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Paper Citation Record · LEDGER

Adaptive Supervised Anchoring for On-Policy Self-Distillation

As of 20 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2608.07935.

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

pith.paper-citation-record.v1
2608.07935 v2

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:30:59.113734Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

38 of 38 outbound references displayed

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  • verified fuzzy16
  • unresolved21
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eb3f397f-f4ce-4197-9582-bac4b4577755 · outbound

This paper cites Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe.

Adaptive Supervised Anchoring for On-Policy Self-Distillation Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe

Reference 1

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source=arxiv_source observed=2026-08-15T14:30:58.977048Z digest=sha256:a4777c015637f2ed732b5116eb2fc96f2f580f96664dbed6d5e0461e8afea074

Observation a4e7a171-046c-4ffa-8b7e-1d1ffe11b2e4 · outbound

This paper cites GPT-4 Technical Report.

Adaptive Supervised Anchoring for On-Policy Self-Distillation GPT-4 Technical Report

Reference 2

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source=arxiv_source observed=2026-08-15T14:30:58.983083Z digest=sha256:8f9fbe14cf9b493886dc96c6ead1007c22730774306c7072f0e56217392287b3

Observation eedeb8b6-9be7-4c0a-8980-e152a72fdd7b · outbound

This paper cites The Llama 3 Herd of Models.

Adaptive Supervised Anchoring for On-Policy Self-Distillation The Llama 3 Herd of Models

Reference 3

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source=arxiv_source observed=2026-08-15T14:30:58.987144Z digest=sha256:972e03837b03f224c68b3e950f03deefcc0bf16ca096bea4166404bbae07b42b

Observation c8e09a10-3630-47eb-8bc2-9e3b8dfa6624 · outbound

This paper cites Revisiting On-Policy Distillation: Empirical Failure Modes and Simple Fixes.

Adaptive Supervised Anchoring for On-Policy Self-Distillation Revisiting On-Policy Distillation: Empirical Failure Modes and Simple Fixes

Reference 4

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source=arxiv_source observed=2026-08-15T14:30:58.990466Z digest=sha256:4021d57c9a683edf8cd3b0459b4c970bb30b838566d7e6311e5a4799215b8ae4

Observation 9abe9b71-a7ee-4838-83fa-6d3f5db86210 · outbound

This paper cites Demystifying OPD: Length Inflation and Stabilization Strategies for Large Language Models.

Adaptive Supervised Anchoring for On-Policy Self-Distillation Demystifying OPD: Length Inflation and Stabilization Strategies for Large Language Models

Reference 5

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source=arxiv_source observed=2026-08-15T14:30:58.993841Z digest=sha256:88eb86309238b1dcdf671fb800097e92c69c19f8da041ebf4a6698bee0716a39

Observation 956f6187-967a-4791-a592-97e3edf3f998 · outbound

This paper cites Findings of the Association for Computational Linguistics: ACL 2023 , pages =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation Findings of the Association for Computational Linguistics: ACL 2023 , pages =

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T14:30:58.997553Z digest=sha256:14f849c1bcde6cdf0e984c379907b2d4a33582df8d234dfc4e881fe5cf377126

Observation 6184d41b-a8a8-4b47-9dea-6f2c3a28a5bc · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Adaptive Supervised Anchoring for On-Policy Self-Distillation Distilling the Knowledge in a Neural Network

Reference 7

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source=arxiv_source observed=2026-08-15T14:30:59.000910Z digest=sha256:1cf3121b07b17746d14e9f86cd8e2c93c9d20f685969a05f1ee42317a55572e4

Observation a55037bb-4c38-459a-9231-00a625671a58 · outbound

This paper cites International Journal of Computer Vision , volume =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation International Journal of Computer Vision , volume =

Reference 8

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T14:30:59.004494Z digest=sha256:8716ce439636219103de8b5d023af6623570983567bbf3963f558aea7dc67acd

Observation d95755b0-12bb-48e1-b83b-8cc663c3d1d1 · outbound

This paper cites The Twelfth International Conference on Learning Representations (ICLR) , year =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation The Twelfth International Conference on Learning Representations (ICLR) , year =

Reference 9

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T14:30:59.007682Z digest=sha256:73bc3ce37a9189d0a14fadd0e837e8fe28ce61b6dc6a71be505b513df7e271e9

Observation 1fb4efeb-2659-416d-9ad6-632848aa3bcc · outbound

This paper cites The Twelfth International Conference on Learning Representations (ICLR) , year =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation The Twelfth International Conference on Learning Representations (ICLR) , year =

Reference 10

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T14:30:59.011561Z digest=sha256:1e66897a72d9e41af04c4cabc78589a50f0ba7d6693201fe876b7f569e39b5be

Observation f4027dd6-8e3b-44f6-8fad-000e178ce8b5 · outbound

This paper cites Self-Distillation Enables Continual Learning.

Adaptive Supervised Anchoring for On-Policy Self-Distillation Self-Distillation Enables Continual Learning

Reference 11

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source=arxiv_source observed=2026-08-15T14:30:59.015436Z digest=sha256:cf013207e1df6f75dd4a300b9aa59cb37e189d2dd112ecd7eb8e0f1c4ca5410e

Observation 297bf072-cc3d-4b96-a893-4347cdd737a3 · outbound

This paper cites OGLS-SD: On-Policy Self-Distillation with Outcome-Guided Logit Steering for LLM Reasoning.

Adaptive Supervised Anchoring for On-Policy Self-Distillation OGLS-SD: On-Policy Self-Distillation with Outcome-Guided Logit Steering for LLM Reasoning

Reference 12

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source=arxiv_source observed=2026-08-15T14:30:59.018986Z digest=sha256:516e78c9284a8cbea890233604c13d2679953bacc80902508651754b92f56b75

Observation 83a821ad-fa66-4253-8098-709a3f82df36 · outbound

This paper cites The Forty-second International Conference on Machine Learning (ICML) , year =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation The Forty-second International Conference on Machine Learning (ICML) , year =

Reference 13

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T14:30:59.022798Z digest=sha256:b784fda3cb72cf572d74f94265d025d1788f304e108ba74b7eab8563b89b06d5

Observation 803542d2-d62d-4886-a17a-8802722180e5 · outbound

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

Adaptive Supervised Anchoring for On-Policy Self-Distillation Advances in Neural Information Processing Systems (NeurIPS) , volume =

Reference 14

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raw_fallback, observed 2026-08-15T14:30:59.472256Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T14:30:59.026426Z digest=sha256:d2b31b621479503ca95ea6cb66fbf65312f7c48f47c6c7959916b973ba82381d

Observation 71671b2e-43c4-4929-966c-f8484c4662bf · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Adaptive Supervised Anchoring for On-Policy Self-Distillation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 15

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source=arxiv_source observed=2026-08-15T14:30:59.029979Z digest=sha256:17d190faf3fe4b74f9c680f6182cb8e70747f0437c32d3a232d680a7c3fbbb7e

Observation 2fad940e-17a3-45fb-bbe3-ea2bd141b3aa · outbound

This paper cites The Forty-first International Conference on Machine Learning (ICML) , year =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation The Forty-first International Conference on Machine Learning (ICML) , year =

Reference 16

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T14:30:59.033615Z digest=sha256:381a5685f120742eb64390bdd7c0520adc5503513c0dd5b0c4737932e412b76b

Observation 5c017229-56de-4653-94b6-953174184778 · outbound

This paper cites Rethinking K ullback- L eibler Divergence in Knowledge Distillation for Large Language Models.

Adaptive Supervised Anchoring for On-Policy Self-Distillation Rethinking K ullback- L eibler Divergence in Knowledge Distillation for Large Language Models

Reference 17

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source=arxiv_source observed=2026-08-15T14:30:59.037234Z digest=sha256:cf32690dccacc6089545fda501dbdf4618369b425509ec545a5767fce2f4e4cd

Observation d4ab564d-b91b-404a-b529-91f9e9aa9181 · outbound

This paper cites T o D i: Token-wise Distillation via Fine-Grained Divergence Control.

Adaptive Supervised Anchoring for On-Policy Self-Distillation T o D i: Token-wise Distillation via Fine-Grained Divergence Control

Reference 18

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source=arxiv_source observed=2026-08-15T14:30:59.041171Z digest=sha256:03d9f9d45d11405b5e6bb48fe64074f5e5ded5fb4ce51a805de03dad370cfe63

Observation 99a2bd73-9554-4472-8c58-5d90eceae9d4 · outbound

This paper cites Proceedings of the National Academy of Sciences , volume =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation Proceedings of the National Academy of Sciences , volume =

Reference 19

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source=arxiv_source observed=2026-08-15T14:30:59.045368Z digest=sha256:53fe195c22dbe2361af2220cf401154a854f3d2532bd92900cd8c839774189c7

Observation 98e74a92-96df-48c8-a7e9-d85301fb13db · outbound

This paper cites An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning.

Adaptive Supervised Anchoring for On-Policy Self-Distillation An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning

Reference 20

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source=arxiv_source observed=2026-08-15T14:30:59.049773Z digest=sha256:a54c7f6f4171c8e5cb050828e1ee9892f4256a4e389e88db0d3caa990aa11255

Observation be367df7-1f78-4904-9ed1-248876fa1083 · outbound

This paper cites The Fourteenth International Conference on Learning Representations (ICLR) , year =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation The Fourteenth International Conference on Learning Representations (ICLR) , year =

Reference 21

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T14:30:59.054139Z digest=sha256:3dead3a1ec2f82569495511a0bd1bf7ea0103807908c8185302d32fd675cb4ac

Observation 14172cd3-6456-4450-bc4c-84de55663785 · outbound

This paper cites ACM Computing Surveys , volume =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation ACM Computing Surveys , volume =

Reference 22

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source=arxiv_source observed=2026-08-15T14:30:59.057469Z digest=sha256:5c2f31ef3e99e3eb3c0bd3b99ee55a94c056db208ca1be3f43ebd60ec648c8b3

Observation 6554449b-7dd4-47c6-990d-6e071b94ffc1 · outbound

This paper cites RL's Razor: Why Online Reinforcement Learning Forgets Less.

Adaptive Supervised Anchoring for On-Policy Self-Distillation RL's Razor: Why Online Reinforcement Learning Forgets Less

Reference 23

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source=arxiv_source observed=2026-08-15T14:30:59.060832Z digest=sha256:87573aa15b1464ba90b403a1f4ce2fe79f2de722a129a83f323e0adc4bac2840

Observation 96cc048c-6a51-4d9d-8d19-c3c81990569e · outbound

This paper cites Retaining by Doing: The Role of On-Policy Data in Mitigating Forgetting.

Adaptive Supervised Anchoring for On-Policy Self-Distillation Retaining by Doing: The Role of On-Policy Data in Mitigating Forgetting

Reference 24

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source=arxiv_source observed=2026-08-15T14:30:59.064521Z digest=sha256:e0bd8c156595ce5f6b776106dea26c0de073289b8d05c81ff4e49683bbb0c648

Observation e6dccabe-05af-4ba3-aa04-99d1bfdcf144 · outbound

This paper cites LoRA Learns Less and Forgets Less.

Adaptive Supervised Anchoring for On-Policy Self-Distillation LoRA Learns Less and Forgets Less

Reference 25

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source=arxiv_source observed=2026-08-15T14:30:59.068406Z digest=sha256:bbddaf28df23c4f2f6cef30fe65485a7565c750b2d86b8af54babcf82dd547a1

Observation bd021fb8-4ca7-416d-8dbc-e14946274aa6 · outbound

This paper cites 2025 , publisher =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation 2025 , publisher =

Reference 26

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T14:30:59.072416Z digest=sha256:879f6c71dc7238bc2f78791d90bcf2df2dfaa10e67e3f0556c3b593001c796a7

Observation 8a34036f-e070-4c2b-97e6-452a0c32e547 · outbound

This paper cites 2025 , publisher =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation 2025 , publisher =

Reference 27

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation b4b42150-e307-4c20-a796-dc0c7b587da5 · outbound

This paper cites ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases.

Adaptive Supervised Anchoring for On-Policy Self-Distillation ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases

Reference 28

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Observation c48d9b77-1d45-44db-b66e-cd2b7a044386 · outbound

This paper cites HuggingFace repository , howpublished =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation HuggingFace repository , howpublished =

Reference 29

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Observation e0949940-0dab-46c0-9699-6ffd8bbff241 · outbound

This paper cites an unresolved cited work.

Adaptive Supervised Anchoring for On-Policy Self-Distillation Unresolved cited work

Reference 30

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source=arxiv_source observed=2026-08-15T14:30:59.087343Z digest=sha256:c52543a84df12f407ed19f4146ed67415095d8ae4521a3496d405b0eeeb8d7dd

Observation 9d625984-c4bd-48aa-a4ca-abcb1d48bcc3 · outbound

This paper cites The Twelfth International Conference on Learning Representations (ICLR) , year =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation The Twelfth International Conference on Learning Representations (ICLR) , year =

Reference 31

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source=arxiv_source observed=2026-08-15T14:30:59.090430Z digest=sha256:bb59470e92217210f0d509eeb215ac413cd5b2ff81afb38c3a959f61a7968468

Observation 9fe2c3ec-dceb-4408-8214-de40686100e5 · outbound

This paper cites NeurIPS Datasets and Benchmarks Track , year =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation NeurIPS Datasets and Benchmarks Track , year =

Reference 32

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T14:30:59.093520Z digest=sha256:e1e4545afec678f2c9179ee10d23cb30c0561e76b69796070503887e82909f41

Observation e3bb0cdb-52cc-4ea7-8d3c-335e809e1257 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Adaptive Supervised Anchoring for On-Policy Self-Distillation DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 33

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source=arxiv_source observed=2026-08-15T14:30:59.096546Z digest=sha256:b2219d1cd84c3f1984fd2b086716f39f163139eb06689c6e50a09d1ab2c84502

Observation 56ec0ebb-7dc8-4bf4-9d26-6610bf176eaa · outbound

This paper cites Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models.

Adaptive Supervised Anchoring for On-Policy Self-Distillation Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models

Reference 34

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source=arxiv_source observed=2026-08-15T14:30:59.100287Z digest=sha256:673edb99254b694f70f12021c7ca216404a1c9fa1c9a4f4b19d8ca58b4d04a00

Observation 01dcbd3a-9392-44ed-84f2-2192eedd7f14 · outbound

This paper cites The Tenth International Conference on Learning Representations (ICLR) , year =.

Adaptive Supervised Anchoring for On-Policy Self-Distillation The Tenth International Conference on Learning Representations (ICLR) , year =

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T14:30:59.103436Z digest=sha256:9738a79870ad7222a9d724d2bced85bc85a3e963efb295f9c7dcd0a98497c66c

Observation 4af330d0-18fa-446d-8941-f9aa0d809036 · outbound

This paper cites Qwen3 Technical Report.

Adaptive Supervised Anchoring for On-Policy Self-Distillation Qwen3 Technical Report

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T14:30:59.106642Z digest=sha256:dd47b357812a5c68b46a904bf52c7982172c254dd3513424f46c998e1c485568

Observation 8c843bf2-b5d4-4618-9bea-18a4fdfe7842 · outbound

This paper cites SWIFT:A Scalable lightWeight Infrastructure for Fine-Tuning.

Adaptive Supervised Anchoring for On-Policy Self-Distillation SWIFT:A Scalable lightWeight Infrastructure for Fine-Tuning

Reference 37

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no resolver link, observed 2026-08-15T14:30:59.109816Z

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source=arxiv_source observed=2026-08-15T14:30:59.109816Z digest=sha256:98077e71cbf6fc4819606d5584b35299da80bcfa82629a7f1c0fa8b6b322d95a

Observation 26c43321-8eea-41be-8b5a-a3315a8ea8d9 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Adaptive Supervised Anchoring for On-Policy Self-Distillation Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 38

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no resolver link, observed 2026-08-15T14:30:59.113734Z

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source=arxiv_source observed=2026-08-15T14:30:59.113734Z digest=sha256:aecd0afb0ad966329212d74cc346d20920ed01ee5acf8fcde466edd453bd0280

Pith citing papers

No inbound Pith citation observations are available.