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Paper Citation Record · LEDGER

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback

As of 21 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2509.10509.

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

pith.paper-citation-record.v1
2509.10509 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:04:05.838523Z

measured 31 of 31 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 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

31 of 31 outbound references displayed

  • verified exact4
  • verified fuzzy14
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 71e09e99-5d90-435f-9662-9177bbe92bca · outbound

This paper cites The Curse of Recursion: Training on Generated Data Makes Models Forget.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback The Curse of Recursion: Training on Generated Data Makes Models Forget

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f298ce14-2409-4c40-87dd-7895bed68fab · outbound

This paper cites AI models collapse when trained on recursively generated data,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback AI models collapse when trained on recursively generated data,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-05T12:04:10.585506Z

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=2026-08-05T12:04:03.300082Z digest=sha256:55447042cb09ed73d2c1f9215c97ecb6002a6c3723b607d073c4a13e538b5dc6

Observation 3c52b74c-c28d-4824-ab6d-f3963610d379 · outbound

This paper cites Recursive training loops in LLMs: How training data properties modulate distribution shift in generated data?,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Recursive training loops in LLMs: How training data properties modulate distribution shift in generated data?,

Reference 3

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verified exact
raw_fallback, observed 2026-08-05T12:04:07.741439Z

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=2026-08-05T12:04:03.385761Z digest=sha256:eb88223493c561dcb20c9bed6bd20c9a87c395950ec5d195f2fceeb4ecfcb416

Observation 4f6ba3b3-58aa-49b0-ad13-64481b3a74e9 · outbound

This paper cites How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 4

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no resolver link, observed 2026-08-05T12:04:03.464968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:03.464968Z digest=sha256:65d1e47f591efdf876c684dac86e4a82ab19918ace19bd6eeb876996384fdbfa

Observation 0d760629-133c-4ec9-af57-a6447ecdb887 · outbound

This paper cites Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data

Reference 5

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no resolver link, observed 2026-08-05T12:04:03.563556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:03.563556Z digest=sha256:045fb093e2ce0f5f67b6027480a21cb041459f559bb68119b76811f9c706a706

Observation 9948cd37-bfb1-4aab-b3f3-95fba413833c · outbound

This paper cites Rate of model collapse in recursive training,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Rate of model collapse in recursive training,

Reference 6

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raw_fallback, observed 2026-08-05T12:04:10.561520Z

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=2026-08-05T12:04:03.631266Z digest=sha256:081f69bfcda65ec89785d1972b5553d8a9b8ea6d89abaf2d6854e7cbbee820a4

Observation bc33e06f-5803-4cba-8572-96046db87081 · outbound

This paper cites Improving the Scaling Laws of Synthetic Data with Deliberate Practice.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Improving the Scaling Laws of Synthetic Data with Deliberate Practice

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:03.747907Z digest=sha256:bc8267484bcb745db3aeb3b49889ba79f108c5d801fadb1e6f1cbaffbeecaa60

Observation 82eff538-4fd2-4964-b592-c5a56efb549d · outbound

This paper cites Cross-Entropy Is All You Need To Invert the Data Generating Process.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Cross-Entropy Is All You Need To Invert the Data Generating Process

Reference 8

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:03.839746Z digest=sha256:afc207dacf25a71c75c8468bee95adfe5063fce6ae93ae8642701b21ef33a98e

Observation 22de80ee-71bb-4b88-9344-fa633f10234b · outbound

This paper cites An entropy-based model for hierarchical learning,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback An entropy-based model for hierarchical learning,

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-05T12:04:10.524458Z

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=2026-08-05T12:04:03.949272Z digest=sha256:68fbf84224cd89a22ef94919f6c618bcf008b634a33ca2cd79f426e5d637c149

Observation 8eef210b-4baa-4101-bd6e-e03307ef2c29 · outbound

This paper cites Cognitive offloading,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Cognitive offloading,

Reference 10

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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=2026-08-05T12:04:04.031888Z digest=sha256:df23f306de854ba6705666cc3725eeeb8337225df0665e5c034045c1aa66bec1

Observation 2292af0c-11f6-4d52-970d-5b6114cc0d3a · outbound

This paper cites Effects of generative artificial intelligence on cognitive effort and task performance: Study protocol for a randomised controlled experiment,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Effects of generative artificial intelligence on cognitive effort and task performance: Study protocol for a randomised controlled experiment,

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-05T12:04:09.957898Z

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.

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Observation f01829ac-4560-4480-a3d3-598496b5a733 · outbound

This paper cites How human–AI feedback loops alter human perceptual, emotional and social judgments,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback How human–AI feedback loops alter human perceptual, emotional and social judgments,

Reference 12

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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.

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Observation f6a66d67-4e82-4ef7-93ae-98fed50f06b3 · outbound

This paper cites University students offload critical thinking, other hard work to AI,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback University students offload critical thinking, other hard work to AI,

Reference 13

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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=2026-08-05T12:04:04.397858Z digest=sha256:8e5d268ff31dcb24c7a212c5a951f9b9a8fc5fef3bdba60fbce2cd33cd729ff6

Observation 99094e2b-c51a-4574-8f0e-d8cf24820c2d · outbound

This paper cites The cognitive paradox of AI in education: between enhancement and erosion,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback The cognitive paradox of AI in education: between enhancement and erosion,

Reference 14

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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.

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Observation 4f890d57-6bb7-4dc3-8c6f-926ed706d0d1 · outbound

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

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Training language models to follow instructions with human feedback,

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-05T12:04:09.018358Z

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=2026-08-05T12:04:04.580343Z digest=sha256:92f08cb5ad219e9dc7a93b03ce7132217776aa3754806550a9d3ae2bbdc84215

Observation 6096402b-40d6-4144-be94-3893aed94153 · outbound

This paper cites Deep reinforcement learning from human preferences,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Deep reinforcement learning from human preferences,

Reference 16

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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=2026-08-05T12:04:04.685971Z digest=sha256:366ce948cafe0ce29eb0451ee8622f55cabf6f3fcf5cf3d14e2b35cf09eadbc9

Observation 204f11e3-f7e5-475c-9fe1-17de2c24ec84 · outbound

This paper cites Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 539215bd-5c0e-438b-9083-e151f4ee169e · outbound

This paper cites Reward shaping to mitigate reward hacking in RLHF,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Reward shaping to mitigate reward hacking in RLHF,

Reference 18

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Observation da17d70c-5e09-46b1-84fd-ffb24531c819 · outbound

This paper cites The Energy Loss Phenomenon in RLHF: A New Perspective on Mitigating Reward Hacking.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback The Energy Loss Phenomenon in RLHF: A New Perspective on Mitigating Reward Hacking

Reference 19

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source=pdf_text observed=2026-08-05T12:04:04.942029Z digest=sha256:5219067340ba114a255b78d3b79c83f61d0bf933714b2b03ca5fd1ac9b298159

Observation 2b70c1c5-bb61-44d0-a842-0e0683b2b3e1 · outbound

This paper cites Helpful, harmless, honest? Sociotechnical limits of AI alignment and safety through reinforcement learning from human feedback,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Helpful, harmless, honest? Sociotechnical limits of AI alignment and safety through reinforcement learning from human feedback,

Reference 20

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raw_fallback, observed 2026-08-05T12:04:08.462076Z

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.

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Observation 56844974-c884-451e-8d05-48902bd092c6 · outbound

This paper cites LoRA: Low-rank adaptation of large language models,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback LoRA: Low-rank adaptation of large language models,

Reference 21

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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.

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Observation 6df64cd8-7e0f-4b3a-b79e-3e2ca3977270 · outbound

This paper cites The False Promise of Imitating Proprietary LLMs.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback The False Promise of Imitating Proprietary LLMs

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:05.171538Z digest=sha256:19984fea1f6d15cdadca70e78d9b25ad82e3046b1e6e2b649c0b5c283f8e8ed0

Observation e088d062-f2f9-458d-907e-8fb55ce4c88c · outbound

This paper cites Non-Parametric Goodness-of-Fit Tests Using Tsallis Entropy Measures.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Non-Parametric Goodness-of-Fit Tests Using Tsallis Entropy Measures

Reference 23

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local_arxiv, observed 2026-08-05T12:04:07.164577Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 45f27741-6e81-4304-8993-2ab58ed95feb · outbound

This paper cites General Table Question Answering via Answer-Formula Joint Generation.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback General Table Question Answering via Answer-Formula Joint Generation

Reference 24

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:05.338256Z digest=sha256:dc373ba055f5034d0db46105cb36a4d6f2381fa0fce877f233956c1f4572a1b5

Observation c1e5145d-1661-4a30-b4c8-0abaa7615c71 · outbound

This paper cites Beyond model collapse: Scaling up with synthesized data requires verification,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Beyond model collapse: Scaling up with synthesized data requires verification,

Reference 25

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verified exact
raw_fallback, observed 2026-08-05T12:04:06.973056Z

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=2026-08-05T12:04:05.378973Z digest=sha256:b8e3e33418a8512ecf70a6b9c9d573071c09d8fe073d9b14ddd17eff444e17f3

Observation cc863294-93fc-406e-bbf2-04c418ff09be · outbound

This paper cites Scaling laws of synthetic data for language models,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Scaling laws of synthetic data for language models,

Reference 26

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verified exact
raw_fallback, observed 2026-08-05T12:04:06.659360Z

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=2026-08-05T12:04:05.437292Z digest=sha256:2768db97dcaa4e73194fec14d578ca12af55f409dd3f3d8cc3355accd512bfc9

Observation 6c0634f3-5e54-4455-aabe-22e489beaeda · outbound

This paper cites Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant for essay writing,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant for essay writing,

Reference 27

Resolution
verified exact
raw_fallback, observed 2026-08-05T12:04:06.383381Z

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=2026-08-05T12:04:05.533497Z digest=sha256:186291827d155e8e4287aa3618d401a827264346a3dcfe2fe9f18577e8334b44

Observation 6502d5a3-b232-4e71-9b71-0aed4f001bc0 · outbound

This paper cites Wing Optimisation for a tractor propeller driven Micro Aerial Vehicle.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Wing Optimisation for a tractor propeller driven Micro Aerial Vehicle

Reference 28

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metadata mismatch
local_arxiv, observed 2026-08-05T12:04:06.134884Z

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=2026-08-05T12:04:05.616586Z digest=sha256:62dec5c33b5e766b0d042d7f272b1acb832c65e7027ecf05480b1409e205f1ba

Observation 33d30845-a044-4fec-9ec7-9b408ad59e5b · outbound

This paper cites Extending minds with generative AI,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Extending minds with generative AI,

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-05T12:04:08.084381Z

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=2026-08-05T12:04:05.705810Z digest=sha256:0885a7fa312dcab0d0079abdaff9b0beff95b7525385a78d7b43f30a07dd60ae

Observation 22e08673-67cd-471e-bebc-3123d7eae642 · outbound

This paper cites Protecting human cognition in the age of AI,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback Protecting human cognition in the age of AI,

Reference 30

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unresolved
no resolver link, observed 2026-08-05T12:04:05.757206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:05.757206Z digest=sha256:534e2e6cb48f23211f0b5861e098ee20e542d5d1d2cb8ebffeb7e8bfc12b2487

Observation 30272053-5232-4c8a-bf19-f0b694045514 · outbound

This paper cites BiMark: Unbiased multilayer watermarking for large language models,.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback BiMark: Unbiased multilayer watermarking for large language models,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-05T12:04:07.919722Z

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=2026-08-05T12:04:05.838523Z digest=sha256:eda219828d28263a4a9ab70c195d6d1d5ce741df332bfab18ffa5c037bd82790

Pith citing papers

No inbound Pith citation observations are available.