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Paper Citation Record · LEDGER

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs

As of 18 August 2026, this Paper Citation Record lists 100 of 300 outbound references and 0 inbound Pith citation observations for arXiv:2607.03561.

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

pith.paper-citation-record.v1
2607.03561 v1

Coverage vector

measured 100 of 300 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T01:34:45.323277Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

100 of 300 outbound references displayed

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  • verified fuzzy0
  • unresolved100
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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Outbound references

Observation c09b2296-df50-4441-86d4-f22ccdec75ad · outbound

This paper cites Proceedings of the 41st International Conference on Machine Learning , pages=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Proceedings of the 41st International Conference on Machine Learning , pages=

Reference 1

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:0e8571dc920d51313a5f124b4d1112e26ee2a9901c530b0587b970cbcd732d1f

Observation 1e8c4855-9a8d-4fc8-b678-98bf86b19bfd · outbound

This paper cites AI safety via debate.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs AI safety via debate

Reference 2

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:b6d4893ff9ddac9ee6537a0c72a633cca73e1c87d982b9fe9a4adf43fc0172b4

Observation 838e1ac5-d873-4f93-8c28-77023b7fdd42 · outbound

This paper cites Avoiding Obfuscation with Prover-Estimator Debate.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Avoiding Obfuscation with Prover-Estimator Debate

Reference 3

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:d4a4ce588203a3c2f8f181c3e01d2b17efcf99dd239aef5755ed821bbbdd7cb8

Observation 728c425f-07fe-443b-98f3-dfb4b839a690 · outbound

This paper cites An alignment safety case sketch based on debate.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs An alignment safety case sketch based on debate

Reference 4

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:ac57975c99da2ad2bab43aab89cf7475fc8af8e8753f1a0c1f99f08c76620253

Observation 7c7702fa-57df-497f-a8f6-397bc8f9f242 · outbound

This paper cites Supervising strong learners by amplifying weak experts.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Supervising strong learners by amplifying weak experts

Reference 5

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:f98aac579f3fd9e3827a5020360cb82b4ac3d59b9126714a8f6f1b6bc645ecd9

Observation fcaf0638-9baf-4b6f-ba54-6d5a5ed255e1 · outbound

This paper cites Scalable agent alignment via reward modeling: a research direction.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Scalable agent alignment via reward modeling: a research direction

Reference 6

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Observation eda47fe1-6cd3-49e5-84d2-b0b999ad3924 · outbound

This paper cites arXiv preprint arXiv:2405.15722 , year=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs arXiv preprint arXiv:2405.15722 , year=

Reference 7

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Observation 015756c0-d47b-4743-82ee-262561cbdc22 · outbound

This paper cites Neural Interactive Proofs.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Neural Interactive Proofs

Reference 8

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:0ccdeea94223cf9165b3c8a8c1073a22725d772d3b6f59e374cc0e952a8033af

Observation d75fdfcd-475d-4d3e-9385-a6d4fd019261 · outbound

This paper cites arXiv preprint arXiv:2410.08864 , year=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs arXiv preprint arXiv:2410.08864 , year=

Reference 9

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Observation 9adf0a7d-5438-4598-9a42-50946701fb78 · outbound

This paper cites Learning to Give Checkable Answers with Prover-Verifier Games.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Learning to Give Checkable Answers with Prover-Verifier Games

Reference 10

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:7e3694cfb1f1bddd45a2f5fa7182ff107d2dda4ea8d0bd11e2212802b85abf47

Observation d56fe3f5-b33d-4020-867f-5579795df7e1 · outbound

This paper cites 2024 , eprint=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs 2024 , eprint=

Reference 11

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:2419cd34417c2813651fa56c41bea9c212e064028cea4ea5ea7d0a18708ca74c

Observation c6bb3969-3f35-4845-9ea6-b0113ad472b7 · outbound

This paper cites Prover-Verifier Games improve legibility of LLM outputs.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Prover-Verifier Games improve legibility of LLM outputs

Reference 12

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Observation 310374a9-addc-476a-a9f5-cb637cfcbfe8 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Advances in Neural Information Processing Systems , volume=

Reference 13

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:cf17c78351cce467717079b69d856f394c5b68ca74187d42fa840b4d5b211829

Observation 80a56620-8aac-4f65-9014-275c53e7c094 · outbound

This paper cites Why Language Models Hallucinate.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Why Language Models Hallucinate

Reference 14

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:d2db9680476680a3fc55e020da6a79d891c9319fa4d529620dab0e73f91dfc98

Observation f66c1c1d-f355-42e0-9993-d0e97b9a40c2 · outbound

This paper cites Hallucination is Inevitable: An Innate Limitation of Large Language Models.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Hallucination is Inevitable: An Innate Limitation of Large Language Models

Reference 15

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:d759a9dacd27db5a64f7887455e4f0a479afb5cba97071dd05c7504509b501ab

Observation 8876ec61-ee07-4589-87f9-c273ae00f735 · outbound

This paper cites Findings of the Association for Computational Linguistics: EACL 2024 , pages=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Findings of the Association for Computational Linguistics: EACL 2024 , pages=

Reference 16

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:ae167d6d1383f68e6c938e482934715406e7a8f78e8b1976cc42082b6c7b9161

Observation 2cebb91a-2087-4052-a83f-eebe9b816bef · outbound

This paper cites Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models

Reference 17

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:6d8c81f11f48285487818d647ed46384180a9322af01e5136df053b36d46181c

Observation e6760f9a-430f-4eab-a449-805382435cba · outbound

This paper cites The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models

Reference 18

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Observation ddc3f4a8-4076-4478-a108-f3cdbe66c9c4 · outbound

This paper cites Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

Reference 19

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Observation 26c577bd-0c9f-4934-a409-54ef986312b8 · outbound

This paper cites arXiv preprint arXiv:2509.15541 , year=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs arXiv preprint arXiv:2509.15541 , year=

Reference 20

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Observation 743c23ad-6d91-4fb6-8d21-53394d1ef0fe · outbound

This paper cites Frontier Models are Capable of In-context Scheming.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Frontier Models are Capable of In-context Scheming

Reference 21

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Observation 4a625bad-60fc-4c4a-b6f1-0107e78a4a88 · outbound

This paper cites Journal of the ACM (JACM) , volume=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Journal of the ACM (JACM) , volume=

Reference 22

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Observation ee1bf300-9f7f-49f7-b311-7e54ecc81022 · outbound

This paper cites Proceedings of the forty-eighth annual ACM symposium on Theory of Computing , pages=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Proceedings of the forty-eighth annual ACM symposium on Theory of Computing , pages=

Reference 23

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Observation a1abcd86-41d5-4a72-ac62-ba4f522edebc · outbound

This paper cites 2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS) , pages=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs 2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS) , pages=

Reference 24

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Observation 6e91e02b-8738-4615-813e-d162bcd2986a · outbound

This paper cites 2025 , eprint=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs 2025 , eprint=

Reference 25

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This paper cites Proceedings of the forty-fifth annual ACM symposium on Theory of computing , pages=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Proceedings of the forty-fifth annual ACM symposium on Theory of computing , pages=

Reference 26

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How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Theory of Cryptography Conference , pages=

Reference 27

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How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs 2025 , month =

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How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs 2020 , month =

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This paper cites Proceedings of the twenty-ninth annual ACM symposium on Theory of computing , pages=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Proceedings of the twenty-ninth annual ACM symposium on Theory of computing , pages=

Reference 30

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Observation 0b4cbdf2-f3d0-4c10-aec6-4c7730b7dbb8 · outbound

This paper cites Proceedings of the 4th conference on Innovations in Theoretical Computer Science , pages=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Proceedings of the 4th conference on Innovations in Theoretical Computer Science , pages=

Reference 31

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How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Information and Computation , volume=

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How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Unresolved cited work

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How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Journal of the ACM (JACM) , volume=

Reference 34

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How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Unresolved cited work

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How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs SIAM Journal on Computing , volume=

Reference 36

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How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Proceedings of the twenty-fourth annual ACM symposium on Theory of computing , pages=

Reference 37

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Observation ab96eb58-78f6-4926-86ae-f944be22973b · outbound

This paper cites Zaverucha and Ian Goldberg , editor =.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Zaverucha and Ian Goldberg , editor =

Reference 38

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:3c2e8c510c9a84bc9e66222071348a45ac00aea762b2ea4bfddad4742ce6d3ad

Observation 3aa7e7bc-3a7a-4304-963c-d3436feb2f0d · outbound

This paper cites Transactions of the Association for Computational Linguistics , volume=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Transactions of the Association for Computational Linguistics , volume=

Reference 39

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:4ddf2269a067bab09191d29bb0c8c5150ceb9cbeb4bbc4ebb4bb84e34d42a32e

Observation 45f85804-8432-4ae3-bf84-12e0190a298d · outbound

This paper cites The Knowledge Complexity of Interactive Proof-Systems (Extended Abstract) , booktitle =.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs The Knowledge Complexity of Interactive Proof-Systems (Extended Abstract) , booktitle =

Reference 40

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:9995652a21475335d013f8cba6e787f27ae8579825e0024d8f84d335016204bb

Observation 649e314d-8da4-4e99-af49-dbdfac93a599 · outbound

This paper cites Trading Group Theory for Randomness , booktitle =.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Trading Group Theory for Randomness , booktitle =

Reference 41

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:a702a417bcc6e024750da05cbe493e43f755a02fc433a5edb834cc31bd9829b3

Observation a246fda5-2a16-46f1-bed6-a4c96d412083 · outbound

This paper cites an unresolved cited work.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Unresolved cited work

Reference 42

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:c99791f46b77ddba66b7e55263f7bb4aa56991710c869e9ef6619d128925985b

Observation 11b79b08-5aca-4a0d-8cbc-01612323130c · outbound

This paper cites Annual Cryptology Conference , pages=.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Annual Cryptology Conference , pages=

Reference 43

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:18f74338ebd6313e24c704a0d45ca6e389dc1d5195ebf134bde249ad7a75a65f

Observation de2785e4-50d0-4e89-a211-a40aa3b2b743 · outbound

This paper cites Foundations and Trends.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Foundations and Trends

Reference 44

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:64185b44a6ae872c76da8da608dcfffb9d23109ba18fa784241e130ca83e26eb

Observation ed39ee35-3f67-4acb-95b2-4ad77d72ed44 · outbound

This paper cites Forgery Attacks on SipHash.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Forgery Attacks on SipHash

Reference 45

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:00c13ef76cfcf154cdb18e2c5900abe95b60a6f827b964cc5130847b29aba834

Observation ee30b804-eacb-4969-be31-3c4005df2411 · outbound

This paper cites Cryptanalysis of Fruit- F : Exploiting Key-Derivation Weaknesses and Initialization Vulnerabilities.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Cryptanalysis of Fruit- F : Exploiting Key-Derivation Weaknesses and Initialization Vulnerabilities

Reference 46

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:f4a38d89d637d6fd15063293982ae7adf53f2763fbb9deaecd4c8b5ec6d1f219

Observation a57338de-6c5d-4d8d-8b05-611b40984240 · outbound

This paper cites Exploring Key-Recovery-Friendly Differential Distinguishers for SM4 and Their Performance in Differential Attacks.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Exploring Key-Recovery-Friendly Differential Distinguishers for SM4 and Their Performance in Differential Attacks

Reference 47

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:cc1d22c6ee62239b3c5b7c24cbfd5ddb26facfbb3d47b3519430974bf25dcc2a

Observation 136884d5-b8b8-41b6-9da0-444ba422ada3 · outbound

This paper cites Inner Product Masked Integral Distinguishers and Integral Sets over Large Finite Fields - Applications to MiMC , CIMINION and Chaghri.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Inner Product Masked Integral Distinguishers and Integral Sets over Large Finite Fields - Applications to MiMC , CIMINION and Chaghri

Reference 48

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:d5f82ae944101a602c45bcb57877e858e3b856de071be84190a42d6bee4a0388

Observation 0405de39-532d-4701-bb0a-590c703892d0 · outbound

This paper cites Improved Differential Meet-in-the-Middle Cryptanalysis on SIMON and Piccolo.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Improved Differential Meet-in-the-Middle Cryptanalysis on SIMON and Piccolo

Reference 49

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:92eb38c28a67f2c86e11b743bbbeeadf6699540d6374ea8d0df1ab61f0704481

Observation 3cfa7a86-09f9-4e67-be96-ab6adba83f85 · outbound

This paper cites Strengthening Key Scheduling of AES -256 with Minimal Software Modifications.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Strengthening Key Scheduling of AES -256 with Minimal Software Modifications

Reference 50

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:42b65a2aeaedddbda35b19a76511ad9b041e7a8288dba371f1397adafc3b65e0

Observation 043e6158-f92c-4bd8-bb19-42a8c06ade0a · outbound

This paper cites Ideal Transformations for Public Key Encryption.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Ideal Transformations for Public Key Encryption

Reference 51

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:f696fd8285dc2fb187b4a5eff92e8b61860c97c80183f36bb8029e455604126c

Observation 9dbbc8bd-8539-4459-9ca1-7cb3da449146 · outbound

This paper cites Indifferentiability Separations in Ideal Public Key Encryption: Explicit vs.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Indifferentiability Separations in Ideal Public Key Encryption: Explicit vs

Reference 52

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:4c82fb0f85df0fc71f6f825f20dfad312d0016644ffe3ed2d32827aec9dcd4d0

Observation beb0f0c1-b311-49ee-a88b-2de782e723e6 · outbound

This paper cites Compressed Sigma Protocols: New Model and Aggregation Techniques.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Compressed Sigma Protocols: New Model and Aggregation Techniques

Reference 53

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:66cfbc9bb1dda0e85b9d96f392370eac10abd0a55784e24e0d954cae192e9bbc

Observation 6f44f560-047c-49b7-871b-7883b916f162 · outbound

This paper cites Glitter : A Fully Adaptive and Tightly Secure Threshold Signature.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Glitter : A Fully Adaptive and Tightly Secure Threshold Signature

Reference 54

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:90d6bd549225d797d6ee2f705d5a688b3fdb75e6989e2ebcb1900c272243d85b

Observation faa6edd4-2b27-4f46-914b-8ddacb7ba24b · outbound

This paper cites Faster VOLEitH Signatures from All-But-One Vector Commitment and Half-Tree.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Faster VOLEitH Signatures from All-But-One Vector Commitment and Half-Tree

Reference 55

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:f5a7659882aad6b2a0145bfcc52b7fa6106285a1bc9fd11ef132f50d7a892585

Observation bf58db56-c825-4c10-95cc-92cd98525648 · outbound

This paper cites Three-Round (Robust) Threshold ECDSA from Threshold CL Encryption.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Three-Round (Robust) Threshold ECDSA from Threshold CL Encryption

Reference 56

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:3ac0d1f29de15675861991490cf069c6f833c541cfcfc3d7c27c560067d462de

Observation c130917a-8765-4661-883b-d901fcbfb031 · outbound

This paper cites Lattice Attack with EHNP : Key Recovery from Two ECDSA Signatures and Breaking the Information-Theoretic Limit.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Lattice Attack with EHNP : Key Recovery from Two ECDSA Signatures and Breaking the Information-Theoretic Limit

Reference 57

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:32a1c5bd77961fbf770fbbcbef9c003fc5274ae36b84c2dbaff740ecd0a63118

Observation 48924546-c045-4fe3-9639-4366ebd1aff9 · outbound

This paper cites FlexiADKG : A Flexible Asynchronous Distributed Key Generation Protocol with Constant Round Complexity.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs FlexiADKG : A Flexible Asynchronous Distributed Key Generation Protocol with Constant Round Complexity

Reference 58

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:39b9be640207d167a25208f6dfbdbdfc9ec6e9abf4892acabeb36684adae8596

Observation 0912ff96-50e1-4315-a1b7-851b5b0918c8 · outbound

This paper cites TEAKEX : TESLA -Authenticated Group Key Exchange.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs TEAKEX : TESLA -Authenticated Group Key Exchange

Reference 59

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:aa23dedbacec2a83411aa5e4bcf4ba65595e63d363c22a0d2696bbb2d3245d09

Observation cca7a3fa-1a1a-4826-a351-3649f93de878 · outbound

This paper cites Liu and Shirui Pan and Tsz Hon Yuen.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Liu and Shirui Pan and Tsz Hon Yuen

Reference 60

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:5ae3c9be484edc32c6b0a3920b3c47dbb7c0c6a99e9e1172720b6307d112122a

Observation 2623b188-0c14-4523-8c93-b852a18e985a · outbound

This paper cites Advanced Temporal Graph Embedding for Detecting Fraudulent Transactions on Complex Blockchain Transactional Networks.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Advanced Temporal Graph Embedding for Detecting Fraudulent Transactions on Complex Blockchain Transactional Networks

Reference 61

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:40ba71750c26f91049a9b7533f604825959196e857871a9232729d9a12429bba

Observation 39d6e79a-c4e3-425c-a8ea-81cb146765a7 · outbound

This paper cites Walnut: A Generic Framework with Enhanced Scalability for BFT Protocols.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Walnut: A Generic Framework with Enhanced Scalability for BFT Protocols

Reference 62

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:9030d22862914099efbe176a72b767300907549f62e67075290cb23c8e162e24

Observation b9ef5426-da72-4bab-9f1f-55d8f9ea92df · outbound

This paper cites PPSCCC : Privacy-Preserving Scalable Cross-Chain Communication Among Multiple Blockchains Based on Parent-Child Blockchain.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs PPSCCC : Privacy-Preserving Scalable Cross-Chain Communication Among Multiple Blockchains Based on Parent-Child Blockchain

Reference 63

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:0f6424fa880a194920bdcc45309ba9335ddbdd34447f0664cb77dd6c20609a67

Observation 7f1f2fbe-1059-40c3-a565-cbdf0088232c · outbound

This paper cites Towards Quantum Security of Hirose Compression Function and Romulus- H.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Towards Quantum Security of Hirose Compression Function and Romulus- H

Reference 64

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:8ef183f1f740188333dc2d6582275a565e2965e3eb929fee088a898ec5b9f367

Observation 96d80807-82a4-4a3f-bb17-ae8e9df955c6 · outbound

This paper cites Efficient Multi-instance Vector Commitment and Application to Post-quantum Signatures.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Efficient Multi-instance Vector Commitment and Application to Post-quantum Signatures

Reference 65

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:96e13461176888230a7b214c6f81e9b90db824459e10424e394c94caea26677a

Observation acf16fea-34bf-4bd2-8adb-0284c0dde5d5 · outbound

This paper cites Breaking the Shield: Novel Fault Attacks on CRYSTALS -Dilithium.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Breaking the Shield: Novel Fault Attacks on CRYSTALS -Dilithium

Reference 66

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:c6274ae117ae965d039b160a024c55c755d6504b3a01d26f115e5fcc7f65d0a6

Observation c7330cc4-b19c-482d-96d7-d5d462690bff · outbound

This paper cites Efficient Revocable Identity-Based Encryption from Middle-Product LWE.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Efficient Revocable Identity-Based Encryption from Middle-Product LWE

Reference 67

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:ec9f4c30ed5021600b9cb6f061057bd21f9441e183cdd13835b5759bb04aeb2b

Observation 55bd5bd5-b6da-4cc6-9e6f-ccc327298843 · outbound

This paper cites Code-Based Fully Dynamic Accountable Ring Signatures and Group Signatures Using the Helper Methodology.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Code-Based Fully Dynamic Accountable Ring Signatures and Group Signatures Using the Helper Methodology

Reference 68

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:2217a36f02a9f4d91328046e4f1b2e8eda6a90a30b3a3d06ddf3e439b1a24343

Observation 6c54de36-61af-45e5-8614-322b1215f87e · outbound

This paper cites Partial Key Exposure Attacks on UOV and Its Variants.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Partial Key Exposure Attacks on UOV and Its Variants

Reference 69

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:d635ed4ff74dd834f38d9359235fa65ed3f4bb434bc2d204f978a838581ffacf

Observation 5ddb31ce-4c6b-4d7f-a969-5d0989f466bd · outbound

This paper cites Unbounded Multi-hop Proxy Re-encryption with HRA Security: An LWE -Based Optimization.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Unbounded Multi-hop Proxy Re-encryption with HRA Security: An LWE -Based Optimization

Reference 70

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:5f0fe3455a7bd51543df80b3b1b086e7136a37222800920b2cc8cf97a60f495a

Observation 7b7c0e0f-68a1-4066-bd01-07c22cc1efe4 · outbound

This paper cites Fiat-Shamir with Rejection and Rotation.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Fiat-Shamir with Rejection and Rotation

Reference 71

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:32c306ee4f6744d0c03fe46fbd8bd39436645e461d9bf107ef977a7db807edd3

Observation d5bcec41-c8e6-4d32-b5b2-99a1de90243f · outbound

This paper cites Amoeba: More Flexible RLWE -Based KEM.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Amoeba: More Flexible RLWE -Based KEM

Reference 72

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:e6b5962d1c47a74d80ca9fb33d4e4045812b8b6381e60996fbb7d1180f3b9d70

Observation bdb7f981-c539-4a5d-8702-b288a717e679 · outbound

This paper cites Get Rid of Templates: A Chosen-Ciphertext Attack on ML - KEM with a DPA -Based Self-comparison Oracle.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Get Rid of Templates: A Chosen-Ciphertext Attack on ML - KEM with a DPA -Based Self-comparison Oracle

Reference 73

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:38137e325acba0314e55a3081826eeb1877c9e802ff8b6e34668fd76e8ca4b20

Observation 3050a2fd-e4b4-4a7d-8978-d48267d1b961 · outbound

This paper cites Accountability for Server Misbehavior in Homomorphic Secret Sharing.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Accountability for Server Misbehavior in Homomorphic Secret Sharing

Reference 74

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:b5397e246685a7fd4641f5d2dcf94d66e1217802dc515057ec73c9f8b6c59a18

Observation ed9f52e2-ddbf-4dab-9430-cb9f89b11372 · outbound

This paper cites Jiang and Jingjing Fan and Man Ho Au and Siu Ming Yiu.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Jiang and Jingjing Fan and Man Ho Au and Siu Ming Yiu

Reference 75

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:01b18a70e9dd761782b25ae57db26f37b0715bd8fab7994596221e60ed5be685

Observation ab28f6bf-1089-4530-b1ce-e7bebe28cccc · outbound

This paper cites Refined Error Management for Gate Bootstrapping.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Refined Error Management for Gate Bootstrapping

Reference 76

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:f61bcb83aff9ccd19b675b9e8ef41ba1c869b89bad00babe8d7d2cb7667a784f

Observation 63962e71-f54a-4109-9692-a2e939f05d5f · outbound

This paper cites Compact Lifting for NTT -Unfriendly Modulus.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Compact Lifting for NTT -Unfriendly Modulus

Reference 77

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:85e330779a438053b50af63acf8809dcab5f114b598c94d1aa3d581fad9b715f

Observation e9ab5e7a-24a4-4df2-844a-1cf1a1b2f72e · outbound

This paper cites Guaranteed Termination Asynchronous Complete Secret Sharing with Lower Communication and Optimal Resilience.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Guaranteed Termination Asynchronous Complete Secret Sharing with Lower Communication and Optimal Resilience

Reference 78

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:d819beff449a7b5bcb0092b30d987a076e32f68e91d39c05d6d02fd455881372

Observation af310697-76a7-4922-bc31-2c98370e3349 · outbound

This paper cites Solving Generalized Approximate Divisor Multiples Problems.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Solving Generalized Approximate Divisor Multiples Problems

Reference 79

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:2f9bf8fb6c1f9f1bb3efaae3eb1458e6f4b1aafc3a6da8e9ddaf9bb1702634da

Observation 548c0f3d-e886-4d50-9be6-a5f8de1f7860 · outbound

This paper cites Comparing and Improving Frequency Estimation Perturbation Mechanisms Under Local Differential Privacy.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Comparing and Improving Frequency Estimation Perturbation Mechanisms Under Local Differential Privacy

Reference 80

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:6b9d7f8469e6db20247b663ceda517cf2e541e27b19a0a6abd985ccbb8b4e0d1

Observation de3f08cf-c7d2-429d-b52c-5b50d5c3750f · outbound

This paper cites Strong Federated Authentication With Password-Based Credential Against Identity Server Corruption.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Strong Federated Authentication With Password-Based Credential Against Identity Server Corruption

Reference 81

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:b67f6d69831d30a1900561d075c4f9c5256d47ab8c14ffe912ea8ebf2519b93b

Observation b1b21127-66dc-4153-8f07-4585fd8597bd · outbound

This paper cites Anonymous Credentials with Credential Redaction and Its Application to SSI -Based Plug& Charge for Shared Vehicles.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Anonymous Credentials with Credential Redaction and Its Application to SSI -Based Plug& Charge for Shared Vehicles

Reference 82

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:1781d86ca98d82888b839fda620e92a0d7970891410ccfc7bf91c6e202996012

Observation 51313e71-85f8-4e75-a6fd-e61d6f4b981c · outbound

This paper cites Direction-Oriented Smooth Sensitivity and Its Application to Genomic Statistical Analysis.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Direction-Oriented Smooth Sensitivity and Its Application to Genomic Statistical Analysis

Reference 83

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:a87e51cd6f9ef0e1a60e0c923d3e782d00b85dd3c0e132888c6098ea9281dc05

Observation 35d93b47-d051-4cfd-bbaa-640c625cbeca · outbound

This paper cites Sentence Embedding Generation Method for Differential Privacy Protection.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Sentence Embedding Generation Method for Differential Privacy Protection

Reference 84

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:26413e775d4d0c152a0851a640c880da453116301429ed752d97df12156aecca

Observation 4e675782-da7f-42f0-9664-a0868ee66826 · outbound

This paper cites KD - IBMRKE - PPFL : A Privacy-Preserving Federated Learning Framework Integrating Knowledge Distillation and Identity-Based Multi-receiver Key Encapsulation.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs KD - IBMRKE - PPFL : A Privacy-Preserving Federated Learning Framework Integrating Knowledge Distillation and Identity-Based Multi-receiver Key Encapsulation

Reference 85

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:6d2ee529c8f616b8da7276476093c67bbbda8358a24634beaef89a1e3256d383

Observation 642d0156-aef8-488c-8e33-8373b1c7f9c2 · outbound

This paper cites Ebron Jr.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Ebron Jr

Reference 86

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:9d0b4870a72cf12a7efa32d913ae8d16b14c270d6f81556389a73989d091b1ca

Observation e166100f-0e79-465f-80c9-4b6acf724e15 · outbound

This paper cites RAGLeak : Membership Inference Attacks on RAG -Based Large Language Models.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs RAGLeak : Membership Inference Attacks on RAG -Based Large Language Models

Reference 87

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:f548c79eb1b8aca23317bc1765f250c81129a418f2886301be73395425f94127

Observation 32d95098-e9d8-4b8e-b4f6-94cc467fea30 · outbound

This paper cites an unresolved cited work.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Unresolved cited work

Reference 88

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:1cdf8fedd185c3dc918f44e97b30b8704d1ae86e58dcfec45a0792fcc8db0fb6

Observation cf9d5f22-a18b-4738-9144-7c2330a15943 · outbound

This paper cites FRFL : Fair and Robust Federated Learning Incentive Model Based on Game Theory.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs FRFL : Fair and Robust Federated Learning Incentive Model Based on Game Theory

Reference 89

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:8e6fd241ab6515eb3a8ff90b2484d887d15c45031a955507a88932d427d61327

Observation 8e841c8a-81aa-4134-94c4-e162e043f638 · outbound

This paper cites DPFedSub : A Differentially Private Federated Learning with Randomized Subspace Descend.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs DPFedSub : A Differentially Private Federated Learning with Randomized Subspace Descend

Reference 90

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:0a731303b883b9de09fe8072c1d32a11ab0d1574847751e4f3b42fefa30ea245

Observation 3ac822cd-308a-4d4e-8649-26d56caa8486 · outbound

This paper cites MG -Det: Deepfake Detection with Multi-granularity.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs MG -Det: Deepfake Detection with Multi-granularity

Reference 91

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:b9021ffa6e279791205fc5b9d8205e02623be92c9e5c42b31a8f4426c774246c

Observation af547fff-1f1a-4d78-b8bc-237c4d834008 · outbound

This paper cites LPIA : Label Preference Inference Attack Against Federated Graph Learning.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs LPIA : Label Preference Inference Attack Against Federated Graph Learning

Reference 92

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:1e937328bf6e964f701d504c3d720dc702c6ce1890e0c07e0f061968454cee64

Observation df3522c5-abe4-4ade-8cd2-f0fc877dbc7e · outbound

This paper cites Kanhere and Jiamou Sun and Sanjay K.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Kanhere and Jiamou Sun and Sanjay K

Reference 93

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:88a863f8ea272edee371bf40d6e1663636d57579ef5766916eaa47fb8c59570f

Observation cfc37329-90eb-4562-96fe-776c575e285d · outbound

This paper cites Zeroth-Order Federated Private Tuning for Pretrained Large Language Models.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Zeroth-Order Federated Private Tuning for Pretrained Large Language Models

Reference 94

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:e5ab641da53b9329697555efe36174b76806347e465d0467ac79be5dc460f499

Observation 93b2558b-c135-4db9-a78a-24febc9ba7e7 · outbound

This paper cites an unresolved cited work.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Unresolved cited work

Reference 95

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:07d6c0713ffeb2490f955a1d511f2a950a5607196f969f80c61c39ff1411d7be

Observation 07dfbbc5-abcc-4f3e-a5b8-f937e144ea5f · outbound

This paper cites Mitigating the Unprivileged User Namespaces Based Privilege Escalation Attacks with Linux Capabilities.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Mitigating the Unprivileged User Namespaces Based Privilege Escalation Attacks with Linux Capabilities

Reference 96

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:96a56dc6b8e01b12a1e414a9e2aad2be5d6c20866ea943fd4ba99a9c07af1bf4

Observation 4ff59652-feff-499e-8baa-8fcc18bd782a · outbound

This paper cites SoK : From Systematization to Best Practices in Fuzz Driver Generation.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs SoK : From Systematization to Best Practices in Fuzz Driver Generation

Reference 97

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:5fc0ac68856bb4702f0a1590d36b9464427e68a7b575dad2cd006ae55c10ee2a

Observation 6d6ccfc4-08a5-49c9-aeee-e7c9aac0c530 · outbound

This paper cites Facial Authentication Security Evaluation Against Deepfake Attacks in Mobile Apps.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Facial Authentication Security Evaluation Against Deepfake Attacks in Mobile Apps

Reference 98

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:6d0ac721e419ce33057fd2c01a35b5df1da702085bdb5bf22dbe972e275d93c9

Observation 568c58fa-f965-4562-ab90-fc5124be77ac · outbound

This paper cites EAPIR : Efficient and Authenticated Private Information Retrieval with Fast Server Processing.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs EAPIR : Efficient and Authenticated Private Information Retrieval with Fast Server Processing

Reference 99

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:0e4ca3108c3275113e86f0e8c4a26e376d59bb9f7f334732e1fb1f3e2e27af95

Observation 79bfe8a3-240b-4550-8831-d308f5bb1170 · outbound

This paper cites an unresolved cited work.

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs Unresolved cited work

Reference 100

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source=arxiv_source observed=2026-07-12T01:34:45.323277Z digest=sha256:68d4936fd8febd9953da90f4b14531f92f0a0207342b35ad6903f90d591b2f7e

Pith citing papers

No inbound Pith citation observations are available.