STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings | Paper Citation Record

Observation 529aed35-87d9-4c92-828c-d8fc908f1267 · outbound

This paper cites write newline.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.147733Z

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Observation af7181b4-de3f-4baf-9ff3-6b17d75f5327 · outbound

This paper cites URL https://aclanthology.org/W01-0500.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings URL https://aclanthology.org/W01-0500

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:37.795091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4acafd28-e54a-4e87-8038-17982f3fdbee · outbound

This paper cites Llama 3 model card, 2024.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Llama 3 model card, 2024

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.161277Z

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Observation d4749487-d6a7-4bc7-94da-70714b3dc4a1 · outbound

This paper cites Claude 3 model card, 2024.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Claude 3 model card, 2024

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:37.724086Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a7c9a82c-8dd9-481b-877b-30fcd7ffb0c0 · outbound

This paper cites G., Bradley, H., O'Brien, K., Hallahan, E., Khan, M.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings G., Bradley, H., O'Brien, K., Hallahan, E., Khan, M

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:37.608331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 70d9c428-1a5e-4ac7-b2d4-189f16403302 · outbound

This paper cites The secret sharer: Evaluating and testing unintended memorization in neural networks.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings The secret sharer: Evaluating and testing unintended memorization in neural networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.180000Z

Source-reported events for the cited work

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Observation 3586f188-fc26-4f78-bf67-ae45d2d194ce · outbound

This paper cites Extracting training data from large language models.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Extracting training data from large language models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.238371Z

Source-reported events for the cited work

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Observation 4a22a493-c019-4b43-99de-f4276e220e0f · outbound

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

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.339865Z

Source-reported events for the cited work

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Observation d8941311-118d-44ea-ae3e-2f52d932d858 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Training Verifiers to Solve Math Word Problems

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.417959Z

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Observation 234445c1-9ae4-420e-a236-bfe325b61be9 · outbound

This paper cites Opencompass: A universal evaluation platform for foundation models, 2023.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Opencompass: A universal evaluation platform for foundation models, 2023

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:37.394253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c7b7bc96-8630-4b1f-b139-c6406b9b7fe5 · outbound

This paper cites Blind Baselines Beat Membership Inference Attacks for Foundation Models.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.502718Z

Source-reported events for the cited work

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Observation d5c780e0-a181-4ba6-a25f-73764cf368fd · outbound

This paper cites Do Membership Inference Attacks Work on Large Language Models?.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Do Membership Inference Attacks Work on Large Language Models?

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.510175Z

Source-reported events for the cited work

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Observation a7714fd9-533e-4bff-8947-a3ef660ec2c7 · outbound

This paper cites P., Groeneveld, D., Soldaini, L., Singh, S., Hajishirzi, H., Smith, N.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings P., Groeneveld, D., Soldaini, L., Singh, S., Hajishirzi, H., Smith, N

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:37.302862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0462733e-1a89-481f-9ca0-fb6d8999ce0c · outbound

This paper cites A framework for few-shot language model evaluation, 2024.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings A framework for few-shot language model evaluation, 2024

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.523728Z

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Observation 0e2c281f-b55c-4ba3-8d97-9adac910e137 · outbound

This paper cites and Surdeanu, M.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings and Surdeanu, M

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:37.281341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 52601c7b-4a3c-4191-a09c-cc58a7f7e7a9 · outbound

This paper cites an unresolved cited work.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-16T12:13:37.165539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d239b600-00df-4ea0-bc64-ff00f7fce980 · outbound

This paper cites an unresolved cited work.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-16T12:13:37.144594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4ce5f105-1a1f-4a52-b295-0fce1408322f · outbound

This paper cites Measuring massive multitask language understanding.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Measuring massive multitask language understanding

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.547964Z

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Observation 84b83e2c-bc6c-43f6-b10f-4427f5d36171 · outbound

This paper cites Stop uploading test data in plain text: Practical strategies for mitigating data contamination by evaluation benchmarks.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Stop uploading test data in plain text: Practical strategies for mitigating data contamination by evaluation benchmarks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.554507Z

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Observation d0c09586-1793-44ea-8854-3cabe4cd284d · outbound

This paper cites T rivia QA : A large scale distantly supervised challenge dataset for reading comprehension.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings T rivia QA : A large scale distantly supervised challenge dataset for reading comprehension

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.560559Z

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Observation b7701373-d02c-4f62-9e29-fc020740a9b4 · outbound

This paper cites A watermark for large language models.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings A watermark for large language models

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:37.033568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 34747d62-db05-4d4a-9181-7fbfb8b64d24 · outbound

This paper cites On the reliability of watermarks for large language models.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings On the reliability of watermarks for large language models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:36.941552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2f4a8c61-5616-4d69-a617-84658d9208bd · outbound

This paper cites Paraphrasing evades detectors of ai-generated text, but retrieval is an effective defense.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Paraphrasing evades detectors of ai-generated text, but retrieval is an effective defense

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:36.816149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c650cd6f-508f-4deb-b6fc-bf2b9bef4a2e · outbound

This paper cites Waterfall: Framework for Robust and Scalable Text Watermarking and Provenance for LLMs.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Waterfall: Framework for Robust and Scalable Text Watermarking and Provenance for LLMs

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.586634Z

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Observation 176f429b-2a38-404e-9624-a07d6b21a514 · outbound

This paper cites AI-AI Bias: large language models favor communications generated by large language models.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings AI-AI Bias: large language models favor communications generated by large language models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.608323Z

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Observation 4fceab2c-afca-4cb7-801f-161a3c9a8559 · outbound

This paper cites Watermarking Text Data on Large Language Models for Dataset Copyright.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Watermarking Text Data on Large Language Models for Dataset Copyright

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.671240Z

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Observation 7565ec86-8d27-4b11-b659-28bef9664e28 · outbound

This paper cites G -eval: NLG evaluation using gpt-4 with better human alignment.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings G -eval: NLG evaluation using gpt-4 with better human alignment

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.752098Z

Source-reported events for the cited work

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Observation 8488ea01-a580-414a-a63e-3c29813e3e9d · outbound

This paper cites and Hutter, F.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings and Hutter, F

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.808317Z

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Observation 98704265-7deb-4c29-839a-ad01162d869f · outbound

This paper cites and Schwartz, R.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings and Schwartz, R

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.815536Z

Source-reported events for the cited work

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Observation fc5baa80-c22f-4fee-af11-11b6255abb22 · outbound

This paper cites Dataset inference: Ownership resolution in machine learning.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Dataset inference: Ownership resolution in machine learning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:36.749328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8547793f-a23e-47f8-86bb-73825ae2a34c · outbound

This paper cites LLM dataset inference: Did you train on my dataset? In Globersons, A., Mackey, L., Belgrave, D., Fan, A., Paquet, U., Tomczak, J.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings LLM dataset inference: Did you train on my dataset? In Globersons, A., Mackey, L., Belgrave, D., Fan, A., Paquet, U., Tomczak, J

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:36.731391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 39cede20-01aa-4784-8d6e-3a59a80e6ffc · outbound

This paper cites Copyright traps for large language models.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Copyright traps for large language models

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:36.712224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 04da9fc0-94f2-472d-8d23-11224fe74b6f · outbound

This paper cites Sok: Membership inference attacks on llms are rushing nowhere (and how to fix it).

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Sok: Membership inference attacks on llms are rushing nowhere (and how to fix it)

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:36.613572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 86824c72-56b1-41bf-ba0b-021377708782 · outbound

This paper cites Characterizing Large Language Models as Rationalizers of Knowledge-intensive Tasks.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Characterizing Large Language Models as Rationalizers of Knowledge-intensive Tasks

Reference 34

Resolution: metadata mismatch; local_arxiv, observed 2026-08-16T12:13:35.796308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation eaa5a76a-6f9f-416e-8c55-194b9fc257da · outbound

This paper cites and Kapoor, S.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings and Kapoor, S

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:36.498365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 86fe8461-bd27-4f2a-8941-e39c782120bc · outbound

This paper cites The times sues openai and microsoft over a.i.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings The times sues openai and microsoft over a.i

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:36.480206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6afa6f97-7bd0-4132-92d9-8491a62610af · outbound

This paper cites GPT-4 Technical Report.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings GPT-4 Technical Report

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.867715Z

Source-reported events for the cited work

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Observation ac767f58-3649-4292-a1a5-1dfcd674fc11 · outbound

This paper cites S., Ladhak, F., and Hashimoto, T.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings S., Ladhak, F., and Hashimoto, T

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:36.460011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7d4d9f8e-2cb2-41c2-9d64-fc1a408de616 · outbound

This paper cites L., and Agirre, E.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings L., and Agirre, E

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.881355Z

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Observation 9a069add-1cdc-45b7-a320-74713c33310e · outbound

This paper cites A., García-Ferreroa, I., and andEneko Agirre, J.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings A., García-Ferreroa, I., and andEneko Agirre, J

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:36.370655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b08537a0-0eb0-4549-a310-9303db0daa2b · outbound

This paper cites Watermarking makes language models radioactive.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Watermarking makes language models radioactive

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:36.213114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bcc8cc3f-772f-4368-a0f3-ace9c6263e70 · outbound

This paper cites Detecting Benchmark Contamination Through Watermarking.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Detecting Benchmark Contamination Through Watermarking

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:34.899787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d848a211-1de1-4e5f-89d7-bf3598f7d645 · outbound

This paper cites Detecting pretraining data from large language models.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Detecting pretraining data from large language models

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:36.195644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation eab83d8c-26d3-4727-a5e6-3f9262b4d4dd · outbound

This paper cites Membership Inference Attacks against Machine Learning Models.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Membership Inference Attacks against Machine Learning Models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:35.037606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8db7120c-aeb6-457b-ac88-04650dbb2bf3 · outbound

This paper cites Evaluation data contamination in LLMs: how do we measure it and (when) does it matter?.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Evaluation data contamination in LLMs: how do we measure it and (when) does it matter?

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:35.083124Z

Source-reported events for the cited work

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Observation 5f9b6c52-7e8e-4dde-9b2d-0445d546ca6c · outbound

This paper cites The probable error of a mean.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings The probable error of a mean

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:13:36.175042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3e1acb7f-128b-4617-aa54-9361f738ae76 · outbound

This paper cites M ini C heck: Efficient fact-checking of LLM s on grounding documents.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings M ini C heck: Efficient fact-checking of LLM s on grounding documents

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:35.095203Z

Source-reported events for the cited work

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Observation 15695660-c222-4f64-9d13-d4eec6a5f728 · outbound

This paper cites Exploring document-level literary machine translation with parallel paragraphs from world literature.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Exploring document-level literary machine translation with parallel paragraphs from world literature

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:35.102809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4be5600-2687-4a8f-888d-ad14ce5de575 · outbound

This paper cites Proving membership in LLM pretraining data via data watermarks.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Proving membership in LLM pretraining data via data watermarks

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:35.109811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d6d4e0a-ece1-40c1-92e7-1e0689fcbbb2 · outbound

This paper cites Paraphrastic representations at scale.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Paraphrastic representations at scale

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:35.116142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 806e82fc-b083-4ef4-bc94-b7398825a6ac · outbound

This paper cites a good pun is its own reword : Can large language models understand puns? In Al-Onaizan, Y., Bansal, M., and Chen, Y.-N.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings a good pun is its own reword : Can large language models understand puns? In Al-Onaizan, Y., Bansal, M., and Chen, Y.-N

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:35.123069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 792acbbd-5277-43e8-b116-1fad57defb5a · outbound

This paper cites Privacy risk in machine learning: Analyzing the connection to overfitting.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Privacy risk in machine learning: Analyzing the connection to overfitting

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:35.129930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a427248-312d-4def-80d7-073979959175 · outbound

This paper cites Tree of Problems: Improving structured problem solving with compositionality.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Tree of Problems: Improving structured problem solving with compositionality

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-08-16T12:13:35.563206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 54abe99e-bc2f-4999-9a28-b1909c98e928 · outbound

This paper cites PaCoST: Paired Confidence Significance Testing for Benchmark Contamination Detection in Large Language Models.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings PaCoST: Paired Confidence Significance Testing for Benchmark Contamination Detection in Large Language Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-16T12:13:35.157856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad46f5e7-154d-427a-8d10-8a84a5600387 · outbound

This paper cites Membership Inference Attacks Cannot Prove that a Model Was Trained On Your Data.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Membership Inference Attacks Cannot Prove that a Model Was Trained On Your Data

Reference 55

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Observation 0e09ecde-3a19-45c6-9df5-1cebbd7517cc · outbound

This paper cites Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models

Reference 56

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Observation fd847f73-7102-49d5-ac6f-f371f12ea372 · outbound

This paper cites Pretraining Data Detection for Large Language Models: A Divergence-based Calibration Method.

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings Pretraining Data Detection for Large Language Models: A Divergence-based Calibration Method

Reference 57

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