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Paper Citation Record · LEDGER

Large Language Models Pass the Turing Test

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2503.23674.

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

pith.paper-citation-record.v1
2503.23674 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:49:45.141278Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

8
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation cfd8dd03-d737-4def-85c5-e354e0284070 · inbound

How Many Human Survey Respondents is a Large Language Model Worth? An Uncertainty Quantification Perspective cites this paper.

How Many Human Survey Respondents is a Large Language Model Worth? An Uncertainty Quantification Perspective Large Language Models Pass the Turing Test

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-23T03:15:21.267334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-23T03:14:00.526112Z digest=sha256:196644903a104d131350a9f7fedb0a1752dba1fb547b00cd189971bfa2b224c3

Observation 54790960-19ce-4065-9cf9-443924b2ea9a · inbound

Large Language Models are Near-Optimal Decision-Makers with a Non-Human Learning Behavior cites this paper.

Large Language Models are Near-Optimal Decision-Makers with a Non-Human Learning Behavior Large Language Models Pass the Turing Test

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T23:49:45.141278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:45.141278Z digest=sha256:545217f1e6a42fe1e1dbe1b18a3bbc4f604565102b070ec1af1da09f4fe65709

Observation 265c2abf-b91c-41cf-9cad-81397626911d · inbound

Too Human to Model:The Uncanny Valley of LLMs in Social Simulation -- When Generative Language Agents Misalign with Modelling Principles cites this paper.

Too Human to Model:The Uncanny Valley of LLMs in Social Simulation -- When Generative Language Agents Misalign with Modelling Principles Large Language Models Pass the Turing Test

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T19:11:23.835573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:11:23.835573Z digest=sha256:fdef1f54944736b76c80c88b5b004438d6f55782e55e8db7818746cf9f4c8e1c

Observation 6a3c5339-af1c-4340-a7d5-8af5a2cd9192 · inbound

A Collaborative Framework Integrating Large Language Model and Chemical Fragment Space: Mutual Inspiration for Lead Design cites this paper.

A Collaborative Framework Integrating Large Language Model and Chemical Fragment Space: Mutual Inspiration for Lead Design Large Language Models Pass the Turing Test

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:53.770180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:53.770180Z digest=sha256:db83e7ab10b29e7eec0c6cb8a478834b587aced2fc1e6d569e1c0fb46b94d47c

Observation 5450d08a-387f-4699-ab24-a061030d7dba · inbound

The Other Mind: How Language Models Exhibit Human Temporal Cognition cites this paper.

The Other Mind: How Language Models Exhibit Human Temporal Cognition Large Language Models Pass the Turing Test

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T15:30:34.964039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:30:34.964039Z digest=sha256:328c574b06584d894536d6ff1fb9132167547c21a0f80bb4cd3a711d3e45c6e0

Observation 249efac2-5cf1-4541-8844-d6ac6b17497c · inbound

Playstyle and Artificial Intelligence: An Initial Blueprint Through the Lens of Video Games cites this paper.

Playstyle and Artificial Intelligence: An Initial Blueprint Through the Lens of Video Games Large Language Models Pass the Turing Test

Reference 148

Resolution
unresolved
no resolver link, observed 2026-08-05T16:00:10.871915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T16:00:10.871915Z digest=sha256:c53877c9c888f41197147cd241d1fce8edea00829fe8ea3e49cb42fefa1468b8

Observation cdd6cbcc-05d9-4221-93bd-c8eac92371c6 · inbound

CoVeR: Conformal Calibration for Versatile and Reliable Autoregressive Next-Token Prediction cites this paper.

CoVeR: Conformal Calibration for Versatile and Reliable Autoregressive Next-Token Prediction Large Language Models Pass the Turing Test

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T06:00:59.641527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T06:00:59.641527Z digest=sha256:7c5d4c7d2639c0ce7b4ba8c9c2ef738203cbf3f260db73d06d5aef38d9ff6a93

Observation 9968977b-7e02-49ab-9bcc-a640253610bb · inbound

Artificially intelligent agents in the social and behavioral sciences: A history and outlook cites this paper.

Artificially intelligent agents in the social and behavioral sciences: A history and outlook Large Language Models Pass the Turing Test

Reference 100

Resolution
unresolved
no resolver link, observed 2026-08-04T11:19:11.657189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:19:11.657189Z digest=sha256:693e4160cb3c3ad74a1477b8f7cd961045ed12ae8e38b522076fd8c9ad7a2ded

Observation cebf3be7-30ae-4f73-bf98-7826ad69ba24 · inbound

Different types of syntactic agreement recruit the same units within large language models cites this paper.

Different types of syntactic agreement recruit the same units within large language models Large Language Models Pass the Turing Test

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-17T02:43:53.199483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-17T02:43:51.273343Z digest=sha256:88aec78a6ebd4e2442f3d718b2824ecebc77483d9e5c937aa9d6abdafc5cc9f5

Observation 29a10268-a4ee-4bb8-a239-ae30308ae50d · inbound

Love, Lies, and Language Models: Investigating AI's Role in Romance-Baiting Scams cites this paper.

Love, Lies, and Language Models: Investigating AI's Role in Romance-Baiting Scams Large Language Models Pass the Turing Test

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T21:48:34.323996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-16T21:47:54.299087Z digest=sha256:7b46bb81383796f96be1ebb9c2aba9ccd1515edea19e8f32057f26620443b3c4

Observation 3c56843d-4647-4b50-8710-8c4af119600f · inbound

More Human or More AI? Visualizing Human-AI Collaboration Disclosures in Journalistic News Production cites this paper.

More Human or More AI? Visualizing Human-AI Collaboration Disclosures in Journalistic News Production Large Language Models Pass the Turing Test

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-03T10:12:38.459948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:12:38.459948Z digest=sha256:5fca2a6807b8d92dbceaedfe88cd9c3fe1a9110a5e9cb0bd180156ba5f919595

Observation 0f2fabf1-5340-419d-ac39-b8c692e53a03 · inbound

The Generalized Turing Test: A Foundation for Comparing Intelligence cites this paper.

The Generalized Turing Test: A Foundation for Comparing Intelligence Large Language Models Pass the Turing Test

Reference 27

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T03:26:18.934499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-12T03:25:48.145137Z digest=sha256:937de7f426033b6680af0169d4a8523b2ae00d7aa2cd8b6c0f7c1c7a60b57d55

Observation a24e8e78-6250-446e-b3cf-95f096c961bc · inbound

Instructions Shape Production of Language, not Processing cites this paper.

Instructions Shape Production of Language, not Processing Large Language Models Pass the Turing Test

Reference 206

Resolution
verified exact
arxiv_id, observed 2026-05-13T03:12:09.315722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T03:09:02.902912Z digest=sha256:dadf0ed5f30cce73f45ba4812a267c90f805dad4692a6ce33a22ddf35331ee32

Observation 5ed63db5-c1eb-4ca3-9046-91196293de2d · inbound

Instructions Shape Production of Language, not Processing cites this paper.

Instructions Shape Production of Language, not Processing Large Language Models Pass the Turing Test

Reference 206

Resolution
verified exact
arxiv_id, observed 2026-05-14T21:02:58.029368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-14T21:02:02.135970Z digest=sha256:8a6ef5595c4dfeefc63daa6e828621acdb5f84294636afda4baf90a06ea33510

Observation e05f5eb6-7e8c-41a4-81ac-bd4b6e44bcbb · inbound

Accommodation Goes Both Ways: Studying Linguistic Convergence Between Humans and Language Models cites this paper.

Accommodation Goes Both Ways: Studying Linguistic Convergence Between Humans and Language Models Large Language Models Pass the Turing Test

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-06-29T08:03:13.930398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-29T08:02:05.148717Z digest=sha256:90675e5e5b2f33050acb0bad1ba79d19eab8438c42a10f49d22682f0cd0ad628

Observation 9f11ef45-7172-4d18-8cba-aa5e9315d929 · inbound

RealityTest: How People Probe AI Identity and Whether Models Disclose It cites this paper.

RealityTest: How People Probe AI Identity and Whether Models Disclose It Large Language Models Pass the Turing Test

Reference 26

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T19:36:08.719550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T22:22:43.432328Z digest=sha256:426a44b3806c9a40d09c6cdf5be574b1a3f81a2ccafccc32a02e8de76609e7ca

Observation a950649b-0b31-469f-b034-9af130664379 · inbound

What biology can, and cannot, tell us about conscious AI cites this paper.

What biology can, and cannot, tell us about conscious AI Large Language Models Pass the Turing Test

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-06-28T12:22:07.921976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T11:44:20.094579Z digest=sha256:41df3407e8024586217984bf541b80665897189b5eb4317f1323367c5ba1fdcf

Observation 0fd309e6-e9d8-494e-abdc-6c1cda46dd88 · inbound

Bridging Creative Intent and Visual Quality: Creator-Driven Recurrent Video Generation with Agentic Feedback Loops cites this paper.

Bridging Creative Intent and Visual Quality: Creator-Driven Recurrent Video Generation with Agentic Feedback Loops Large Language Models Pass the Turing Test

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T23:39:03.375214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T22:02:18.035999Z digest=sha256:d071a9056759c0d9c2629f079ac01eeca08f9de5e1104cd27d0d41be33f64634