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Paper Citation Record · LEDGER

Autoregressive Large Language Models are Computationally Universal

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2410.03170.

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

pith.paper-citation-record.v1
2410.03170 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T19:58:59.011935Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T18:45:00.539738Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e74d7a1c-fb85-4f37-a06e-5dba6101a925 · inbound

Learning Model Successors cites this paper.

Learning Model Successors Autoregressive Large Language Models are Computationally Universal

Reference 143

Resolution
unresolved
no resolver link, observed 2026-08-09T19:58:59.011935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:58:59.011935Z digest=sha256:493d80df4032bd19bee2582369d168c2588783c1b361b39ff0e8b47c45deba7a

Observation 4d0d7592-21c2-4dea-a979-fb0b8887d555 · inbound

Semantic Concurrency Limits in Large Language Models cites this paper.

Semantic Concurrency Limits in Large Language Models Autoregressive Large Language Models are Computationally Universal

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-22T18:41:56.354657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-22T18:41:30.008331Z digest=sha256:bdc6878af6ed0397567ae6e7584bad7625556adb4a2cd4b58ebe019f5b35fcbf

Observation b77dad33-2e0f-4bfe-a08c-b004e621c283 · inbound

Re:Form -- Reducing Human Annotations in Scalable Formal Software Verification with RL in LLMs: A Preliminary Study on Dafny cites this paper.

Re:Form -- Reducing Human Annotations in Scalable Formal Software Verification with RL in LLMs: A Preliminary Study on Dafny Autoregressive Large Language Models are Computationally Universal

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:16.110693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:20:16.110693Z digest=sha256:747fa6d9fa790eea583e65a1496f60e35c9d781e1884df3b82dab046a4fa524a

Observation 853dc093-8e92-4427-ac70-a97af1136c66 · inbound

Loom: A Scalable Analytical Neural Computer Architecture cites this paper.

Loom: A Scalable Analytical Neural Computer Architecture Autoregressive Large Language Models are Computationally Universal

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T07:41:01.335224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T17:01:33.381684Z digest=sha256:5104366fc076746441f6f8f79cb178a98e7b6aa7499dca54f0e3918666427506

Observation 17a3c7f1-82f7-4776-b77f-3e1dfc652476 · inbound

Position: The Turing-Completeness of Autoregressive Transformers Relies Heavily on Context Management cites this paper.

Position: The Turing-Completeness of Autoregressive Transformers Relies Heavily on Context Management Autoregressive Large Language Models are Computationally Universal

Reference 46

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T06:33:05.855695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-20T06:28:15.713072Z digest=sha256:b93c109125460366539bb94d1e82803a29f0e689ab2b22fb84ff68290e2dba03

Observation 74a9b41e-f863-4dd2-9b41-00b18d66df53 · inbound

Position: The Turing-Completeness of Autoregressive Transformers Relies Heavily on Context Management cites this paper.

Position: The Turing-Completeness of Autoregressive Transformers Relies Heavily on Context Management Autoregressive Large Language Models are Computationally Universal

Reference 46

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T18:45:00.541638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-30T18:41:29.893246Z digest=sha256:fc994446319ec60c0fe63789ea0a7f84914455a644b1d0e4290b3a25d5015ae8

Observation 196d35ae-0bf7-4791-96a2-638c2dcec071 · inbound

Efficient Diffusion LLMs via Temporal-Spatial Parallel Decoding and Confidence Extrapolation cites this paper.

Efficient Diffusion LLMs via Temporal-Spatial Parallel Decoding and Confidence Extrapolation Autoregressive Large Language Models are Computationally Universal

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T22:52:44.932813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T22:51:36.013299Z digest=sha256:8f7afb53b3930f2ee53f779f471206b61c5d73c6be69669c9cb790a27d1e695b