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Paper Citation Record · LEDGER

Watermarking across Modalities for Content Tracing and Generative AI

As of 10 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2502.05215.

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

pith.paper-citation-record.v1
2502.05215 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:46:23.205545Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

33 of 33 outbound references displayed

  • verified exact1
  • verified fuzzy3
  • unresolved28
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 17da1c9a-18c3-4e11-bfa1-38d071b070e8 · outbound

This paper cites An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion.

Watermarking across Modalities for Content Tracing and Generative AI An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

Reference 7

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source=pdf_text observed=2026-08-09T11:46:23.088415Z digest=sha256:aed2dc7ffa848ff549645721e6b8b1b2c7a7ece3e4902e521342c7ccef96391d

Observation b6fbdde1-239e-4e38-a130-071eb18838a0 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Watermarking across Modalities for Content Tracing and Generative AI Training Compute-Optimal Large Language Models

Reference 9

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source=pdf_text observed=2026-08-09T11:46:23.097403Z digest=sha256:f521f2fdb209b7a65ad4f4ca945e7d3287a9b75907ecac6a292d1059ef45934c

Observation 6c31919c-bde5-486b-9e53-1caf687483e8 · outbound

This paper cites Mixtral of Experts.

Watermarking across Modalities for Content Tracing and Generative AI Mixtral of Experts

Reference 11

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source=pdf_text observed=2026-08-09T11:46:23.106421Z digest=sha256:9f40f268bff2f958ac2eb64b7d1e340e2c76f46630d85acc81bb06c59347777c

Observation 69cc228f-e7a1-4d2f-9750-ea66f8df7daf · outbound

This paper cites Watermark Stealing in Large Language Models.

Watermarking across Modalities for Content Tracing and Generative AI Watermark Stealing in Large Language Models

Reference 12

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source=pdf_text observed=2026-08-09T11:46:23.110929Z digest=sha256:3d576e5a92bb32208741a7b80aaa48c5046e9ab8a8b9d8bca8e92a9bc2bb0788

Observation 7b6c77fb-1536-4e81-8c84-d30d1c5cd30c · outbound

This paper cites Scaling Laws for Neural Language Models.

Watermarking across Modalities for Content Tracing and Generative AI Scaling Laws for Neural Language Models

Reference 13

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source=pdf_text observed=2026-08-09T11:46:23.115672Z digest=sha256:f60d7b4b813b8ad37c75d877132b6decabea05b6aef5ff7e76e08f6f315865c0

Observation ea6fdf99-c86f-4979-9a02-e9f0147347e9 · outbound

This paper cites AudioGen: Textually Guided Audio Generation.

Watermarking across Modalities for Content Tracing and Generative AI AudioGen: Textually Guided Audio Generation

Reference 14

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source=pdf_text observed=2026-08-09T11:46:23.120195Z digest=sha256:b0e3f794af8c323e1e9a452b98e2a52dbe953cd64b9d98aa764313f9cd2d54b5

Observation 43324ef5-5fdc-4982-8528-a408de310342 · outbound

This paper cites Membership Inference on Word Embedding and Beyond.

Watermarking across Modalities for Content Tracing and Generative AI Membership Inference on Word Embedding and Beyond

Reference 16

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source=pdf_text observed=2026-08-09T11:46:23.129851Z digest=sha256:d633f43f8a6a97cad8f62e269c481b7860b307d0802695c570b982816a2144b2

Observation 15bd14ff-4a5d-4766-8bd4-c86d4fecee78 · outbound

This paper cites The Llama 3 Herd of Models.

Watermarking across Modalities for Content Tracing and Generative AI The Llama 3 Herd of Models

Reference 17

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source=pdf_text observed=2026-08-09T11:46:23.134318Z digest=sha256:f4b4e14a455fcf21e3bcc730026f1d1183389c5bc0c938181247346a2c240f3d

Observation 80372540-ad80-455d-9481-446f38e02808 · outbound

This paper cites Null-text Inversion for Editing Real Images using Guided Diffusion Models.

Watermarking across Modalities for Content Tracing and Generative AI Null-text Inversion for Editing Real Images using Guided Diffusion Models

Reference 18

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source=pdf_text observed=2026-08-09T11:46:23.138935Z digest=sha256:fbce637422be2e1b532fbe27e7c1970ae4999250f958f859e746394efa4283ee

Observation 91d4dc7d-9225-4bdb-823d-779aebc5b0d5 · outbound

This paper cites Robust image watermarking in the spatial domain.Signal processing, 1998.

Watermarking across Modalities for Content Tracing and Generative AI Robust image watermarking in the spatial domain.Signal processing, 1998

Reference 19

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-09T11:46:23.144239Z digest=sha256:2b40001b34b742cfb5af57c186c21e9041f706fa6b1614a16f41f159a52cc33b

Observation f4c5e5fd-2ed4-40b3-99f2-8d84993ab1e1 · outbound

This paper cites MarkLLM: An Open-Source Toolkit for LLM Watermarking.

Watermarking across Modalities for Content Tracing and Generative AI MarkLLM: An Open-Source Toolkit for LLM Watermarking

Reference 20

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source=pdf_text observed=2026-08-09T11:46:23.148479Z digest=sha256:08a045f25bfb4f684a555e708d7b5fb28d7f65868e7a585d580677767d1d31be

Observation 24d63e47-4748-4b49-925a-c9b3616f7e47 · outbound

This paper cites Dct-based watermark recovering without resorting to the uncorrupted original image.

Watermarking across Modalities for Content Tracing and Generative AI Dct-based watermark recovering without resorting to the uncorrupted original image

Reference 21

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T11:46:23.152898Z digest=sha256:559b06eb4a7a56dd308ce59cdd1d935857eac24e9efc552409b2be6cfd6bab45

Observation bdd8fde9-6f77-45a3-a1a8-a24357632ad0 · outbound

This paper cites Provably Robust Multi-bit Watermarking for AI-generated Text.

Watermarking across Modalities for Content Tracing and Generative AI Provably Robust Multi-bit Watermarking for AI-generated Text

Reference 22

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source=pdf_text observed=2026-08-09T11:46:23.157014Z digest=sha256:ca29d66e1c3103bfc8a24d0371b33e8d3fa1d7cc9a7ddc4de2153bd787353f7d

Observation e70fc1e1-303f-4a96-9b3f-2e8e6bb61cf4 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Watermarking across Modalities for Content Tracing and Generative AI Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 23

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source=pdf_text observed=2026-08-09T11:46:23.161628Z digest=sha256:a68769823ee84646253e22681ac557f6a24f91ad70baffb545cffa1360cf5963

Observation a7a52313-6d62-4cc4-9c18-d1b341771f40 · outbound

This paper cites Neural Machine Translation of Rare Words with Subword Units.

Watermarking across Modalities for Content Tracing and Generative AI Neural Machine Translation of Rare Words with Subword Units

Reference 24

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source=pdf_text observed=2026-08-09T11:46:23.166231Z digest=sha256:b241c7074ee67c70f429a4dc9794c3bde1530fa4532a6d7101cbdbeb9c891632

Observation 908b72a9-d1da-4e88-a172-bb08a85933b6 · outbound

This paper cites RoFormer: Enhanced Transformer with Rotary Position Embedding.

Watermarking across Modalities for Content Tracing and Generative AI RoFormer: Enhanced Transformer with Rotary Position Embedding

Reference 25

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source=pdf_text observed=2026-08-09T11:46:23.170935Z digest=sha256:cabe6e8e90daae3ff34d1ddf9027de67e435aea2b256f4bf3ff0ddceb5169532

Observation e9e764aa-33fb-4f6c-99c5-9c761be60717 · outbound

This paper cites Snr-constrained heuristics for optimizing the scaling parameter of robust audio watermarking.IEEE Trans.

Watermarking across Modalities for Content Tracing and Generative AI Snr-constrained heuristics for optimizing the scaling parameter of robust audio watermarking.IEEE Trans

Reference 26

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source=pdf_text observed=2026-08-09T11:46:23.175048Z digest=sha256:5bfe44c942bca3edb027ef47a739aad3697dfbbd6211b7316b7e36b62fe97307

Observation 85da5622-e2f4-48bc-8013-25534c4e67a7 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Watermarking across Modalities for Content Tracing and Generative AI LLaMA: Open and Efficient Foundation Language Models

Reference 27

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source=pdf_text observed=2026-08-09T11:46:23.179300Z digest=sha256:c2175c7a88cfdffec72820d33e46773445c538195f3f56e9827b6498cf86da5e

Observation 42745c84-4f9a-4081-98e2-6ba54818cf0f · outbound

This paper cites Lightfieldmessagingwithdeepphotographicsteganography.

Watermarking across Modalities for Content Tracing and Generative AI Lightfieldmessagingwithdeepphotographicsteganography

Reference 31

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source=pdf_text observed=2026-08-09T11:46:23.196985Z digest=sha256:cecb22b63c734a4140bd6acb4724e1d8d2d3d96ae71fee4bde263b98fe04b80d

Observation 8c89fa09-e44d-4aac-baef-3d9051e49870 · outbound

This paper cites Unifying Diffusion Models' Latent Space, with Applications to CycleDiffusion and Guidance.

Watermarking across Modalities for Content Tracing and Generative AI Unifying Diffusion Models' Latent Space, with Applications to CycleDiffusion and Guidance

Reference 32

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source=pdf_text observed=2026-08-09T11:46:23.201046Z digest=sha256:3962ff18239c4abf346f560daab69c2bb3821a094c34ac76f9be69482f929908

Observation 53944e93-4520-4cfd-9871-f1e153b6021a · outbound

This paper cites Vector-quantized Image Modeling with Improved VQGAN.

Watermarking across Modalities for Content Tracing and Generative AI Vector-quantized Image Modeling with Improved VQGAN

Reference 33

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source=pdf_text observed=2026-08-09T11:46:23.205545Z digest=sha256:bfeb01397416b68e1859ed93d08ebf65b6b6b937a654365225e2489e44f8e6fe

Observation 1d60a02f-a961-4453-a433-5e76ee8022b1 · outbound

This paper cites On the Importance of Difficulty Calibration in Membership Inference Attacks.

Watermarking across Modalities for Content Tracing and Generative AI On the Importance of Difficulty Calibration in Membership Inference Attacks

Reference 1993

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source=pdf_text observed=2026-08-09T11:46:23.192542Z digest=sha256:f322f44153e73b43fc5459f76fac8363da935db25d67916c41cd7ca24a0e5a37

Observation 10688d71-1672-4556-8c46-c3c322f0810c · outbound

This paper cites HowkGPT: Investigating the Detection of ChatGPT-generated University Student Homework through Context-Aware Perplexity Analysis.

Watermarking across Modalities for Content Tracing and Generative AI HowkGPT: Investigating the Detection of ChatGPT-generated University Student Homework through Context-Aware Perplexity Analysis

Reference 1994

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source=pdf_text observed=2026-08-09T11:46:23.183741Z digest=sha256:c825042fa8dcdd136f65125bc9178c45a25b6339ccf1dc8ecc5e2ebdc3938c72

Observation 23c907a3-1547-40a4-a428-d01fa510d1ef · outbound

This paper cites SoundStorm: Efficient Parallel Audio Generation.

Watermarking across Modalities for Content Tracing and Generative AI SoundStorm: Efficient Parallel Audio Generation

Reference 1996

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source=pdf_text observed=2026-08-09T11:46:23.072517Z digest=sha256:c091286be213d5b470bb8c02e738deab6c7f71216c31d7d51216004818ab85e2

Observation fdf8cc5d-6164-4670-9a03-168e14d9e85d · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Watermarking across Modalities for Content Tracing and Generative AI Measuring Massive Multitask Language Understanding

Reference 1997

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source=pdf_text observed=2026-08-09T11:46:23.093021Z digest=sha256:2b99e6a5d59d88ac06d1e629eeb6d819a40503c978c39c79eae166c9e0c0d353

Observation 46aeac13-7e49-4029-add8-f691bb580e80 · outbound

This paper cites Efficient Image Generation with Variadic Attention Heads.

Watermarking across Modalities for Content Tracing and Generative AI Efficient Image Generation with Variadic Attention Heads

Reference 2012

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local_arxiv, observed 2026-08-09T11:46:23.299718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T11:46:23.187963Z digest=sha256:8212a75f444475617878dc329ecb4815a87e7b1756e0807c6aa2aa92c1229231

Observation 7a3ed29e-7ebd-477d-bbc8-11f4ccf548e8 · outbound

This paper cites EAGLE: A Domain Generalization Framework for AI-generated Text Detection.

Watermarking across Modalities for Content Tracing and Generative AI EAGLE: A Domain Generalization Framework for AI-generated Text Detection

Reference 2013

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source=pdf_text observed=2026-08-09T11:46:23.067675Z digest=sha256:fdd3f52d9e514370be2f5edc78fd0e9b643ace385249050917b90a7cbc508249

Observation 354f022b-6d08-42c9-badf-07a5187e1013 · outbound

This paper cites Who Wrote this Code? Watermarking for Code Generation.

Watermarking across Modalities for Content Tracing and Generative AI Who Wrote this Code? Watermarking for Code Generation

Reference 2015

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source=pdf_text observed=2026-08-09T11:46:23.125023Z digest=sha256:206c3c61f0ebf79fc3c376993f38052a1c6c5eb5b52002a9ca0be6f950a35a7a

Observation afd6a256-8f37-482b-9e3a-fab4d8938168 · outbound

This paper cites Stable Signature is Unstable: Removing Image Watermark from Diffusion Models.

Watermarking across Modalities for Content Tracing and Generative AI Stable Signature is Unstable: Removing Image Watermark from Diffusion Models

Reference 2018

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source=pdf_text observed=2026-08-09T11:46:23.101769Z digest=sha256:ffc752fe851c19f81301a2f2027cde6b368e3c81cfba344e2677d7e8a6acecc5

Observation 6214a7f4-1f51-436b-a9e0-ccdf9edab361 · outbound

This paper cites WMAdapter: Adding WaterMark Control to Latent Diffusion Models.

Watermarking across Modalities for Content Tracing and Generative AI WMAdapter: Adding WaterMark Control to Latent Diffusion Models

Reference 2019

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source=pdf_text observed=2026-08-09T11:46:23.077744Z digest=sha256:d2c3df5838bb008ccae54c5392024a73dd50d86a177c75d873f51bfa5cef3ffe

Observation 8a970900-4a3f-4af4-b1e8-96d6986b1fea · outbound

This paper cites The 2021 Image Similarity Dataset and Challenge.

Watermarking across Modalities for Content Tracing and Generative AI The 2021 Image Similarity Dataset and Challenge

Reference 2021

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source=pdf_text observed=2026-08-09T11:46:23.082966Z digest=sha256:4b1a1c70221ca01548585ba6bf60500cc0119211c3b4cdf45d4f23e220e96798

Observation 25f25f0e-8ac1-44d4-949e-6aa22a1d3f8c · outbound

This paper cites eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers.

Watermarking across Modalities for Content Tracing and Generative AI eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers

Reference 2022

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source=pdf_text observed=2026-08-09T11:46:23.056519Z digest=sha256:dce4100b531ed434c2cf58acd7dff59a1322293912935b884b1083131ad6fb34

Observation 1ff48bd7-75c7-47e9-abd5-5dc7d3e3703c · outbound

This paper cites CompressAI: a PyTorch library and evaluation platform for end-to-end compression research.

Watermarking across Modalities for Content Tracing and Generative AI CompressAI: a PyTorch library and evaluation platform for end-to-end compression research

Reference 2023

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source=pdf_text observed=2026-08-09T11:46:23.062311Z digest=sha256:e761275ae8e45c02ba4f5caeac17e6af20fa727dc110713cc5c25dfedd41f6ea

Pith citing papers

No inbound Pith citation observations are available.