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Paper Citation Record · LEDGER

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning

As of 21 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 2 inbound Pith citation observations for arXiv:2505.14585.

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

pith.paper-citation-record.v1
2505.14585 v2

Coverage vector

measured 66 of 66 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:37:31.442193Z

measured 68 of 68 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:38:15.928177Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:38:20.641277Z

Reference resolution

66 of 66 outbound references displayed

  • verified exact5
  • verified fuzzy0
  • unresolved60
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 39372ee0-310d-4014-9563-c6249e5ce4f3 · outbound

This paper cites Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations

Reference 1

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metadata mismatch
local_arxiv, observed 2026-08-07T15:37:33.808468Z

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=arxiv_source observed=2026-08-07T15:37:24.568421Z digest=sha256:093ae5355e7679223938597d1b7c18e2b5a7b52db9f9749372d20bf998ff89a5

Observation 98d5261d-aec7-41d1-87e6-b061f686cbd0 · outbound

This paper cites an unresolved cited work.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Unresolved cited work

Reference 2

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source=arxiv_source observed=2026-08-07T15:37:24.652966Z digest=sha256:41565142746e28f4a58489ccf476100151855c91ef34bdfade0f3660c8d8ebcf

Observation e8775409-1e12-4eb4-8e46-f34f00afda2b · outbound

This paper cites an unresolved cited work.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Unresolved cited work

Reference 3

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source=arxiv_source observed=2026-08-07T15:37:24.786439Z digest=sha256:3bc3e4c8ea748a9a761efd7f3fefaa5f9e8b590b0d8b653d892716c80803a6ac

Observation ba1cd59e-96f6-4094-8274-c9999a2bab12 · outbound

This paper cites The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks

Reference 4

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source=arxiv_source observed=2026-08-07T15:37:24.927576Z digest=sha256:b6af520bff1c66daf0abc1e7d62818dcf380ed59da90fe63ec4a432b76977ca0

Observation 73256e9c-8ad7-463d-8010-e673d7e5b027 · outbound

This paper cites Extracting Training Data from Large Language Models.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Extracting Training Data from Large Language Models

Reference 5

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source=arxiv_source observed=2026-08-07T15:37:25.072025Z digest=sha256:b4be97d0c108d103bd9cbd98e462a2767c00ab083c3262b76956a31580b062ae

Observation 990725b1-be1d-46c1-914d-3fc89abcb71c · outbound

This paper cites Jailbreaking Black Box Large Language Models in Twenty Queries.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Jailbreaking Black Box Large Language Models in Twenty Queries

Reference 6

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source=arxiv_source observed=2026-08-07T15:37:25.204373Z digest=sha256:f6d9c02e4567133ae612a0454271ca4c7d0a8bedfb169870bf13c6a85abb47e1

Observation 479f46f2-999d-4390-b4b3-e682553bf8d2 · outbound

This paper cites an unresolved cited work.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Unresolved cited work

Reference 7

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source=arxiv_source observed=2026-08-07T15:37:25.308495Z digest=sha256:6839cba2386a18d4af38c6fa2c6ea624b1bae4d79327fcf0458e94e031825c42

Observation 9465ff60-eece-440f-b092-eaf26ede060d · outbound

This paper cites an unresolved cited work.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Unresolved cited work

Reference 8

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source=arxiv_source observed=2026-08-07T15:37:25.421845Z digest=sha256:8313ff14d8d3ed97d889317781e7769473480e05043557c5f1109e368f096028

Observation b4c83403-ada1-4f8e-a984-2e5013396b1b · outbound

This paper cites an unresolved cited work.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Unresolved cited work

Reference 9

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source=arxiv_source observed=2026-08-07T15:37:25.578725Z digest=sha256:a1e62533d0f492ba00d47f649286f4b2b74fd935c51ff2a765a5991d0dec0e19

Observation 6f69d212-7e44-4e3a-b3e3-18fa67d7dd94 · outbound

This paper cites CI-Bench: Benchmarking Contextual Integrity of AI Assistants on Synthetic Data.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning CI-Bench: Benchmarking Contextual Integrity of AI Assistants on Synthetic Data

Reference 10

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source=arxiv_source observed=2026-08-07T15:37:25.713365Z digest=sha256:b558857049464a16295d5c756010b69bd2afd42a742ef6500928d5232c379ad7

Observation fc839245-d41b-4f72-8890-306b4f6ff67d · outbound

This paper cites Process Reinforcement through Implicit Rewards.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Process Reinforcement through Implicit Rewards

Reference 11

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no resolver link, observed 2026-08-07T15:37:25.785540Z

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source=arxiv_source observed=2026-08-07T15:37:25.785540Z digest=sha256:6ff41146ba6778eeb072094a9e064b5005ed90a0b6f4c8b16b15d6bddb4e934d

Observation e587ec70-73d8-4fe2-9bc2-04b660216276 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 12

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source=arxiv_source observed=2026-08-07T15:37:25.789933Z digest=sha256:a8552b67dfb585fd374019c2f5410f8b1faf2fccd424d0a31cd17b6bb89cd318

Observation 9dab7cdd-f49e-4fbf-b733-b9dc94183f9e · outbound

This paper cites Structuring the Unstructured: A Systematic Review of Text-to-Structure Generation for Agentic AI with a Universal Evaluation Framework.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Structuring the Unstructured: A Systematic Review of Text-to-Structure Generation for Agentic AI with a Universal Evaluation Framework

Reference 13

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verified exact
local_arxiv, observed 2026-08-07T15:37:33.205897Z

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=arxiv_source observed=2026-08-07T15:37:25.794251Z digest=sha256:83839e1806928a154b384b98dd8adcea64858a05a839ab8e8dc3b80e1f54dc6d

Observation bacdce3f-568c-49a5-ae88-18e3e8131156 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 14

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source=arxiv_source observed=2026-08-07T15:37:25.866924Z digest=sha256:eab7da767a01571529cca2ec7c2d6e758df4cb57ffb8241fb99b127fabcb306e

Observation cbfdfc53-e9ef-4cc5-a835-1b4a994e05e0 · outbound

This paper cites GoldCoin: Grounding Large Language Models in Privacy Laws via Contextual Integrity Theory.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning GoldCoin: Grounding Large Language Models in Privacy Laws via Contextual Integrity Theory

Reference 15

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verified exact
local_arxiv, observed 2026-08-07T15:37:32.892279Z

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=arxiv_source observed=2026-08-07T15:37:26.009555Z digest=sha256:42b7056dca3740802ddb0a6d3866735a698320307a9b49229baa5e5a9cd95648

Observation b702bf90-def5-4573-a119-0451594a1add · outbound

This paper cites Bias of AI-Generated Content: An Examination of News Produced by Large Language Models.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Bias of AI-Generated Content: An Examination of News Produced by Large Language Models

Reference 16

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source=arxiv_source observed=2026-08-07T15:37:26.097347Z digest=sha256:4de56934114e0476cd0e55e75ab8b7407a40b831f512a9703ead08f24292228e

Observation 27fb1375-bff2-4cba-a340-09b8db6da751 · outbound

This paper cites LawBench: Benchmarking Legal Knowledge of Large Language Models.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 17

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source=arxiv_source observed=2026-08-07T15:37:26.187600Z digest=sha256:7bda5694ad9baa2574cbdf0ac65ba0720db8d18a1ceda025d15a194e053e6dd5

Observation fef6c64a-e147-43c6-a8b0-824ba5572579 · outbound

This paper cites Operationalizing Contextual Integrity in Privacy-Conscious Assistants.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Operationalizing Contextual Integrity in Privacy-Conscious Assistants

Reference 18

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source=arxiv_source observed=2026-08-07T15:37:26.304358Z digest=sha256:6139610e0f3cac3d55efa579ca7be1d4b4c09b78a41420d63d54c7c77895f9f5

Observation b7a153d4-0757-4f75-a5ea-f25b1c108195 · outbound

This paper cites Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast

Reference 19

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source=arxiv_source observed=2026-08-07T15:37:26.435481Z digest=sha256:6a22c57fe0a0837931879b6d4a765c8cbf471abc3f73886549613c51c0d34867

Observation 067804ab-144d-4d0d-9762-7e1ba74c4a27 · outbound

This paper cites LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models

Reference 20

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source=arxiv_source observed=2026-08-07T15:37:26.528544Z digest=sha256:d89cba3aaa168f1fb77c514ab8ebc325a257cb94981361f117ceb6765f6401b3

Observation 6ba1bf51-3967-4541-bdd5-a3c618b1d5cc · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Measuring Massive Multitask Language Understanding

Reference 21

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no resolver link, observed 2026-08-07T15:37:26.628909Z

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source=arxiv_source observed=2026-08-07T15:37:26.628909Z digest=sha256:0d4c3b6ad895740ae31dabae94ed00a2ba7ce1c67a4e9629fceed8b46ab26d35

Observation a2333286-0158-4099-8106-2cacae11a345 · outbound

This paper cites OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework

Reference 22

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source=arxiv_source observed=2026-08-07T15:37:26.704153Z digest=sha256:830743c6437e083c7f8e75cc62e7b6ee35fce84a4b00ca15123c3bb32c76fff9

Observation ec8375de-bade-4e2e-8ce2-8b5f1a83e83e · outbound

This paper cites an unresolved cited work.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Unresolved cited work

Reference 23

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source=arxiv_source observed=2026-08-07T15:37:26.780649Z digest=sha256:0f677799524566cc626fc53140fcde205d2c718e952895fad387c6a9dcbdeb9a

Observation 4487fc13-7444-4f37-89e3-8d559c0be63a · outbound

This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 24

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source=arxiv_source observed=2026-08-07T15:37:26.913997Z digest=sha256:b1c982eb73b368ef709692d26e35fba1c62fbaede147b95a67150a729479a19b

Observation d1853068-8c23-40ec-bdd7-29e702130f21 · outbound

This paper cites an unresolved cited work.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Unresolved cited work

Reference 25

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source=arxiv_source observed=2026-08-07T15:37:27.029278Z digest=sha256:a3a4628c586acc34b39d4ddd6c89220926067a09c956529b055a32c94d60285b

Observation c59c179e-81a5-45a2-afc1-87ed334df0df · outbound

This paper cites Privacy in Large Language Models: Attacks, Defenses and Future Directions.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Privacy in Large Language Models: Attacks, Defenses and Future Directions

Reference 26

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source=arxiv_source observed=2026-08-07T15:37:27.148812Z digest=sha256:d92b6583395aeab4f666c37c7a9222f0b9f40fdf704b58af3be1ee94725ced9d

Observation 58eb9242-5b8c-4f41-9903-b5fdadd27428 · outbound

This paper cites Privacy Checklist: Privacy Violation Detection Grounding on Contextual Integrity Theory.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Privacy Checklist: Privacy Violation Detection Grounding on Contextual Integrity Theory

Reference 27

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source=arxiv_source observed=2026-08-07T15:37:27.233556Z digest=sha256:103cb1bc2304224aa610c6852a0c79895711ca356d7562efeb0daa3d5b3032bd

Observation f7e18a7c-af09-43e7-a55d-7dc2e77a5963 · outbound

This paper cites Multi-step Jailbreaking Privacy Attacks on ChatGPT.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Multi-step Jailbreaking Privacy Attacks on ChatGPT

Reference 28

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source=arxiv_source observed=2026-08-07T15:37:27.312304Z digest=sha256:10222488e0f90b516d58149b5347dffb3462de9296935b4118e6f072b42cc662

Observation 7ba95d35-7c49-42cb-9484-dd87661f6893 · outbound

This paper cites PrivaCI-Bench: Evaluating Privacy with Contextual Integrity and Legal Compliance.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning PrivaCI-Bench: Evaluating Privacy with Contextual Integrity and Legal Compliance

Reference 29

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source=arxiv_source observed=2026-08-07T15:37:27.419956Z digest=sha256:6f389276d9ae13ae5459e4fd7d8ec645fd3de91ee69d11ee4e80b7fbe750c745

Observation 5980dbd6-2928-4bbf-800a-fc9376c9a236 · outbound

This paper cites DeepInception: Hypnotize Large Language Model to Be Jailbreaker.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning DeepInception: Hypnotize Large Language Model to Be Jailbreaker

Reference 30

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source=arxiv_source observed=2026-08-07T15:37:27.502326Z digest=sha256:49d063b07dd7e634476e2fc4aa19ed955d526d119e04f27b9f5d618628cad55d

Observation 5094c26d-9c13-4d18-bba0-2b2d99d36fcb · outbound

This paper cites Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security

Reference 31

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source=arxiv_source observed=2026-08-07T15:37:27.632302Z digest=sha256:4850a9a2e4efae6c4a7b9f115c573e5cb29a34d9f48e5100eabe54ea7b3060db

Observation b87d7704-760f-4733-9942-2bbf1c04246f · outbound

This paper cites Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimism.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimism

Reference 32

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source=arxiv_source observed=2026-08-07T15:37:27.735776Z digest=sha256:7c4b900aa812ba7d796607f360fb26d02e3af87fab33fc82ab72f2a4960279ef

Observation c30a8834-e4ad-45dd-a616-498d642e8474 · outbound

This paper cites TruthfulQA: Measuring How Models Mimic Human Falsehoods.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning TruthfulQA: Measuring How Models Mimic Human Falsehoods

Reference 33

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source=arxiv_source observed=2026-08-07T15:37:27.835124Z digest=sha256:5799d18740d1d9def116eaee589f583932df72dd279274a6353e4835c535a917

Observation aa9fa9bf-f5d7-4496-8632-368ff503d553 · outbound

This paper cites Prompt Injection attack against LLM-integrated Applications.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Prompt Injection attack against LLM-integrated Applications

Reference 34

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source=arxiv_source observed=2026-08-07T15:37:27.924319Z digest=sha256:84178af30072cdc5b9864d4af51c4cabf3afac0ab4fcf841f4f993fe3afffe62

Observation 3d6c3987-3ffe-4eb9-9cc3-45ea47f9aea6 · outbound

This paper cites Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory

Reference 35

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source=arxiv_source observed=2026-08-07T15:37:28.028759Z digest=sha256:397e48f597b941346cd2a5fb20065f8627f2d698b252a39968b25a9e4ca4f71b

Observation 11479c46-247c-49e9-a952-b96ccdbb76b9 · outbound

This paper cites an unresolved cited work.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Unresolved cited work

Reference 36

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raw_fallback, observed 2026-08-07T15:37:34.235599Z

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=arxiv_source observed=2026-08-07T15:37:28.162230Z digest=sha256:bb52388520cb63c55cb1ac05f10323a08e98707686896e08371c4364e7777efd

Observation de1ba10a-b695-469b-8824-53816953cf6f · outbound

This paper cites GPT-4o System Card.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning GPT-4o System Card

Reference 37

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source=arxiv_source observed=2026-08-07T15:37:28.278624Z digest=sha256:6399694c27fa9160d019ca6ecee7a6f8b0a4050d3b7b5b317b7d1fb10c9b2011

Observation 62b6b9ae-bcd5-4c87-8601-37f27a930680 · outbound

This paper cites an unresolved cited work.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Unresolved cited work

Reference 38

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raw_fallback, observed 2026-08-07T15:37:34.042678Z

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=arxiv_source observed=2026-08-07T15:37:28.400443Z digest=sha256:799909ffef2e4173c134e73b828e2551fd67e921711443d1b9e68eb2b6b03348

Observation 6618858b-b737-4f8a-92d8-c33b401ca31a · outbound

This paper cites Training language models to follow instructions with human feedback.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Training language models to follow instructions with human feedback

Reference 39

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source=arxiv_source observed=2026-08-07T15:37:28.515613Z digest=sha256:e717cb842fb190d9e7b996b7ef8a2e1f027cfa1bdb115406bf139f781efc1002

Observation 486809dd-1a11-4bb1-8fa9-8b0e89c82e63 · outbound

This paper cites Brendan McMahan, Sergei Vassilvitskii, Steve Chien, and Abhradeep Guha Thakurta.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Brendan McMahan, Sergei Vassilvitskii, Steve Chien, and Abhradeep Guha Thakurta

Reference 40

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source=arxiv_source observed=2026-08-07T15:37:28.688518Z digest=sha256:e8b71b438b1a8289d3cbbbc8c8db9ad18b7819ccd92a8678832822e2a45b6d12

Observation 5cb2798a-9944-4a40-8031-4ef46e772760 · outbound

This paper cites Qwen2.5 Technical Report.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Qwen2.5 Technical Report

Reference 41

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source=arxiv_source observed=2026-08-07T15:37:28.876330Z digest=sha256:23ec07f9d89f512b71489779fe5e5a07d47e079d54dca1b5f27d7a8b61735129

Observation f3a04e38-52b1-4441-8be7-adac42b2cf39 · outbound

This paper cites WinoGrande: An Adversarial Winograd Schema Challenge at Scale.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning WinoGrande: An Adversarial Winograd Schema Challenge at Scale

Reference 42

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no resolver link, observed 2026-08-07T15:37:29.013764Z

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source=arxiv_source observed=2026-08-07T15:37:29.013764Z digest=sha256:1036468c64ee4e077c6e2b2c06e3a2cf8bf280ad3a769113bc9308751f48dcc0

Observation 62e3c68a-c131-4125-af26-f5768d6306aa · outbound

This paper cites Trust Region Policy Optimization.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Trust Region Policy Optimization

Reference 43

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source=arxiv_source observed=2026-08-07T15:37:29.124059Z digest=sha256:008306f5181425010e86af9006f7d547481fc8f0bbabe0fd43c0f4be5de8ba10

Observation 92e376a2-5fe9-4744-831c-413a80925506 · outbound

This paper cites High-Dimensional Continuous Control Using Generalized Advantage Estimation.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 44

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source=arxiv_source observed=2026-08-07T15:37:29.274966Z digest=sha256:2e583c0a8f8af7d05353cc16b78b6462643ed3d50d87518b79882ea811edbee7

Observation 66cd6366-c2e6-4c65-8bf3-be3220eeb346 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 45

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source=arxiv_source observed=2026-08-07T15:37:29.386957Z digest=sha256:18bf02f5c18fb614cf1cca54990a6f1c583757df50824756e5993e9c8ec2819b

Observation 1576fe6c-af4c-432b-af4e-5c1b6d7860b0 · outbound

This paper cites Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks

Reference 46

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source=arxiv_source observed=2026-08-07T15:37:29.522948Z digest=sha256:954cfafb90f81c91128d47224906d210dce88911d571be452e4819363594ccac

Observation eb02cbac-84df-4a97-b20f-a9093090f566 · outbound

This paper cites "Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning "Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models

Reference 47

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source=arxiv_source observed=2026-08-07T15:37:29.632571Z digest=sha256:9ecb08091feba1d0f43925427bf67ac8595fd07e6e099cd27b9339ceb3cdc7e5

Observation c1636e9e-1bc9-45b0-b391-92f2a876e4e8 · outbound

This paper cites INFERENCEDYNAMICS: Efficient Routing Across LLMs through Structured Capability and Knowledge Profiling.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning INFERENCEDYNAMICS: Efficient Routing Across LLMs through Structured Capability and Knowledge Profiling

Reference 48

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verified exact
local_arxiv, observed 2026-08-07T15:37:32.326115Z

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=arxiv_source observed=2026-08-07T15:37:29.724188Z digest=sha256:4654c3eea780a52d01f12651f1a099e7daf3a4111fd85bc4980dfc4308678a02

Observation 4c6097ab-0a34-4a5b-9dee-9d50b7b73b76 · outbound

This paper cites Membership Inference Attacks against Machine Learning Models.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Membership Inference Attacks against Machine Learning Models

Reference 49

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source=arxiv_source observed=2026-08-07T15:37:29.827094Z digest=sha256:95f53ed935b7d9bbe2c7be2123e2f9fcffe7695a08b6c9597502dd8ae5c27565

Observation fa043073-fcc7-4bcc-a37c-2c236a655372 · outbound

This paper cites an unresolved cited work.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Unresolved cited work

Reference 50

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verified exact
raw_fallback, observed 2026-08-07T15:37:32.205258Z

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=arxiv_source observed=2026-08-07T15:37:29.969859Z digest=sha256:0e55ead3bf71029f97989f39a6e0ce312eb1fd8eb94b9722ef588e44c1986ded

Observation 6d6c5988-c25c-4d7a-9a8e-699ac05660b6 · outbound

This paper cites Certified Defenses for Data Poisoning Attacks.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Certified Defenses for Data Poisoning Attacks

Reference 51

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source=arxiv_source observed=2026-08-07T15:37:30.109588Z digest=sha256:9c0ea5ab5ab7b50c3ebe226da602298ff2a5b6a1bb02b2da219f12774399cb7e

Observation a820e140-31ed-415a-bd95-f9abb0ac5a3b · outbound

This paper cites Data Poisoning Attacks Against Federated Learning Systems.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Data Poisoning Attacks Against Federated Learning Systems

Reference 52

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verified exact
local_arxiv, observed 2026-08-07T15:37:31.937855Z

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=arxiv_source observed=2026-08-07T15:37:30.222364Z digest=sha256:36218e541858c2ad902934de88fd146f5fe725c7a200b8f5c175e180c2943829

Observation b1eb8f5e-018f-4d87-a30f-b8e88e93bda9 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning LLaMA: Open and Efficient Foundation Language Models

Reference 53

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source=arxiv_source observed=2026-08-07T15:37:30.290138Z digest=sha256:a1593fb058dfc23f8aa095c33dca31c149883d53ac19d7586fc68a430a3e2509

Observation a4b6069e-05b6-4e2b-b0f4-b60cb5c7be29 · outbound

This paper cites an unresolved cited work.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Unresolved cited work

Reference 54

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source=arxiv_source observed=2026-08-07T15:37:30.379542Z digest=sha256:65fe4b9fcc9855977d9c5df0773adb6506bcf8772b23e6c4d5ccb76f7460c004

Observation 1fbee1af-5bd7-48d0-a783-857fd091681a · outbound

This paper cites Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations

Reference 55

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no resolver link, observed 2026-08-07T15:37:30.498244Z

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source=arxiv_source observed=2026-08-07T15:37:30.498244Z digest=sha256:d76ba814385887a56bf833901c5d50a5c92aedafef7d63f28d79ca903221cb81

Observation bbcee3d7-8de2-4d4f-a310-df21ca0b17e2 · outbound

This paper cites Efficient Adversarial Training in LLMs with Continuous Attacks.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 56

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source=arxiv_source observed=2026-08-07T15:37:30.568678Z digest=sha256:9daa43546c0c7e1d126b026c957f2476c5bb4a0d0af57f99953b633801219845

Observation 90cd7ff6-f1eb-4947-b4cd-1eaf29f02015 · outbound

This paper cites The Rise and Potential of Large Language Model Based Agents: A Survey.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning The Rise and Potential of Large Language Model Based Agents: A Survey

Reference 57

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:37:30.637518Z digest=sha256:3871f39dcbc936846038f2134569fad259a2ecd8e76fac7352678911aad998f7

Observation 69f8b6ff-4719-4c93-b8b6-64d6c4e0eca4 · outbound

This paper cites Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning

Reference 58

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no resolver link, observed 2026-08-07T15:37:30.734019Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T15:37:30.734019Z digest=sha256:8ae6223ddc95491a0a270e88e70ee2c7f84915e16db45cd0d2bf187b709784db

Observation 04bd2685-fe14-4ac5-a7de-b0ab2e454d5e · outbound

This paper cites an unresolved cited work.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Unresolved cited work

Reference 59

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no resolver link, observed 2026-08-07T15:37:30.835377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:37:30.835377Z digest=sha256:44888321882f65eae84fe3990502d0e51a944089e8caa089320c3171c6f678a2

Observation 39ef9557-10bf-46a0-a162-fdd838650712 · outbound

This paper cites an unresolved cited work.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Unresolved cited work

Reference 60

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source=arxiv_source observed=2026-08-07T15:37:30.925687Z digest=sha256:86afc02db98117c143c41fb2246456e4a3fee79a48b6a2e3c60e7fd860a6131c

Observation c7e0e76c-dfb0-42dd-a0ac-40850cb5cca2 · outbound

This paper cites Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model

Reference 61

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no resolver link, observed 2026-08-07T15:37:31.014205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:37:31.014205Z digest=sha256:efe788bb77ad95faf90eaa52c371e28fadbf37c0b34b737d953511bd2238cc90

Observation bde7067d-2eb5-44ca-bf9c-a58bf81fefe1 · outbound

This paper cites Differentially Private Fine-tuning of Language Models.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Differentially Private Fine-tuning of Language Models

Reference 62

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no resolver link, observed 2026-08-07T15:37:31.106379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:37:31.106379Z digest=sha256:432aea1c3a6aa2fdeed8b5954640347c53ff1e992d4bcff385b6a5a84ae39807

Observation fd6fddfe-7dd6-4593-9f8e-389c59ea9d33 · outbound

This paper cites an unresolved cited work.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Unresolved cited work

Reference 63

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:37:31.194994Z digest=sha256:a50006e41020565cbf28e1f403e40cb229e29332058bf24b4f5743fb3cec770f

Observation 97a2a604-06e6-4a7c-ba26-a760461be9bd · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 64

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:37:31.261817Z digest=sha256:c26739e1c8163943ed568944cf505e5ceb389c954576ad296b20d74f790a9993

Observation 1563a4df-d57c-4a8b-a89d-2a75f427ff5f · outbound

This paper cites online" 'onlinestring :=.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning online" 'onlinestring :=

Reference 65

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no resolver link, observed 2026-08-07T15:37:31.367911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:37:31.367911Z digest=sha256:9c5ec2219fdba2bbcae04ecb03f82b733715e7508e194bec65681e053d4fdb0b

Observation 2c0c20cf-47b3-4045-9497-cdbe27181b09 · outbound

This paper cites write newline.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning write newline

Reference 66

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no resolver link, observed 2026-08-07T15:37:31.442193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:37:31.442193Z digest=sha256:02d339e571e7aa3e8a78826a674e14d54c88568a1c4a26a51528c8f4df03b90d

Pith citing papers

Observation 48e6a4e1-d5b3-4f4b-bdc1-1603a6fae1b6 · inbound

HKGAI-V1: Towards Regional Sovereign Large Language Model for Hong Kong cites this paper.

HKGAI-V1: Towards Regional Sovereign Large Language Model for Hong Kong Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning

Reference 21

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verified exact
local_arxiv, observed 2026-08-06T17:38:20.745079Z

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=2026-08-06T17:38:15.928177Z digest=sha256:ad88e799305a451aa30a691b2ba7f3257cf76f10f929eec6ee16d1577f9cec9c

Observation b83fe0b0-dcaa-4c11-b003-c3021ae15ad2 · 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 Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning

Reference 156

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no resolver link, observed 2026-08-05T10:39:07.039355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:39:07.039355Z digest=sha256:71274d72b91b5161bffbdd72e39f0f7a09b431134c41fb5ff9e70e184f930d5c