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Paper Citation Record · LEDGER

Aligning LLMs by Predicting Preferences from User Writing Samples

As of 8 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2505.23815.

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

pith.paper-citation-record.v1
2505.23815 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:30:24.218058Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

36 of 36 outbound references displayed

  • verified exact1
  • verified fuzzy8
  • unresolved26
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 013d5bf4-c53b-4a2f-bade-6c469d129d7d · outbound

This paper cites write newline.

Aligning LLMs by Predicting Preferences from User Writing Samples write newline

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T13:30:21.034846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:21.034846Z digest=sha256:5e002d0ee35a55b1856fbfba89eb40be6f2dceb30845eb3e9e23d3b83c0deec4

Observation d151dc49-3c8a-4e2c-a883-db23cae26983 · outbound

This paper cites PROST : P hysical reasoning about objects through space and time.

Aligning LLMs by Predicting Preferences from User Writing Samples PROST : P hysical reasoning about objects through space and time

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:21.154748Z digest=sha256:1c7fc65215ebe22dd2688a599699e7a4e8a04375cfac918e3f6804254ef880e3

Observation 68975d56-02c7-4bd0-aea9-89810a207976 · outbound

This paper cites an unresolved cited work.

Aligning LLMs by Predicting Preferences from User Writing Samples Unresolved cited work

Reference 3

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no resolver link, observed 2026-08-07T13:30:21.244785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:21.244785Z digest=sha256:0c2d8af9b6f52425f9557afe0c0c5e89a71857bb901ae14af62b29ef6e9f05a5

Observation abd8ac26-0c19-42aa-8887-82c36425652b · outbound

This paper cites Art or artifice? large language models and the false promise of creativity.

Aligning LLMs by Predicting Preferences from User Writing Samples Art or artifice? large language models and the false promise of creativity

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:29.030572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:30:21.344764Z digest=sha256:7b9e50e30abd621fbc13d56a8f6d520fdd034d2317027147ab28dc2c1f1e40e5

Observation 4533792d-5434-4edd-9ed2-7dc4c277ae66 · outbound

This paper cites Aligning LLM Agents by Learning Latent Preference from User Edits.

Aligning LLMs by Predicting Preferences from User Writing Samples Aligning LLM Agents by Learning Latent Preference from User Edits

Reference 5

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unresolved
no resolver link, observed 2026-08-07T13:30:21.434743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:21.434743Z digest=sha256:14ee78c7c17c6ae81a88bb55cc9fa3b800aeac8bf0f719ba9803ec60f8344557

Observation 9d244e8c-8260-46b4-95ae-3b7164cb2962 · outbound

This paper cites an unresolved cited work.

Aligning LLMs by Predicting Preferences from User Writing Samples Unresolved cited work

Reference 6

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unresolved
raw_fallback, observed 2026-08-07T13:30:28.892016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:30:21.514743Z digest=sha256:4af9e011fb5fb7241c1adaf31674ff9c27401d3a144a108351ac869f853fe843

Observation 35335f18-4f8a-4071-8230-cadff30d80c1 · outbound

This paper cites Inference-time intervention: Eliciting truthful answers from a language model.

Aligning LLMs by Predicting Preferences from User Writing Samples Inference-time intervention: Eliciting truthful answers from a language model

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:28.782727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:30:21.614849Z digest=sha256:261778bf32f9f11bf841c3af6920a01e4381f8b5fd959bb58883f4ab5ff5a262

Observation c10bf89f-d525-48b5-8f5b-0b0875d8261d · outbound

This paper cites Prompt Optimization with Human Feedback.

Aligning LLMs by Predicting Preferences from User Writing Samples Prompt Optimization with Human Feedback

Reference 8

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no resolver link, observed 2026-08-07T13:30:21.687814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:21.687814Z digest=sha256:59f166fe7bda7d025cd86bcb4b0ddd959a66f904634a0a8f8d4cce6c3f9efee8

Observation fdc6afa4-afa7-48c5-9115-fe6e1fb0f131 · outbound

This paper cites an unresolved cited work.

Aligning LLMs by Predicting Preferences from User Writing Samples Unresolved cited work

Reference 9

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raw_fallback, observed 2026-08-07T13:30:28.679715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:30:21.797225Z digest=sha256:a6ab50c6bbfa2ab24eb7159c43df54d3d234beb7d614c0abbeb0c53539690e2e

Observation 6cf85125-6bc7-47ca-962d-b07785e76b5a · outbound

This paper cites Llm-powered hierarchical language agent for real-time human-ai coordination.

Aligning LLMs by Predicting Preferences from User Writing Samples Llm-powered hierarchical language agent for real-time human-ai coordination

Reference 10

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metadata mismatch
raw_fallback, observed 2026-08-07T13:30:25.904762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:30:21.937190Z digest=sha256:ff7a2045b39d045e4078e5482cb337c8492f4daac4dfed0b7413eeec27a140ae

Observation 39dc3f3c-40ec-498e-9178-81be1f084ad6 · outbound

This paper cites GPT-4 Technical Report.

Aligning LLMs by Predicting Preferences from User Writing Samples GPT-4 Technical Report

Reference 11

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source=arxiv_source observed=2026-08-07T13:30:22.045668Z digest=sha256:dc251c98abef81eeb33d2f3dd8fa9e02fd4ab18c6c5f99e31bf2f2a2d5872951

Observation 9d952153-77d8-4ce8-95f2-217def04825b · outbound

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

Aligning LLMs by Predicting Preferences from User Writing Samples Training language models to follow instructions with human feedback

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:22.158182Z digest=sha256:3ad9b79e19d7c93f3041cac7c68fc1dcd74eade104756db83802e35955ac1b10

Observation c0396970-80b8-4bcd-93cf-444f3c36a46c · outbound

This paper cites Z., Sumers, T.

Aligning LLMs by Predicting Preferences from User Writing Samples Z., Sumers, T

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-07T13:30:28.534367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:30:22.239944Z digest=sha256:6e6ffa07d0572c4adf57d7a92ca0b48e67f7c612d62581e11ea2483ea86ad071

Observation 7af9e6cc-2b41-4b39-bb56-5b36027e040a · outbound

This paper cites and Hruschka, E.

Aligning LLMs by Predicting Preferences from User Writing Samples and Hruschka, E

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:22.287941Z digest=sha256:7eb0c6c5bafd1ceab3aa16f996163cfe7b0ae22680f29f4b0d07f4e8e4a6b49b

Observation 10a1c055-94c4-474f-8fbf-51a2843b67a3 · outbound

This paper cites Language models are unsupervised multitask learners.

Aligning LLMs by Predicting Preferences from User Writing Samples Language models are unsupervised multitask learners

Reference 15

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source=arxiv_source observed=2026-08-07T13:30:22.376574Z digest=sha256:084895e243e69a6da9d383a12fa657ec83783dbe2bb20dfc267a97dce8d3aa54

Observation 301b8453-97ce-4af9-b7cc-e05b67074eea · outbound

This paper cites D., Ermon, S., and Finn, C.

Aligning LLMs by Predicting Preferences from User Writing Samples D., Ermon, S., and Finn, C

Reference 16

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no resolver link, observed 2026-08-07T13:30:22.503063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:22.503063Z digest=sha256:dd3ecc46ab6a4d3aa64e41b9c0cf9e894b9f90ce2cca7adf936a22e9d15e41df

Observation 431d7f5a-84a0-4a64-8de0-75affe2d92e4 · outbound

This paper cites LaMP: When Large Language Models Meet Personalization.

Aligning LLMs by Predicting Preferences from User Writing Samples LaMP: When Large Language Models Meet Personalization

Reference 17

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:22.645052Z digest=sha256:b7dad18d8c677499be514651270a869bc6132a7213696d43fd03c5de012ced8e

Observation 06b77df8-33f8-4cd7-9f65-7892a8689fe3 · outbound

This paper cites Whose opinions do language models reflect? In International Conference on Machine Learning, pp.\ 29971--30004.

Aligning LLMs by Predicting Preferences from User Writing Samples Whose opinions do language models reflect? In International Conference on Machine Learning, pp.\ 29971--30004

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:28.125665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:30:22.736290Z digest=sha256:48d6cc206d5873dfa2b4828f2a11a3805850685c65266e946caf1ede52cf4bfb

Observation 6a94c13f-caca-4a28-8740-1e285bcad0b0 · outbound

This paper cites Aligning Language Models with Demonstrated Feedback.

Aligning LLMs by Predicting Preferences from User Writing Samples Aligning Language Models with Demonstrated Feedback

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:22.805705Z digest=sha256:5c23ca7fb6a141315f5a8cb319d32bb88e5c313e0494d79f189d07af18b9c5df

Observation 546ccb6e-cca1-47fc-afdb-a3051f30cc15 · outbound

This paper cites an unresolved cited work.

Aligning LLMs by Predicting Preferences from User Writing Samples Unresolved cited work

Reference 20

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:22.899023Z digest=sha256:2fd3934709626e9685412ec83a82b6b943e710e9b45f07ae20e13e2545f1ae5f

Observation 03cdc084-2e30-449f-9ab8-c9380064f693 · outbound

This paper cites PMG : Personalized Multimodal Generation with Large Language Models.

Aligning LLMs by Predicting Preferences from User Writing Samples PMG : Personalized Multimodal Generation with Large Language Models

Reference 21

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verified exact
local_arxiv, observed 2026-08-07T13:30:24.984811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:30:23.026121Z digest=sha256:2d0c0726043c7ce5f7c39da6126e0013865f805411a3201410b8a9d31ff01211

Observation 668575e3-93c7-4c3b-a0be-401117460d2e · outbound

This paper cites M., Lowe, R., Voss, C., Radford, A., Amodei, D., and Christiano, P.

Aligning LLMs by Predicting Preferences from User Writing Samples M., Lowe, R., Voss, C., Radford, A., Amodei, D., and Christiano, P

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:27.855745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:30:23.121700Z digest=sha256:b8c78399e4645453f05657c81e5cbea6940652ec482f41aeb6c65a4448bf12d7

Observation cb612c1d-2226-4570-9657-f550653f3952 · outbound

This paper cites Principle-driven self-alignment of language models from scratch with minimal human supervision.

Aligning LLMs by Predicting Preferences from User Writing Samples Principle-driven self-alignment of language models from scratch with minimal human supervision

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-07T13:30:27.474739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:30:23.225440Z digest=sha256:fdbe7338ed4db1ecd252927b7de3a8817c173dd848be0d752b1f1865475a2633

Observation 20ffa8c8-64be-45d7-9aab-9fde5c193855 · outbound

This paper cites D., Yang, Y., and Gan, C.

Aligning LLMs by Predicting Preferences from User Writing Samples D., Yang, Y., and Gan, C

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:27.194950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:30:23.305705Z digest=sha256:f40d3f43c393051d236105aa6d770e8abedc77ecd287ad32f0bb1a357a6e3eb9

Observation 68f80e06-3d45-43a9-b360-e97ce81fa804 · outbound

This paper cites Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning.

Aligning LLMs by Predicting Preferences from User Writing Samples Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 25

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source=arxiv_source observed=2026-08-07T13:30:23.380941Z digest=sha256:4c3e47ad16c724265378ed76ecbaf1a628dd1875c8b9b0394076656ea117bac7

Observation b1a8d50d-e3da-46e1-8b9c-aff4224f09ed · outbound

This paper cites Steering Language Models With Activation Engineering.

Aligning LLMs by Predicting Preferences from User Writing Samples Steering Language Models With Activation Engineering

Reference 26

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:23.460336Z digest=sha256:aff4d4653ee4fd22c25e6346b028c6a2836a11350d84559630f8c14208a1f0cf

Observation e25facdc-56ba-481a-af1c-2b9d10df184d · outbound

This paper cites Qwen2.5 Technical Report.

Aligning LLMs by Predicting Preferences from User Writing Samples Qwen2.5 Technical Report

Reference 27

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unresolved
no resolver link, observed 2026-08-07T13:30:23.584750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:23.584750Z digest=sha256:750811953e260c6a245adfd6ffec30f2be67af746184db845036b1e4b6162a00

Observation 0714e5d9-3102-4d17-a6a2-b02ac8245622 · outbound

This paper cites Y., Hartmann, B., and Yang, Q.

Aligning LLMs by Predicting Preferences from User Writing Samples Y., Hartmann, B., and Yang, Q

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:26.956302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:30:23.667806Z digest=sha256:cc417d7118907e32dc4fa52f3246659f721ca9ac7eac494312538d7733b26fee

Observation 28489972-3aec-4062-acb2-540f8b0dcad1 · outbound

This paper cites Q., and Artzi, Y.

Aligning LLMs by Predicting Preferences from User Writing Samples Q., and Artzi, Y

Reference 29

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no resolver link, observed 2026-08-07T13:30:23.754751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:23.754751Z digest=sha256:ca99b271d5b9cad22a85e48bae10f33ecff81f869beab0c376a4e1b2eec596c7

Observation b4c15a79-e315-4e43-92ba-61b6833b7de9 · outbound

This paper cites E., and Stoica, I.

Aligning LLMs by Predicting Preferences from User Writing Samples E., and Stoica, I

Reference 30

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no resolver link, observed 2026-08-07T13:30:23.807838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:23.807838Z digest=sha256:8bfb24e0475c851a01fe8b979b4e13af6bd4dc9db31e371e10e55c5096f27286

Observation 1c936125-0d5d-4c7c-ae55-4784b2b0994b · outbound

This paper cites Large Language Models Are Human-Level Prompt Engineers.

Aligning LLMs by Predicting Preferences from User Writing Samples Large Language Models Are Human-Level Prompt Engineers

Reference 31

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no resolver link, observed 2026-08-07T13:30:23.876476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:23.876476Z digest=sha256:5e0152a0f14fab4586119e589e1a5157a763fb1758048baa63e77e7c2773b580

Observation 9a5de857-ba1f-40f6-a0c4-ee416d66231e · outbound

This paper cites HYDRA: Model Factorization Framework for Black-Box LLM Personalization.

Aligning LLMs by Predicting Preferences from User Writing Samples HYDRA: Model Factorization Framework for Black-Box LLM Personalization

Reference 32

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no resolver link, observed 2026-08-07T13:30:23.975627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:23.975627Z digest=sha256:513520628cc7df627f19e8f8dfb95eaa94b36a6f82ee9e7559e69497ac98e5d5

Observation e437c8c6-8424-4950-97cc-fd3fc54b0e10 · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

Aligning LLMs by Predicting Preferences from User Writing Samples Fine-Tuning Language Models from Human Preferences

Reference 33

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no resolver link, observed 2026-08-07T13:30:24.009574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:24.009574Z digest=sha256:7f5bb98eb7fca7457c66d33569538eb681ca9986ed80b62b46f3fe7434834792

Observation e2b6b2da-0958-4c1d-b2cd-cade2d81ddee · outbound

This paper cites @esa (Ref.

Aligning LLMs by Predicting Preferences from User Writing Samples @esa (Ref

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:24.084746Z digest=sha256:423c50025916c8752708a974d18b973cddaa7eace1d4343647ca601ac4f08e93

Observation b86dbe9c-96c9-4c39-8182-b9d23b67b249 · outbound

This paper cites an unresolved cited work.

Aligning LLMs by Predicting Preferences from User Writing Samples Unresolved cited work

Reference 35

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no resolver link, observed 2026-08-07T13:30:24.167968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:24.167968Z digest=sha256:6782ea3263a0caf898479917ba2c8e9667b722db5aed969abd958f1537aa460d

Observation 3602191d-48be-4126-8e30-4f43296dd175 · outbound

This paper cites an unresolved cited work.

Aligning LLMs by Predicting Preferences from User Writing Samples Unresolved cited work

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:24.218058Z digest=sha256:5b4bcb2cc8cf5a7f130165a23c6376bac5a7d8584a648e10f128ddca39b5d214

Pith citing papers

No inbound Pith citation observations are available.