Pith. sign in

Paper Citation Record · LEDGER

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment

As of 23 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 7 inbound Pith citation observations for arXiv:2507.07341.

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

pith.paper-citation-record.v1
2507.07341 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:58:12.233861Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:17:57.147946Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T22:57:25.939777Z

Reference resolution

24 of 24 outbound references displayed

  • verified exact0
  • verified fuzzy16
  • unresolved7
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fe69d402-7470-4b7d-9933-a0db35ac2131 · outbound

This paper cites an unresolved cited work.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:58:12.423612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.169746Z digest=sha256:19794ad7feff7d93d02812f5f8a19cf7588b47df7efb207b99b6f147cd5de9db

Observation 8a43ddb7-cfd5-456e-94af-d96a72e563cd · outbound

This paper cites , n− 1}, and computes s ← re mod n, where e = 2t is a tower of repeated squarings (i.e., t squarings of r).

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment , n− 1}, and computes s ← re mod n, where e = 2t is a tower of repeated squarings (i.e., t squarings of r)

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.415545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.172303Z digest=sha256:d04040f391c72f6fe2f236241d2b4acd2e6c7dece1a8cb7a6467a74690f2c8d4

Observation 5baf7d0c-44c7-4ca3-962c-9eeeb3c24b6e · outbound

This paper cites Returns (Z, s).

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment Returns (Z, s)

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.408136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.174834Z digest=sha256:c4865cc960a626dd42caf535171fc04730ba45423e085d4689f5b66943047c2f

Observation acd774a3-3239-41e0-b6f7-52350fcf5806 · outbound

This paper cites Note that Sol computes s using t repeated squarings, each of which is inexpensive, but the full process requires Θ(t) sequential steps.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment Note that Sol computes s using t repeated squarings, each of which is inexpensive, but the full process requires Θ(t) sequential steps

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.400530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.178052Z digest=sha256:8d851240d75f260e6cc00b72185d27b85aa3f4973d6a596995a908a7de337e18

Observation 8b291c00-dcc9-4a85-b140-1c913a702369 · outbound

This paper cites an unresolved cited work.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment Unresolved cited work

Reference 6

Resolution
parse uncertain
raw_fallback, observed 2026-08-06T18:58:12.392727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.180750Z digest=sha256:74505a13b91c98461ed5ccd9cdeefb902d5f4f3a055e9ec9a8cb4504cf7efbae

Observation d46fd4b8-f49b-4033-bc75-73fee52d2e27 · outbound

This paper cites , zi−1, before the if statement (step 8 of Algorithm 1) is executed, the distribution of q is uniform in [k].

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment , zi−1, before the if statement (step 8 of Algorithm 1) is executed, the distribution of q is uniform in [k]

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.385979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.183128Z digest=sha256:6d3a68cab0464a32e95e1f0ff7cc1c372d75ac14bb87a1fb46bd7dff7603e80c

Observation fad5a9c2-f919-47d0-9e85-9c97058d7ce3 · outbound

This paper cites an unresolved cited work.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:58:12.378541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.185511Z digest=sha256:47b86d492e925b78223e63aee180f8325dcd5bfdac5766a04939c323dc19e309

Observation ecaaba91-1c55-41ff-a4ef-154395ac7631 · outbound

This paper cites an unresolved cited work.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:58:12.371479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.188145Z digest=sha256:242e948fd3da7210ae1a4c3d960f072665ef31d6d60754d3e4e6bcd9d20c978d

Observation dfa16466-05f2-49f2-be26-90984e80612c · outbound

This paper cites threshold randomness.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment threshold randomness

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.363827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.190469Z digest=sha256:67240068a15559b209d920359b69df58104853d2c9d20a02d12640c0fb2ecd3e

Observation 691dccf3-bebd-4577-a6dc-eb29da9853b2 · outbound

This paper cites With probability 1 − λ−Ω(1) over z ← G the distributions M ′(z) and M (z) are equal.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment With probability 1 − λ−Ω(1) over z ← G the distributions M ′(z) and M (z) are equal

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.350294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.194932Z digest=sha256:b3c709b1b197c1bbb412aaddaeaea3e4193c8574c51285cbd0696cdfc5c37571

Observation 1e515cec-d1a8-4e04-8766-9ad6dc5e8502 · outbound

This paper cites remember.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment remember

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.342434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.197775Z digest=sha256:3121f755e744e2bf1d3e2dda9b25fcfe24a087329dd5fb459a152dd1f1f8044b

Observation ff162a5c-ffdc-4ecc-8778-200eb4f33e10 · outbound

This paper cites With all but negligible in λ probability over z ← G the distributions M ′(z) and M (z) are equal.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment With all but negligible in λ probability over z ← G the distributions M ′(z) and M (z) are equal

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.336253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.202926Z digest=sha256:04658454334e6f93d15e62fa54e898a2093602e85893e45b3919926ffcd3b378

Observation 9b583590-d2fd-4471-bcc5-214846fbcfc9 · outbound

This paper cites an unresolved cited work.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment Unresolved cited work

Reference 16

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:58:12.328507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.205269Z digest=sha256:d135a6c3514285d0c192bc60c37df507c2ce1597ba38aa4c79a5ab39d4b08df7

Observation cb9a0965-1034-4335-b85e-7193e0c32ff0 · outbound

This paper cites For every malicious prompt m ∈ SH, the following two distributions are close: {M ′(z) | z ← G′(m)} , {M (m)}.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment For every malicious prompt m ∈ SH, the following two distributions are close: {M ′(z) | z ← G′(m)} , {M (m)}

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.356904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.207466Z digest=sha256:9b253afbea65f9eecddab316fc60891bafbbb1663ff02c119f72cb7568d06a75

Observation 8030ea81-0e17-4d5d-9be6-a7a7a7e91807 · outbound

This paper cites an unresolved cited work.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:58:12.313074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.212095Z digest=sha256:66333d323d4de20a62152af6583d385188cc67a1a94104ce2d43d428ea3481fa

Observation 77dd7ad5-381e-4cbc-8a27-e993a48fb012 · outbound

This paper cites For every malicious prompt m ∈ SH, with all but negligible in λ probability over z ← M ′(m),16 it holds that H′(z) = Ω Ez←M (m)[H(z)].

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment For every malicious prompt m ∈ SH, with all but negligible in λ probability over z ← M ′(m),16 it holds that H′(z) = Ω Ez←M (m)[H(z)]

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.306843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.215474Z digest=sha256:32b37399ca8c291fe2f80fba11dab0ff8a74e75f5d421d0f9717ece77679db0f

Observation bb1bb0bc-dc53-4c78-9f22-9f5de51de429 · outbound

This paper cites With all but negligible probability in λ over z ← M ()17 H′(z) = H(z).

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment With all but negligible probability in λ over z ← M ()17 H′(z) = H(z)

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.299835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.217875Z digest=sha256:bdd85f1ff2d9609ec02718119800a1107312bf134fb71c54917de7f601f1c4c9

Observation cd6aabf9-c86b-4db4-ba34-d1232c57496c · outbound

This paper cites running time.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment running time

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.292654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.220098Z digest=sha256:da4c3f220be9317eaa10cd9d51c9e4f945c2c60c1f1ea0fc4ccffca145f27411

Observation bd40fa10-5628-4348-bb1b-e73ff970e608 · outbound

This paper cites For every prompt-mitigation filter F running in polynomial-time with all but negligible in λ probability over z ← G′ it holds that F (z) = ⊥ or M ′(z) is harmful.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment For every prompt-mitigation filter F running in polynomial-time with all but negligible in λ probability over z ← G′ it holds that F (z) = ⊥ or M ′(z) is harmful

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.285864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.222677Z digest=sha256:06e99c9078569ee1376aef1c14126ebd211916f2c04aca7d32259b84457a82c8

Observation 01fc0440-95cf-4888-8da8-718ed9507b76 · outbound

This paper cites With all but negligible in λ probability over z ← G the distributions M ′(z) and M (z) are equal.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment With all but negligible in λ probability over z ← G the distributions M ′(z) and M (z) are equal

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.321567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.226038Z digest=sha256:b7570f34b4c67a2ed63df260f14d3ab2e87ffbedfb5d9b25fcd6ed6a0af3172e

Observation 02281eff-8c48-4e47-bc59-68ffce24dc43 · outbound

This paper cites For every algo- rithm running in polynomial-time the advantage in distinguishing outputs of G and G′ is negligible in λ.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment For every algo- rithm running in polynomial-time the advantage in distinguishing outputs of G and G′ is negligible in λ

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.278200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.228455Z digest=sha256:2e57429bdba755c3fb452f9e273ca318200d48d82925edc7fbcf97b636247839

Observation 53cc2ef4-869b-4e1f-bf11-585c097852bc · outbound

This paper cites an unresolved cited work.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:58:12.269202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.231336Z digest=sha256:f406925888ba716e40e60957ec03baf3860d9c514184d1342a689cedfa15f11e

Observation 4d45f48b-5366-48a4-ab81-8c896183cff9 · outbound

This paper cites E.4 Proof The proof requires a careful comparison of requirements of Theorem 11 and properties of watermark- ing schemes robust against classes of transformations.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment E.4 Proof The proof requires a careful comparison of requirements of Theorem 11 and properties of watermark- ing schemes robust against classes of transformations

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:58:12.261759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:58:12.233861Z digest=sha256:727529d679e330137048c125cf2daefe94a20d66c17e97fdd925114fdcfcd89e

Observation 29fb1548-5629-450c-8d10-5f410caa377a · outbound

This paper cites JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models.

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models

Reference 2000

Resolution
unresolved
no resolver link, observed 2026-08-06T18:58:12.164527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:58:12.164527Z digest=sha256:1378343e0904f2533fb452531666c08b29e685eece9dd1fa02137b47a143ec12

Pith citing papers

Observation 9c73fe2c-2ab8-4d51-ac48-520cb5bbaebb · inbound

Spore: Efficient and Training-Free Privacy Extraction Attack on LLMs via Inference-Time Hybrid Probing cites this paper.

Spore: Efficient and Training-Free Privacy Extraction Attack on LLMs via Inference-Time Hybrid Probing On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T21:16:19.975892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T06:10:20.358899Z digest=sha256:12c9fe316d0d494f70e6f5ca3ce81e6a6273805bec085295335cd69e43231b06

Observation 7889dbcd-fc97-4143-a227-790564200922 · inbound

Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning cites this paper.

Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment

Reference 113

Resolution
verified exact
arxiv_id, observed 2026-05-19T21:52:48.244988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-19T21:49:07.440832Z digest=sha256:3f6aa84039731b0875b9dd1653c945af5c67e36c9db2973b470f51f8654ab0ca

Observation 857653ea-e86a-4bc1-a68b-5f351d09e5d4 · inbound

Send a SCOUT First: Pre-hoc Reasoning for Adaptive Detector Allocation in Prompt-Injection Defense cites this paper.

Send a SCOUT First: Pre-hoc Reasoning for Adaptive Detector Allocation in Prompt-Injection Defense On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T19:36:08.905765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-28T22:17:40.164877Z digest=sha256:3231dd3e32776d2ec011923b3878a95913fe52013bb9bea5208bb5ae1e89e972

Observation 247c9dce-fb0c-4caa-a103-4b422e058c2e · inbound

Emergence World: A Platform for Evaluating Long-Horizon Multi-Agent Autonomy cites this paper.

Emergence World: A Platform for Evaluating Long-Horizon Multi-Agent Autonomy On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment

Reference 69

Resolution
verified exact
arxiv_id, observed 2026-07-02T22:57:25.941483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-27T18:36:44.265273Z digest=sha256:0ae475e1c654215a9af5c1c71451fc104b22cb2b981325656ec334656553d6a4

Observation a826c4d7-1022-49fe-b3e6-90123e186a9c · inbound

On the Limits of Support-Preserving Alignment and Bounded Filtering cites this paper.

On the Limits of Support-Preserving Alignment and Bounded Filtering On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-02T09:19:34.923841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T09:19:34.923841Z digest=sha256:03de1b467562cb1448c4aed15fded172f167de8bf75dee09b45f494be66d6ec6

Observation 2f80ecdc-dcd6-4e20-bd07-30b267bc2e16 · inbound

Safeguards Based on Copyable Context Cannot Provide Reliable Safety for LLMs cites this paper.

Safeguards Based on Copyable Context Cannot Provide Reliable Safety for LLMs On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-31T22:25:22.203096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T22:25:22.203096Z digest=sha256:99887924ef90ddf42963c5f8e7ecf4c13a3b526162be480a4e206f56ee29fb83

Observation bf092eaf-f1b5-442a-9d68-aa8c9233828e · inbound

Measure, Don't Optimize: Forecasting Recovery in LLM Unlearning cites this paper.

Measure, Don't Optimize: Forecasting Recovery in LLM Unlearning On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment

Reference 184

Resolution
unresolved
no resolver link, observed 2026-08-15T14:17:57.147946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T14:17:57.147946Z digest=sha256:72d7d183b5401f9f974f839e7fd6f2e8c6025078860294cef000816058b16395