Z digest=sha256:66b41302c22f476ba530624b365b7eb429117e07103b3cd5c7467ffcb2188eec

Observation 86d6065a-488b-4180-8dbc-b3fb19586d46 · outbound

This paper cites an unresolved cited work.

Agent Safety Alignment via Reinforcement Learning Unresolved cited work

Reference 2023

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:29:35.441056Z digest=sha256:950bca40b51c63c5b72eadb951ccef29f04b84632f7118ec412af1c172673799

Pith citing papers

Observation 4e0b924d-c7a3-4880-af77-73a752de6b5f · inbound

S3LoRA: Safe Spectral Sharpness-Guided Pruning in Adaptation of Agent Planner cites this paper.

S3LoRA: Safe Spectral Sharpness-Guided Pruning in Adaptation of Agent Planner Agent Safety Alignment via Reinforcement Learning

Reference 24

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source=arxiv_source observed=2026-08-05T18:12:35.170680Z digest=sha256:232580b0f5592d0f4ccc435a793ec0157c5566c318af8d0daa8c5814293a08f6

Observation df93920d-a25d-43be-90bb-e4a56a80e3e5 · inbound

RUBAS: Rubric-Based Reinforcement Learning for Agent Safety cites this paper.

RUBAS: Rubric-Based Reinforcement Learning for Agent Safety Agent Safety Alignment via Reinforcement Learning

Reference 5

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verified exact
arxiv_id, observed 2026-07-02T02:16:26.562656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-28T11:07:47.814115Z digest=sha256:a69c66c6ca94ca16f364554a1a920dd32521911a85170f17b42048fe5b268b9b

Observation 302533e2-3be7-4e66-9313-72f4e359b5d8 · inbound

SAFETY SENTRY: Context-Aware Human Intervention via EXECUTE-ASK-REFUSE Routing cites this paper.

SAFETY SENTRY: Context-Aware Human Intervention via EXECUTE-ASK-REFUSE Routing Agent Safety Alignment via Reinforcement Learning

Reference 23

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source=arxiv_source observed=2026-08-02T04:49:08.700306Z digest=sha256:2d21dacc7de8b37fa4377b1310335fab45f091f312e729dc4b50a55cdff7c489

Observation 1de972a0-65c9-483d-bc7a-6cef8dca0b61 · inbound

$S^3$: Improving Agent Safety through Multi-Stage Defense cites this paper.

$S^3$: Improving Agent Safety through Multi-Stage Defense Agent Safety Alignment via Reinforcement Learning

Reference 16

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no resolver link, observed 2026-08-07T00:14:57.067936Z

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source=arxiv_source observed=2026-08-07T00:14:57.067936Z digest=sha256:ff5ea70040bd4ba2f49d1763cb7cbcc0b557539b1b34556e0eaac322dc684319

Observation 9fde75e9-3488-4d78-9538-2781d2be5cef · inbound

Beyond Handcrafted Security: Towards Self-Evolving Defense for LLM Agents cites this paper.

Beyond Handcrafted Security: Towards Self-Evolving Defense for LLM Agents Agent Safety Alignment via Reinforcement Learning

Reference 14

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no resolver link, observed 2026-08-15T19:23:23.093260Z

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source=pdf_text observed=2026-08-15T19:23:23.093260Z digest=sha256:3930b0d9df55662877afb96de971f983f88ca03881d0c6ee0ef7c7dad60d7289