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Paper Citation Record · LEDGER

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts

As of 9 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2607.20462.

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

pith.paper-citation-record.v1
2607.20462 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T13:52:10.042016Z

measured 44 of 44 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

44 of 44 outbound references displayed

  • verified exact3
  • verified fuzzy0
  • unresolved39
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 783f8749-fdfc-4431-ae65-54298d8afd1e · outbound

This paper cites 2026 physician survey on augmented intelligence.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts 2026 physician survey on augmented intelligence

Reference 1

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source=pdf_text observed=2026-08-02T13:52:06.658640Z digest=sha256:019bffde8012b70931f7229803f8f580c3153e2417e0d97c5cbec02108a95896

Observation bea3622a-2d62-44ee-baab-c17aa17093c0 · outbound

This paper cites Gowda, Meer C.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Gowda, Meer C

Reference 2

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doi, observed 2026-08-02T13:53:25.256995Z

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source=pdf_text observed=2026-08-02T13:52:06.762968Z digest=sha256:bfb01665e0e17a04e44a2d0ccaa773f641f26d5a3268140b91e19b743ffb85c5

Observation 5f9d6ae9-1876-48a0-8186-8e5ab57691e0 · outbound

This paper cites Weissman, Toni Mankowitz, and Genevieve P.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Weissman, Toni Mankowitz, and Genevieve P

Reference 3

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source=pdf_text observed=2026-08-02T13:52:06.925097Z digest=sha256:1bb1cf7c710fd00cc57965222a3051dc4577a4737b59a632e9c73a45907b6027

Observation 756f2688-1494-40c5-8c38-15b2005615be · outbound

This paper cites Regulation (EU) 2024/1689 of the European Parliament and of the Council laying down harmonised rules on artificial intelligence (AI Act).

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Regulation (EU) 2024/1689 of the European Parliament and of the Council laying down harmonised rules on artificial intelligence (AI Act)

Reference 4

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source=pdf_text observed=2026-08-02T13:52:07.034217Z digest=sha256:2d1cd7111654baa242aa71077830591f5dde6eec80374492e6fb275ae4a76bed

Observation 6a9f0836-8dfe-4373-b477-52e4a57b4c06 · outbound

This paper cites Second draft code of practice on marking and labelling of AI-generated content.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Second draft code of practice on marking and labelling of AI-generated content

Reference 5

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source=pdf_text observed=2026-08-02T13:52:07.190533Z digest=sha256:3fb6952efa40a8637edea12926e8ab16065b0b99331506aa1aa90ae71c724977

Observation a2590ecc-a5f8-4d69-8877-4b8def378a86 · outbound

This paper cites WaterBench: Towards holistic evaluation of watermarks for large language models.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts WaterBench: Towards holistic evaluation of watermarks for large language models

Reference 6

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source=pdf_text observed=2026-08-02T13:52:07.485409Z digest=sha256:b44a442798b655da909e5af4c057e89f9c424bf110f90875679edee9c5c32207

Observation 05395fc4-457f-44fa-a622-f7413a32db5a · outbound

This paper cites Adams, and Keno K.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Adams, and Keno K

Reference 7

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source=pdf_text observed=2026-08-02T13:52:07.548806Z digest=sha256:49c2afd0fa24524794586338c935682d0444b6a1874443f8bd832315863acbf7

Observation f1cc4f28-4915-41d1-96d3-1fc771b90657 · outbound

This paper cites Evaluation and mitigation of the limitations of large language models in clinical decision-making.Nature Medicine, 30:2613–2622, 2024.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Evaluation and mitigation of the limitations of large language models in clinical decision-making.Nature Medicine, 30:2613–2622, 2024

Reference 8

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source=pdf_text observed=2026-08-02T13:52:07.615785Z digest=sha256:a023b927fb83bd2343b107877193ef38f4a6d78cef7fb279dbdb3e006f71e862

Observation 30c58ed8-4a76-438f-aa27-06db3c905964 · outbound

This paper cites What disease does this patient have? a large-scale open domain question answering dataset from medical exams.Applied Sciences, 11(14):6421, 2021.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts What disease does this patient have? a large-scale open domain question answering dataset from medical exams.Applied Sciences, 11(14):6421, 2021

Reference 9

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source=pdf_text observed=2026-08-02T13:52:07.701231Z digest=sha256:3c8352ee29ca1515d8a43cb0604b9cf39c504b7e9f39ea743075729123451fa3

Observation fc89b9ab-1259-4958-8829-bebef03aedcb · outbound

This paper cites an unresolved cited work.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Unresolved cited work

Reference 10

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verified exact
doi, observed 2026-08-02T13:53:24.499875Z

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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=2026-08-02T13:52:07.758350Z digest=sha256:550f37ae3acb113c54f3b4e10d44c21d6b9559e026b7bd713f01a03bb3c82b42

Observation 3893950d-7b77-440f-92aa-c7bc032972aa · outbound

This paper cites Hu et al.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Hu et al

Reference 11

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source=pdf_text observed=2026-08-02T13:52:07.823463Z digest=sha256:77b5e8c9d09d91adda9c6ee75f7b31e8a24a7bc292a183e011852dd8f3133e4f

Observation 0c79f66d-e09c-4af3-a27e-78e5f01b2b7f · outbound

This paper cites GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AI.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AI

Reference 12

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source=pdf_text observed=2026-08-02T13:52:07.866376Z digest=sha256:3c833f127df88a755f7036d4373506f8f6013c557828b882982dd5a3c9431991

Observation 91269e56-7bc3-4f7c-9000-d352c58b5e09 · outbound

This paper cites MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding

Reference 13

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source=pdf_text observed=2026-08-02T13:52:07.924487Z digest=sha256:ca3684dc7ddc816365f3a34279ec4e16dc54529796d58fc383cde72445429c47

Observation b1a95139-86d5-41e4-9b1f-9eec5a622440 · outbound

This paper cites Right Prediction, Wrong Reasoning: Uncovering LLM Misalignment in RA Disease Diagnosis.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Right Prediction, Wrong Reasoning: Uncovering LLM Misalignment in RA Disease Diagnosis

Reference 14

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source=pdf_text observed=2026-08-02T13:52:07.978709Z digest=sha256:8d5e3491655ea7d1cf81c8f2dc38261f861d4659fd128cfb3b2b7e179af946c7

Observation e774f4d5-dd74-48e9-985d-fd689aeab6dc · outbound

This paper cites Med-HALT: Medical domain hallucination test for large language models.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Med-HALT: Medical domain hallucination test for large language models

Reference 15

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source=pdf_text observed=2026-08-02T13:52:08.060621Z digest=sha256:e22f128d41654d7541df9bf567779de75913f1df3f5bfc3854ac40b7415b84bb

Observation d6d4520c-c76a-444d-a9e3-9d8211565557 · outbound

This paper cites Clinical large language model evaluation by expert review (CLEVER): Framework development and validation.JMIR AI, 4(1):e72153, 2025.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Clinical large language model evaluation by expert review (CLEVER): Framework development and validation.JMIR AI, 4(1):e72153, 2025

Reference 16

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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=2026-08-02T13:52:08.122902Z digest=sha256:cec7f4fe3d05d9c0d36b4a504c7ba308f696258c599f75166953d48100a4d5dc

Observation cf273ccb-e1a5-44ae-a50c-53ceb563caae · outbound

This paper cites HealthBench: Evaluating Large Language Models Towards Improved Human Health.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts HealthBench: Evaluating Large Language Models Towards Improved Human Health

Reference 17

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source=pdf_text observed=2026-08-02T13:52:08.174030Z digest=sha256:b5f5920fab793c2942d7d87332d4a2b81f79b94b24e0f63cfdd02ab669091a37

Observation e55e239a-fee2-48c7-be3c-8414812a22b3 · outbound

This paper cites A Survey of Text Watermarking in the Era of Large Language Models.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts A Survey of Text Watermarking in the Era of Large Language Models

Reference 18

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source=pdf_text observed=2026-08-02T13:52:08.235584Z digest=sha256:019de1076fd1fafa50031c249473244c3d0c400f64018c565c7c5168580abd62

Observation 76c79d4c-5e80-4fba-8fca-90253b9394df · outbound

This paper cites A watermark for large language models.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts A watermark for large language models

Reference 19

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source=pdf_text observed=2026-08-02T13:52:08.286511Z digest=sha256:d9b5e8362bdb090acf39aeea28d8eb2d321e193c83ec0f87fc3b36a4ded62ef0

Observation 78705dfb-1f5c-4ec9-b8c6-30138689338d · outbound

This paper cites A unified framework for llm watermarks, 2026.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts A unified framework for llm watermarks, 2026

Reference 20

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source=pdf_text observed=2026-08-02T13:52:08.295781Z digest=sha256:7c54779362cc0af0fe53fb79b252f95f5421b9c0687df93b91a5572f78ad5949

Observation bc85d6b7-decb-44fe-8b3e-8241fd7a6419 · outbound

This paper cites Dipmark: A stealthy, efficient and resilient watermark for large language models.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Dipmark: A stealthy, efficient and resilient watermark for large language models

Reference 21

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source=pdf_text observed=2026-08-02T13:52:08.316121Z digest=sha256:37f52b8c0a91de72c09a5c7e0aa043aae9b55b8ae74c373f26efbba1819ee6fe

Observation d91a2457-4eb7-4f89-82fa-089a7211a822 · outbound

This paper cites Watermarking of large language models.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Watermarking of large language models

Reference 22

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source=pdf_text observed=2026-08-02T13:52:08.460409Z digest=sha256:72f223df7dcb61f133b8d47e4bb85c116bf69ea8bc7b0991ca4398aa441d61ff

Observation bae609b7-224e-4a81-84c5-3f2dc63be9e4 · outbound

This paper cites Scalable watermarking for identifying large language model outputs.Nature, 634(8035):818–823, 2024.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Scalable watermarking for identifying large language model outputs.Nature, 634(8035):818–823, 2024

Reference 23

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source=pdf_text observed=2026-08-02T13:52:08.600408Z digest=sha256:dcc295de26b2625b79abc5379a879be1ef8284fb3e7464504136f89bfd573a8a

Observation 780a5121-1972-4c2b-9c49-53a8431ef975 · outbound

This paper cites Robust distortion- free watermarks for language models.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Robust distortion- free watermarks for language models

Reference 24

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source=pdf_text observed=2026-08-02T13:52:08.718721Z digest=sha256:5b42938177ab43293c138c781bc4b4550aedbf9984515bd68e45a8a413938a65

Observation dc0a0d99-cb81-477f-8022-ca16b3683eaf · outbound

This paper cites Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness

Reference 25

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source=pdf_text observed=2026-08-02T13:52:08.772681Z digest=sha256:c079022606223ba312873e12e26453895cc1e264ceb87eca0240cf2d3c2b3e92

Observation cd9c35e0-7d5b-4beb-b6d1-3fe2d9dcfe92 · outbound

This paper cites Who wrote this code? watermarking for code generation.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Who wrote this code? watermarking for code generation

Reference 26

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source=pdf_text observed=2026-08-02T13:52:08.828408Z digest=sha256:89b9f49dd10f0a175c4e201713676a94ca87d93b06dc08addda441b411a54b38

Observation 24ca80a4-6971-447b-85b2-80f82f9389d4 · outbound

This paper cites WatME: Towards lossless watermarking through lexical redundancy.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts WatME: Towards lossless watermarking through lexical redundancy

Reference 27

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verified exact
doi, observed 2026-08-02T13:53:23.839302Z

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=2026-08-02T13:52:08.933606Z digest=sha256:67915865d7d527a8ad72e85a4519bf520170bdc0135d6df613ea3c2d802e97fe

Observation fd70e832-e009-4f7f-8dbc-1e38ad8d6282 · outbound

This paper cites Distilling the thought, watermarking the answer: A principle semantic guided watermark for reasoning large language models.OpenReview, 2026.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Distilling the thought, watermarking the answer: A principle semantic guided watermark for reasoning large language models.OpenReview, 2026

Reference 28

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source=pdf_text observed=2026-08-02T13:52:08.993007Z digest=sha256:0acce7396bbb397b070919492f0b07d268d8c8ffe814c089d024a57a70dfb39b

Observation 90f8b60f-c079-4b3b-aec9-69683b36faa9 · outbound

This paper cites Factuality beyond coherence: Evaluating LLM watermarking methods for medical texts.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Factuality beyond coherence: Evaluating LLM watermarking methods for medical texts

Reference 29

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source=pdf_text observed=2026-08-02T13:52:09.062725Z digest=sha256:50832adc65631ed001d74072f3f383b1838ac0b229183183273ee93d81af6f9b

Observation e55ac359-7ccc-4171-b528-9f65f63a0392 · outbound

This paper cites The Llama 3 Herd of Models.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts The Llama 3 Herd of Models

Reference 30

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source=pdf_text observed=2026-08-02T13:52:09.125400Z digest=sha256:0e981111d127dc47ec60e4e9bcde575d4a7737f12d03a0fb9154114772e4e8cc

Observation 262b438c-4a55-4767-a9de-f469fbc9bab1 · outbound

This paper cites Gemma 3 Technical Report.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Gemma 3 Technical Report

Reference 31

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source=pdf_text observed=2026-08-02T13:52:09.178667Z digest=sha256:55448851471cbead8ab862fbc955d79b7df9574719326f2ec5ce18c8c6eb0480

Observation f52c7146-9c44-4f72-a46c-fa1eabc08b98 · outbound

This paper cites Phi-4 Technical Report.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Phi-4 Technical Report

Reference 32

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source=pdf_text observed=2026-08-02T13:52:09.240197Z digest=sha256:63c68ed0f1734e5157b025ca48fab3c597445b63d58ec665e22bdf00e96f221f

Observation 56bb0ab4-a76e-448e-9d21-ee9a588aba96 · outbound

This paper cites OpenBioLLMs: Advancing open-source large language models for healthcare and life sciences.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts OpenBioLLMs: Advancing open-source large language models for healthcare and life sciences

Reference 33

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source=pdf_text observed=2026-08-02T13:52:09.283359Z digest=sha256:bc5181f644e3c5078ce8c1f88067db10b4c8dbabf6bc589b7cb7f9635be01f19

Observation 925b2a94-4114-4997-937f-2785e5506aeb · outbound

This paper cites UltraMedical: Building Specialized Generalists in Biomedicine.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts UltraMedical: Building Specialized Generalists in Biomedicine

Reference 34

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source=pdf_text observed=2026-08-02T13:52:09.335865Z digest=sha256:576a385ebccbdaa4a89df721942874f71a7a8e8363635535d0bde7a9ff013993

Observation edf2e9d7-2094-4b0d-9c1a-7366cde0541d · outbound

This paper cites DeepSeek-R1: Incentivizing reason- ing capability in LLMs via reinforcement learning.Nature, 645:633–638, 2025.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts DeepSeek-R1: Incentivizing reason- ing capability in LLMs via reinforcement learning.Nature, 645:633–638, 2025

Reference 35

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source=pdf_text observed=2026-08-02T13:52:09.418688Z digest=sha256:8763b2ea50d9991f9cf1cb775e7d1822b1880b01a4db5594c093e2b0979d102d

Observation 544122aa-a92a-4c4a-90cd-d3b90f8dcc08 · outbound

This paper cites Qwen3.5: Towards native multimodal agents, February 2026.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Qwen3.5: Towards native multimodal agents, February 2026

Reference 36

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source=pdf_text observed=2026-08-02T13:52:09.500727Z digest=sha256:72e4041092ac4ff65a51802a0023b86b152921067be16e1a51bf58538bfc548c

Observation 3ceeff89-e153-485e-bd87-b6ad45f0cfee · outbound

This paper cites Qwen3 technical report.arXiv preprint, 2025.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Qwen3 technical report.arXiv preprint, 2025

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-02T13:52:09.555148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:52:09.555148Z digest=sha256:e2657c71bbe7e1e7adcce11f3c194872d16d269f221b34b4153006bbdd38ab84

Observation 2e1dae17-24c5-4492-bca1-2e845b0693a3 · outbound

This paper cites Gemma 4: Expanding the gemmaverse with Apache 2.0, April 2026.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Gemma 4: Expanding the gemmaverse with Apache 2.0, April 2026

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-02T13:52:09.631297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:52:09.631297Z digest=sha256:2ecf1a87f4ca4de50cf4407cd279a8033e9eaed2896f80d134ed07da7c856eb4

Observation dbb29d8e-86ed-4283-b1c6-9c45e01b1769 · outbound

This paper cites Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-02T13:52:09.717618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:52:09.717618Z digest=sha256:60fb25530e094780d8ef23648bd25099f6bb3cd2cf281a04d619109303776a2e

Observation 4f86d1d6-ea79-436a-99b9-c8f357b18b13 · outbound

This paper cites MedGemma Technical Report.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts MedGemma Technical Report

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-02T13:52:09.783385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:52:09.783385Z digest=sha256:5ee4768cedb3f4000bdc0dd8b04cfd787f8cdf0107967afe5f3c45b54b044dc8

Observation 9008f87f-b6da-43be-9933-57ec79d56d00 · outbound

This paper cites the answer is X.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts the answer is X

Reference 42

Resolution
malformed identifier
no resolver link, observed 2026-08-02T13:52:09.850340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:52:09.850340Z digest=sha256:2398b109b510a06b74920cbb573f26e382bb18e4b35e011800f535a8795b65ba

Observation 87c4ebef-5c52-468c-a797-e4fc2c00d108 · outbound

This paper cites an unresolved cited work.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Unresolved cited work

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-02T13:52:09.958567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:52:09.958567Z digest=sha256:1b1c40e494a83e73900cc23c82af9cf8f2c1b1da90195a88226b754d24c3575e

Observation 58074d12-9f0e-49cf-808b-965419f575f0 · outbound

This paper cites configuration.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts configuration

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-02T13:52:10.042016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:52:10.042016Z digest=sha256:8473c2f4eb8e1b3e3673788e49de66b2de98fdd2d6d02b6959ad9f9750c1a095

Observation a6e528e4-7c0b-4e59-a28c-a21b6044c4bd · outbound

This paper cites Accessed: 2026-04-30.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Accessed: 2026-04-30

Reference 2026

Resolution
unresolved
no resolver link, observed 2026-08-02T13:52:07.316590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:52:07.316590Z digest=sha256:4832be4c79925835b9ca3423298391d8b9251afc1ebec4c7710c75ad9a4aae32

Pith citing papers

No inbound Pith citation observations are available.