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Paper Citation Record · LEDGER

ScoreShield: Differentially Private Release of Similarity Scores

As of 9 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 0 inbound Pith citation observations for arXiv:2607.25041.

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

pith.paper-citation-record.v1
2607.25041 v1

Coverage vector

measured 83 of 83 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T02:59:45.889162Z

measured 83 of 83 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

83 of 83 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved81
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8bec450b-94a5-4161-8002-cc3056a161bf · outbound

This paper cites SemDeDup: Data-efficient learning at web-scale through semantic deduplication.

ScoreShield: Differentially Private Release of Similarity Scores SemDeDup: Data-efficient learning at web-scale through semantic deduplication

Reference 1

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source=pdf_text observed=2026-07-31T02:59:45.457159Z digest=sha256:c4fc7a3e84fcb5ef91a55ce56bf38b24f76bbd3b274e7a3806ed2223083d55b0

Observation d59eb55e-8b4f-49d0-8316-31d0d9a09916 · outbound

This paper cites Is my data in your retrieval database? membership inference attacks against retrieval augmented generation.

ScoreShield: Differentially Private Release of Similarity Scores Is my data in your retrieval database? membership inference attacks against retrieval augmented generation

Reference 2

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source=pdf_text observed=2026-07-31T02:59:45.462588Z digest=sha256:bb72ed15b03df5b10876a3af8404b54cb73204969611c89a92ef43013ef20f74

Observation 29004a17-aae4-4bdf-9d4d-111679f73589 · outbound

This paper cites Cryptomask: Privacy-preserving face recognition.

ScoreShield: Differentially Private Release of Similarity Scores Cryptomask: Privacy-preserving face recognition

Reference 3

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source=pdf_text observed=2026-07-31T02:59:45.466930Z digest=sha256:137881ad78a18cb63625f03469610f6bf1c1faa21b5acb6079dfc1a50d4753e3

Observation 902e3526-b90e-4d60-b1f3-d68c6f0d8043 · outbound

This paper cites Safeguarding privacy of retrieval data against membership inference attacks: Is this query too close to home?arXiv preprint arXiv:2505.22061, 2025.

ScoreShield: Differentially Private Release of Similarity Scores Safeguarding privacy of retrieval data against membership inference attacks: Is this query too close to home?arXiv preprint arXiv:2505.22061, 2025

Reference 6

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source=pdf_text observed=2026-07-31T02:59:45.481363Z digest=sha256:d6da90c609b2a499dafc01ea202f2cfc51bc4ac871d17d04738a7415bc9d760d

Observation 7c4efbc6-8aaa-4c80-8c33-986ecbeee4d9 · outbound

This paper cites Total recall: Automatic query expansion with a generative feature model for object retrieval.

ScoreShield: Differentially Private Release of Similarity Scores Total recall: Automatic query expansion with a generative feature model for object retrieval

Reference 7

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source=pdf_text observed=2026-07-31T02:59:45.486205Z digest=sha256:e2243da98045e3120b82a16051f9922a39a20dda7aebfa5ff44f0713effc6b99

Observation dffff1d2-ddb8-400e-94d9-60341a2b40ab · outbound

This paper cites Arcface: Additive angular margin loss for deep face recognition.

ScoreShield: Differentially Private Release of Similarity Scores Arcface: Additive angular margin loss for deep face recognition

Reference 9

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source=pdf_text observed=2026-07-31T02:59:45.494875Z digest=sha256:e14c7a4b142e426babbdb494c958ecf7ee7118d397681c738b9e08d5d6367d72

Observation 73044f3b-817f-4911-b4f9-64b09f2bc439 · outbound

This paper cites The algorithmic foundations of differential privacy.Foundations and trends® in theoretical computer science, 9(3–4):211–407, 2014.

ScoreShield: Differentially Private Release of Similarity Scores The algorithmic foundations of differential privacy.Foundations and trends® in theoretical computer science, 9(3–4):211–407, 2014

Reference 10

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source=pdf_text observed=2026-07-31T02:59:45.498904Z digest=sha256:b5e51b3ad5792bc2ee15d4bcff9392be32867c950da0c71e67fa3edebc9f0f02

Observation d7357af5-e5a8-4950-999c-a1a2e00bbf90 · outbound

This paper cites On the vulnerability of face verification systems to hill-climbing attacks.Pattern Recognition, 43(3):1027–1038, 2010.

ScoreShield: Differentially Private Release of Similarity Scores On the vulnerability of face verification systems to hill-climbing attacks.Pattern Recognition, 43(3):1027–1038, 2010

Reference 11

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source=pdf_text observed=2026-07-31T02:59:45.503625Z digest=sha256:2e2951c10e33fbba0c1e0657a518ae092adc75160db5021b5a13ee982f34f469

Observation 6a8ed8a8-1ee0-4532-8b35-f691f08ed35d · outbound

This paper cites Billion-scale similarity search with gpus.IEEE Transactions on Big Data, 7(3):535–547, 2019.

ScoreShield: Differentially Private Release of Similarity Scores Billion-scale similarity search with gpus.IEEE Transactions on Big Data, 7(3):535–547, 2019

Reference 15

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source=pdf_text observed=2026-07-31T02:59:45.521812Z digest=sha256:76602380af4993d666217688e6f96e95e6f7f0fe19149c71e0e8da051b5f2375

Observation a6e84e59-7117-41ae-a2ef-20c1177e39ed · outbound

This paper cites Privacy via the johnson- lindenstrauss transform.Journal of Privacy and Confidentiality, 5(1):39–71, 2013.

ScoreShield: Differentially Private Release of Similarity Scores Privacy via the johnson- lindenstrauss transform.Journal of Privacy and Confidentiality, 5(1):39–71, 2013

Reference 16

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source=pdf_text observed=2026-07-31T02:59:45.526052Z digest=sha256:920cec0d78a948558d723feb953a9c01f7a792b52ed6f4b9feb5ed02957dd548

Observation d3130310-a0be-490a-b66c-fd0748305066 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.Advances in neural information processing systems, 33:9459–9474, 2020.

ScoreShield: Differentially Private Release of Similarity Scores Retrieval-augmented generation for knowledge-intensive nlp tasks.Advances in neural information processing systems, 33:9459–9474, 2020

Reference 18

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source=pdf_text observed=2026-07-31T02:59:45.534278Z digest=sha256:5fb1f58752c87ce363998bd0d165152155bd53de61b3b179d6f6f59e246ee0b9

Observation 2ea8f782-a34b-4786-8396-b36b08c2d940 · outbound

This paper cites Budgetleak: Membership inference attacks on rag systems via the generation budget side channel.arXiv preprint arXiv:2511.12043, 2025.

ScoreShield: Differentially Private Release of Similarity Scores Budgetleak: Membership inference attacks on rag systems via the generation budget side channel.arXiv preprint arXiv:2511.12043, 2025

Reference 19

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source=pdf_text observed=2026-07-31T02:59:45.538658Z digest=sha256:99a453b7fe13b550e90ee95e75b68af4a4e53ca54037aeac5e1e8a737a5d126b

Observation dc583842-abfc-445d-9a57-d2d64609efa6 · outbound

This paper cites Generating is believing: Membership inference attacks against retrieval-augmented generation.

ScoreShield: Differentially Private Release of Similarity Scores Generating is believing: Membership inference attacks against retrieval-augmented generation

Reference 20

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source=pdf_text observed=2026-07-31T02:59:45.543281Z digest=sha256:3e07c06c022897e2867d586dea1095104377fcca8bb38ff4593ce8a1ab10bacd

Observation 1f7eed09-54d0-40ed-b056-b0cca59d2fbf · outbound

This paper cites Hill-climbing attacks on multibiometrics recognition systems.IEEE Transactions on Information Forensics and Security, 10(5):900–915, 2014.

ScoreShield: Differentially Private Release of Similarity Scores Hill-climbing attacks on multibiometrics recognition systems.IEEE Transactions on Information Forensics and Security, 10(5):900–915, 2014

Reference 22

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source=pdf_text observed=2026-07-31T02:59:45.552399Z digest=sha256:a4f98573f976eeb0d0e5d28a2ccabf41a4b793af789f633203f75bd9b893f4d4

Observation 6283ed56-cb63-40ff-8e57-6f2f0ec9717b · outbound

This paper cites A survey on bias and fairness in machine learning.ACM computing surveys (CSUR), 54(6):1–35, 2021.

ScoreShield: Differentially Private Release of Similarity Scores A survey on bias and fairness in machine learning.ACM computing surveys (CSUR), 54(6):1–35, 2021

Reference 25

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source=pdf_text observed=2026-07-31T02:59:45.565591Z digest=sha256:784bcd99cda2eaf107523cc9c08f1e84c726889d4df5e66aa5e1154b3b7ccb52

Observation 965f20bc-3385-4ca0-be79-3a2105cdc712 · outbound

This paper cites Magface: A universal representation for face recognition and quality assessment.

ScoreShield: Differentially Private Release of Similarity Scores Magface: A universal representation for face recognition and quality assessment

Reference 26

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source=pdf_text observed=2026-07-31T02:59:45.569729Z digest=sha256:72545089c2d7030704607d90cd0ddac7a08c3d58de2807c9b793fbf286ff9802

Observation 953c6e7a-0373-4434-8a5b-fbb5efa3215e · outbound

This paper cites MTEB: Massive text embedding benchmark.

ScoreShield: Differentially Private Release of Similarity Scores MTEB: Massive text embedding benchmark

Reference 28

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source=pdf_text observed=2026-07-31T02:59:45.578695Z digest=sha256:96d192993d1550dffc0671827c6035a0cb6b798a912c9b8429f0b17ff072794b

Observation 32154b05-d9ad-492f-b61b-a0e801c4f57e · outbound

This paper cites Riddle me this! stealthy membership inference for retrieval-augmented generation.

ScoreShield: Differentially Private Release of Similarity Scores Riddle me this! stealthy membership inference for retrieval-augmented generation

Reference 29

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source=pdf_text observed=2026-07-31T02:59:45.583449Z digest=sha256:e71847798ca09ee74ab99da5e130c94d0f3722367a7be3ea8c06b497db699eff

Observation f02746dd-9d3c-48a5-99d7-28c795fa9802 · outbound

This paper cites On spectral clustering: Analysis and an algorithm.Advances in neural information processing systems, 14, 2001.

ScoreShield: Differentially Private Release of Similarity Scores On spectral clustering: Analysis and an algorithm.Advances in neural information processing systems, 14, 2001

Reference 30

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source=pdf_text observed=2026-07-31T02:59:45.588223Z digest=sha256:37364fe8c2eef292bce5a7632c670f464e704e8c31e83f51407e0870a66fb5fb

Observation e4f9a2bc-7703-4f0d-855f-a3c066dcd8ff · outbound

This paper cites Deepface-emd: Re-ranking using patch-wise earth mover’s distance improves out-of- distribution face identification.

ScoreShield: Differentially Private Release of Similarity Scores Deepface-emd: Re-ranking using patch-wise earth mover’s distance improves out-of- distribution face identification

Reference 31

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source=pdf_text observed=2026-07-31T02:59:45.592533Z digest=sha256:acbee3a9185d266a6b0fd477ebcf7248af03449b95966a4648193eea57057248

Observation 19c09d29-de00-42d6-9aa0-b4216fc417db · outbound

This paper cites Sentence-bert: Sentence embeddings using siamese BERT-networks.

ScoreShield: Differentially Private Release of Similarity Scores Sentence-bert: Sentence embeddings using siamese BERT-networks

Reference 32

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source=pdf_text observed=2026-07-31T02:59:45.596829Z digest=sha256:8ce0ff44b14e0c54d8d50d4a79861837e94f00bb21d7e22b8bc24d7681133397

Observation 1e390028-4103-4a29-b14e-bac38a62c5d5 · outbound

This paper cites Normalized cuts and image segmentation.IEEE Transactions on pattern analysis and machine intelligence, 22(8):888–905, 2000.

ScoreShield: Differentially Private Release of Similarity Scores Normalized cuts and image segmentation.IEEE Transactions on pattern analysis and machine intelligence, 22(8):888–905, 2000

Reference 33

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source=pdf_text observed=2026-07-31T02:59:45.600961Z digest=sha256:dd42c72a10fe5af305d7575ff2d4d004fad51e63147a8f2792805ccd0fe5f406

Observation 210d86cb-b27f-4f82-9689-ddff0d45cd17 · outbound

This paper cites FairDeDup: Detecting and mitigating vision-language fairness disparities in semantic dataset deduplication.

ScoreShield: Differentially Private Release of Similarity Scores FairDeDup: Detecting and mitigating vision-language fairness disparities in semantic dataset deduplication

Reference 34

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source=pdf_text observed=2026-07-31T02:59:45.605446Z digest=sha256:be385b1a94d3db60f54ed672be0e9e348816df931417f4fc6d8a03555d930424

Observation 7b873386-6eb7-480e-a7fc-af6708179f10 · outbound

This paper cites Iarpa janus benchmark-b face dataset.

ScoreShield: Differentially Private Release of Similarity Scores Iarpa janus benchmark-b face dataset

Reference 35

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source=pdf_text observed=2026-07-31T02:59:45.609625Z digest=sha256:f6c18e42570ba02ba9ddc007ee8c694d0b6ce7ac6bf48efc277874df294f6339

Observation f6e1b0a7-7cf0-4a32-86ee-83dfe8840932 · outbound

This paper cites Face clustering via graph convolutional networks with confidence edges.

ScoreShield: Differentially Private Release of Similarity Scores Face clustering via graph convolutional networks with confidence edges

Reference 38

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source=pdf_text observed=2026-07-31T02:59:45.622672Z digest=sha256:3655f2c7cb0e24f26abd34a8d257563f807265149c402985138d282d77bea715

Observation 88a102fe-cf88-4a72-8bd5-fee93725f472 · outbound

This paper cites an old dog performs new tricks.

ScoreShield: Differentially Private Release of Similarity Scores an old dog performs new tricks

Reference 40

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source=pdf_text observed=2026-07-31T02:59:45.631234Z digest=sha256:2acf0b2eac53a0aee81daddab2fb9baaa30b2f177cfa69aa132d7383c1aa5751

Observation 257bdf35-bb37-4ddb-a8a9-8a3b5d35b9ed · outbound

This paper cites an unresolved cited work.

ScoreShield: Differentially Private Release of Similarity Scores Unresolved cited work

Reference 41

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source=pdf_text observed=2026-07-31T02:59:45.636428Z digest=sha256:722357f40372523fdb675ea089ebb901ad0fe4158f6d25ae1bb461233a9266bd

Observation 1a268aa1-3a81-4377-b338-b01ff93651d7 · outbound

This paper cites the corpus.

ScoreShield: Differentially Private Release of Similarity Scores the corpus

Reference 42

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source=pdf_text observed=2026-07-31T02:59:45.640830Z digest=sha256:0fd8e7bbb32bdea00d0bddb688cd7f07e3061a0177aed713bdbc01c5e67a3c5c

Observation dc3b2d03-e62a-4503-bd37-8e355ece51c2 · outbound

This paper cites Beyond per-question privacy.

ScoreShield: Differentially Private Release of Similarity Scores Beyond per-question privacy

Reference 43

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source=pdf_text observed=2026-07-31T02:59:45.645377Z digest=sha256:5255e1e3a7e72be8da6cebdb23ccb078ba57fcfd6ec7b592e316902cb28e6242

Observation e801e5fb-4aa4-494e-9f53-5a20382993b6 · outbound

This paper cites no match.

ScoreShield: Differentially Private Release of Similarity Scores no match

Reference 44

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source=pdf_text observed=2026-07-31T02:59:45.650175Z digest=sha256:6ef9cd59bf3594d1136d9df6ad93b2e96238e6a9eccebe172bff209bc2cf05ac

Observation eb3ef824-cc81-47bd-a70c-6ee2e5b865ac · outbound

This paper cites Thus fori̸=j,|S ij|=|⟨e i,ej⟩|≤∥e i∥2∥ej∥2 = 1.

ScoreShield: Differentially Private Release of Similarity Scores Thus fori̸=j,|S ij|=|⟨e i,ej⟩|≤∥e i∥2∥ej∥2 = 1

Reference 45

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source=pdf_text observed=2026-07-31T02:59:45.654856Z digest=sha256:45913b36afe6002e6c980c48ab8e7080e79b829906b1e72e9f4401ba1c3f168d

Observation 4b803b32-5ad5-4709-b178-f51e85ba6a77 · outbound

This paper cites >” (Remark G.13). BecauseW has a continuous density,Pr[S +W =τ] = 0for every τ <1, so the strict “>.

ScoreShield: Differentially Private Release of Similarity Scores >” (Remark G.13). BecauseW has a continuous density,Pr[S +W =τ] = 0for every τ <1, so the strict “>

Reference 46

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source=pdf_text observed=2026-07-31T02:59:45.661552Z digest=sha256:a3de335ef9a73d4222ec48760eb32c74ee91902a1ec797fa0dc476172ee8cfc5

Observation 85babf72-f5fd-4492-8a78-c127adb5e986 · outbound

This paper cites 2.Transition regime(35≤ε<70): utility improves rapidly with either increasingεor relaxingδ.

ScoreShield: Differentially Private Release of Similarity Scores 2.Transition regime(35≤ε<70): utility improves rapidly with either increasingεor relaxingδ

Reference 47

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source=pdf_text observed=2026-07-31T02:59:45.667697Z digest=sha256:306bf7f0a4aac839b96bf5b101c5e3e2c945d8cbeabf59cb4a430736e270bf63

Observation 3a0e07be-75dd-4e81-a452-f1002c4ad8e3 · outbound

This paper cites Retrieval-document.

ScoreShield: Differentially Private Release of Similarity Scores Retrieval-document

Reference 48

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source=pdf_text observed=2026-07-31T02:59:45.672063Z digest=sha256:9a9074abc7b4bf9f833f79b55f9a28941a7e07d67468a33f8e8aeee542666d17

Observation 87143eb5-454e-44c1-8d6f-fb98a699aa17 · outbound

This paper cites This serves as the non-private reference.

ScoreShield: Differentially Private Release of Similarity Scores This serves as the non-private reference

Reference 49

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source=pdf_text observed=2026-07-31T02:59:45.678148Z digest=sha256:504aa06ae82be3a4682378d53d4a826c6512d1fdc5a7294e92fe9bd76771630c

Observation 01c7e79c-a959-4c99-b0d5-3b5cd7649425 · outbound

This paper cites The resulting matrix need not be positive semidefinite, need not have unit diagonal, and may have entries outside[−1,1].

ScoreShield: Differentially Private Release of Similarity Scores The resulting matrix need not be positive semidefinite, need not have unit diagonal, and may have entries outside[−1,1]

Reference 50

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source=pdf_text observed=2026-07-31T02:59:45.684080Z digest=sha256:91625f10f564ed37e78606acbf9a0387ee3b90f5b410ec57756687e84d2b03ed

Observation 5ad32a9e-4685-43e7-accd-38abc2e1e705 · outbound

This paper cites In the large-scale experiments, this step is implemented by AAP over the PSD cone, the unit-diagonal affine set, and the entrywise box[−1,1].

ScoreShield: Differentially Private Release of Similarity Scores In the large-scale experiments, this step is implemented by AAP over the PSD cone, the unit-diagonal affine set, and the entrywise box[−1,1]

Reference 51

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source=pdf_text observed=2026-07-31T02:59:45.688939Z digest=sha256:efaa5fef2643743b43fc75a680f02c7fc41ecdce768cac1d0dbaa4a836a18ab5

Observation 0844cd50-f235-494e-ad96-74b36f59269e · outbound

This paper cites Springer, 2007.

ScoreShield: Differentially Private Release of Similarity Scores Springer, 2007

Reference 52

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source=pdf_text observed=2026-07-31T02:59:45.693996Z digest=sha256:d1573dd0592a5161cff0919712c889ac9436ab166420cb63ec56cd1e92808a86

Observation bf54c044-b81e-40ce-a4bf-7d412cc2ddd0 · outbound

This paper cites On Opial's Lemma.

ScoreShield: Differentially Private Release of Similarity Scores On Opial's Lemma

Reference 53

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source=pdf_text observed=2026-07-31T02:59:45.698170Z digest=sha256:45eee3f3140eac132cff76822d253064319df6be87684b5c749e855a621d0af5

Observation 58955e82-d3db-4efc-85cd-83e785d273ad · outbound

This paper cites Improving the gaussian mechanism for differential privacy: Analytical calibration and optimal denoising.

ScoreShield: Differentially Private Release of Similarity Scores Improving the gaussian mechanism for differential privacy: Analytical calibration and optimal denoising

Reference 54

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source=pdf_text observed=2026-07-31T02:59:45.702918Z digest=sha256:3808c5baa77dc4541cea8b91b2ff69dd080fc70fd31393620f8953b5d2906746

Observation 7cc45a9a-9527-4160-b5cf-63729f5b565b · outbound

This paper cites The area above the ordinal dominance graph and the area below the receiver operating characteristic graph.Journal of mathematical psychology, 12(4):387–415, 1975.

ScoreShield: Differentially Private Release of Similarity Scores The area above the ordinal dominance graph and the area below the receiver operating characteristic graph.Journal of mathematical psychology, 12(4):387–415, 1975

Reference 55

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source=pdf_text observed=2026-07-31T02:59:45.707055Z digest=sha256:9d2dd28b6154953e5c6ca66a2d1ae14144a9eff87594015103d7bf1a5937c263

Observation 940e08c0-f238-4bf6-80fd-e712f24fd18e · outbound

This paper cites Dykstra’ s alternating projection algorithm for two sets.Journal of Approximation Theory, 79(3):418–443, 1994.

ScoreShield: Differentially Private Release of Similarity Scores Dykstra’ s alternating projection algorithm for two sets.Journal of Approximation Theory, 79(3):418–443, 1994

Reference 56

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source=pdf_text observed=2026-07-31T02:59:45.711487Z digest=sha256:c699ab79493b43f2fe5a906c77c03e263d48141b269ecf0da89a3e27a54598e8

Observation a145a38c-fb55-4b78-a70c-985143d9e6a5 · outbound

This paper cites On projection algorithms for solving convex feasibility problems.

ScoreShield: Differentially Private Release of Similarity Scores On projection algorithms for solving convex feasibility problems

Reference 57

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source=pdf_text observed=2026-07-31T02:59:45.715784Z digest=sha256:6016a10dec5815e4a7da1814a2e2f08893d2740765be3580e0f2ebfbf7a935f8

Observation 8631100d-794e-4485-ad57-8556cbd7124e · outbound

This paper cites Correction to: convex analysis and monotone operator theory in hilbert spaces.

ScoreShield: Differentially Private Release of Similarity Scores Correction to: convex analysis and monotone operator theory in hilbert spaces

Reference 58

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source=pdf_text observed=2026-07-31T02:59:45.720122Z digest=sha256:e36d69c46660c7b0760b703a8afb1f5426868df4442254c6c952bc1898f14ab9

Observation ad6c0f01-36ea-45d4-bb54-8d7284582072 · outbound

This paper cites Strong conical hull intersection property, bounded linear regularity, jameson’s property (g), and error bounds in convex optimization.Mathematical Programming, 86(1): 135–160, 1999.

ScoreShield: Differentially Private Release of Similarity Scores Strong conical hull intersection property, bounded linear regularity, jameson’s property (g), and error bounds in convex optimization.Mathematical Programming, 86(1): 135–160, 1999

Reference 59

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source=pdf_text observed=2026-07-31T02:59:45.724395Z digest=sha256:331a89514afd3e792ad2b6cf46a090c2c510be06622596aa0b4455eed85f8b6c

Observation cebc1e40-e474-4b7d-a36d-517ec18c04f5 · outbound

This paper cites The johnson-lindenstrauss transform itself preserves differential privacy.

ScoreShield: Differentially Private Release of Similarity Scores The johnson-lindenstrauss transform itself preserves differential privacy

Reference 60

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source=pdf_text observed=2026-07-31T02:59:45.728869Z digest=sha256:b3d7f846eb050fefe5baec38437f62eeefefd232cb009f35601d316cf277096d

Observation bff9f746-8e1e-4cbd-a1a4-1434a7ab8ed7 · outbound

This paper cites A method for finding projections onto the intersection of convex sets in hilbert spaces.

ScoreShield: Differentially Private Release of Similarity Scores A method for finding projections onto the intersection of convex sets in hilbert spaces

Reference 61

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source=pdf_text observed=2026-07-31T02:59:45.733163Z digest=sha256:6b1186d57efd266dbfee111c8239e2a801a25f133b4b5aee81b1d8f69f0e33aa

Observation d6c2fbee-b02e-463c-a943-41ed98b44c80 · outbound

This paper cites SemEval-2017 task 1: Semantic textual similarity multilingual and cross-lingual focused evaluation.

ScoreShield: Differentially Private Release of Similarity Scores SemEval-2017 task 1: Semantic textual similarity multilingual and cross-lingual focused evaluation

Reference 62

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source=pdf_text observed=2026-07-31T02:59:45.737472Z digest=sha256:42d6ef42187d10ab5362dc988ba3a105156d0adfa0a06327a11ea2c5666c2d31

Observation c40c5dbf-2c34-49dc-90df-c6dc2cc7c4a4 · outbound

This paper cites Privacy preserving face recognition utilizing differential privacy.Computers & Security, 97, 2020.

ScoreShield: Differentially Private Release of Similarity Scores Privacy preserving face recognition utilizing differential privacy.Computers & Security, 97, 2020

Reference 63

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source=pdf_text observed=2026-07-31T02:59:45.741609Z digest=sha256:4203bcefc15a5bce0114a0a16f464c834903ecb6b27e518bfde2602589071416

Observation d2b77839-1cf9-4e35-8c20-a8fa17de3ee9 · outbound

This paper cites Talagrand meets talagrand: Upper and lower bounds on expected soft maxima of gaussian processes with finite index sets.arXiv preprint arXiv:2502.06709, 2025.

ScoreShield: Differentially Private Release of Similarity Scores Talagrand meets talagrand: Upper and lower bounds on expected soft maxima of gaussian processes with finite index sets.arXiv preprint arXiv:2502.06709, 2025

Reference 64

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source=pdf_text observed=2026-07-31T02:59:45.745878Z digest=sha256:0fdf542605ebd5600a02118666c560fea531a5bbe5e06912e1a494cd31eab53d

Observation 91302f14-2a30-4f07-ba9e-763c59c1edcd · outbound

This paper cites Perturb-and- project: differentially private similarities and marginals.

ScoreShield: Differentially Private Release of Similarity Scores Perturb-and- project: differentially private similarities and marginals

Reference 65

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source=pdf_text observed=2026-07-31T02:59:45.749852Z digest=sha256:c9c1868dd5d97cdce46007787433f6dc6fc127e086db586badfabeb3d41f3ed6

Observation e9960521-bf6d-4e31-a466-a6c2c3ff29a7 · outbound

This paper cites Partial auc estimation and regression.Biometrics, 59(3):614–623, 2003.

ScoreShield: Differentially Private Release of Similarity Scores Partial auc estimation and regression.Biometrics, 59(3):614–623, 2003

Reference 66

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source=pdf_text observed=2026-07-31T02:59:45.753766Z digest=sha256:b7fc1839a9bc0c74471dbaa8d58418b933e72a82b7dc95bd2bd7401cba0a5d70

Observation d4730797-0422-4a64-9278-b2e5152344d9 · outbound

This paper cites Differentially private covariance revisited.Advances in Neural Information Processing Systems, 35:850–861, 2022.

ScoreShield: Differentially Private Release of Similarity Scores Differentially private covariance revisited.Advances in Neural Information Processing Systems, 35:850–861, 2022

Reference 67

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source=pdf_text observed=2026-07-31T02:59:45.758102Z digest=sha256:870a234eecd30ecda43d77dff250f3a3fba94c8783db830b736ad8e538d136b0

Observation 202b006d-9bd0-4284-bf5f-f4dce0342b7c · outbound

This paper cites An algorithm for restricted least squares regression.Journal of the American Statistical Association, 78(384):837–842, 1983.

ScoreShield: Differentially Private Release of Similarity Scores An algorithm for restricted least squares regression.Journal of the American Statistical Association, 78(384):837–842, 1983

Reference 68

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source=pdf_text observed=2026-07-31T02:59:45.762710Z digest=sha256:9f058a2b521b79c66757faa9e081c9a2e10474ad7f4c870de500c5a5ae00fb3c

Observation 28dcd72c-ddea-45dd-b59e-005590c0ea8c · outbound

This paper cites An iterative procedure for obtaining i-projections onto the intersection of convex sets.The annals of Probability, pp.

ScoreShield: Differentially Private Release of Similarity Scores An iterative procedure for obtaining i-projections onto the intersection of convex sets.The annals of Probability, pp

Reference 69

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source=pdf_text observed=2026-07-31T02:59:45.767123Z digest=sha256:b37d505dd399a3ba441ac3dd2b5dee3e2f1bbba53164273a60887cc9b10f79f8

Observation 402061ab-07e8-440c-9d5e-246d9cd3257f · outbound

This paper cites Gemma 3 Technical Report.

ScoreShield: Differentially Private Release of Similarity Scores Gemma 3 Technical Report

Reference 70

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source=pdf_text observed=2026-07-31T02:59:45.771542Z digest=sha256:d31d65c6812ffcece99cca309ed32c607bd9065ea1881352f24cdc61a8e3112e

Observation 4d637cec-a234-4025-88ee-7d3403305569 · outbound

This paper cites Rag with differential privacy.

ScoreShield: Differentially Private Release of Similarity Scores Rag with differential privacy

Reference 71

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source=pdf_text observed=2026-07-31T02:59:45.776558Z digest=sha256:0b2f4a48298aaa35a58f23c9c2485d4caad7a9a43f5b9eb1ca2757d01958e409

Observation 5d24cb6b-bf1b-4002-8404-a64aedee5581 · outbound

This paper cites The movielens datasets: History and context.ACM transactions on interactive intelligent systems (TIIS), 5(4):1–19, 2015.

ScoreShield: Differentially Private Release of Similarity Scores The movielens datasets: History and context.ACM transactions on interactive intelligent systems (TIIS), 5(4):1–19, 2015

Reference 72

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source=pdf_text observed=2026-07-31T02:59:45.781027Z digest=sha256:31867b03f1f3f77ffb502f1c21fc1d6dfbba80754c7b2c3b89972d9b3444415c

Observation 9a7d8de3-3367-40b7-92af-36a08204a014 · outbound

This paper cites Privacy-preserving face recognition with learnable privacy budgets in frequency domain.

ScoreShield: Differentially Private Release of Similarity Scores Privacy-preserving face recognition with learnable privacy budgets in frequency domain

Reference 73

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source=pdf_text observed=2026-07-31T02:59:45.786056Z digest=sha256:ae505d755d0710b9400935d21411fae2088c981cbaf5e341be48eeaecd45fb1e

Observation d6fabe84-0cd7-46f6-99d1-26f20cc09257 · outbound

This paper cites Less is more: Revisiting the gaussian mechanism for differential privacy.

ScoreShield: Differentially Private Release of Similarity Scores Less is more: Revisiting the gaussian mechanism for differential privacy

Reference 74

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source=pdf_text observed=2026-07-31T02:59:45.790248Z digest=sha256:e87744ca1bc973aa7665b824d84a246c9c93ed9ccaaf00dc1dc3c984a7084855

Observation 5cf5b2be-5810-4212-a5de-cefe63275ae9 · outbound

This paper cites Privacy-preserving retrieval-augmented generation with differential privacy.arXiv preprint arXiv:2412.04697, 2024.

ScoreShield: Differentially Private Release of Similarity Scores Privacy-preserving retrieval-augmented generation with differential privacy.arXiv preprint arXiv:2412.04697, 2024

Reference 75

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source=pdf_text observed=2026-07-31T02:59:45.794080Z digest=sha256:7d7a0674dff6ce5beb56da8f7ba9531aa8b237f49f4372f04fd5edb82a237b12

Observation 02c6fa10-34b4-4d36-917a-adcc9a099fc1 · outbound

This paper cites Fact, fetch, and reason: A unified evaluation of retrieval-augmented generation.

ScoreShield: Differentially Private Release of Similarity Scores Fact, fetch, and reason: A unified evaluation of retrieval-augmented generation

Reference 76

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source=pdf_text observed=2026-07-31T02:59:45.798317Z digest=sha256:cee3eef185736b66b8f812ec596bbed71de82cc171d0785fbe3c14e656692360

Observation 2fbd5b9c-37ca-4c3d-b151-086799081755 · outbound

This paper cites Learning multiple layers of features from tiny images.

ScoreShield: Differentially Private Release of Similarity Scores Learning multiple layers of features from tiny images

Reference 77

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source=pdf_text observed=2026-07-31T02:59:45.802493Z digest=sha256:3cf5d632e0f73d53ba3787644ab72e42c69b2cb821d1f49faf301e5a6b1c6534

Observation 85f6a256-ac4d-422f-b82f-68dd228d5c46 · outbound

This paper cites Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking.

ScoreShield: Differentially Private Release of Similarity Scores Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking

Reference 78

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source=pdf_text observed=2026-07-31T02:59:45.807022Z digest=sha256:4628668dde61a8014c6c46524019d19a6eda393c56306b49060e85f82b2d6a9d

Observation cb1b0788-4eb0-4b63-bd6a-3672238e5af9 · outbound

This paper cites Two comments on the method of successive approximations.Usp.

ScoreShield: Differentially Private Release of Similarity Scores Two comments on the method of successive approximations.Usp

Reference 79

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source=pdf_text observed=2026-07-31T02:59:45.811693Z digest=sha256:6c550df0bb014f5b76849e0a0b098894a2e74781e7560ae4cd2fd177968c4d53

Observation 4bc686cd-2bb9-410d-bca3-0ab2498e5f1e · outbound

This paper cites Mean value methods in iteration.Proceedings of the American Mathematical Society, 4(3): 506–510, 1953.

ScoreShield: Differentially Private Release of Similarity Scores Mean value methods in iteration.Proceedings of the American Mathematical Society, 4(3): 506–510, 1953

Reference 80

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source=pdf_text observed=2026-07-31T02:59:45.815989Z digest=sha256:5b541362009a0feeb37bc4ef98183415142e81e19e2892510991d51795d6eaa1

Observation 655b84bc-498b-41df-84ee-ab8098460849 · outbound

This paper cites Iarpa janus benchmark-c: Face dataset and protocol.

ScoreShield: Differentially Private Release of Similarity Scores Iarpa janus benchmark-c: Face dataset and protocol

Reference 81

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source=pdf_text observed=2026-07-31T02:59:45.819829Z digest=sha256:ff4a899b085d37e9fa93ca4f79fab96bb16f262c9aa6fc89b63b1999690f36ba

Observation c4e0a55e-6b04-4ecf-ac9e-393bb9163336 · outbound

This paper cites Décomposition orthogonale d’un espace hilbertien selon deux cônes mutuellement polaires.

ScoreShield: Differentially Private Release of Similarity Scores Décomposition orthogonale d’un espace hilbertien selon deux cônes mutuellement polaires

Reference 82

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source=pdf_text observed=2026-07-31T02:59:45.823784Z digest=sha256:d56ec5b5a43aeea5592e00b6c6e93d80c7c7a91a2c499f647b960f08db6fb7f7

Observation 6768fbb1-b615-48e1-bbd4-4a3730c114f3 · outbound

This paper cites Differentially Private Synthetic Text Generation for Retrieval-Augmented Generation (RAG).

ScoreShield: Differentially Private Release of Similarity Scores Differentially Private Synthetic Text Generation for Retrieval-Augmented Generation (RAG)

Reference 83

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source=pdf_text observed=2026-07-31T02:59:45.828032Z digest=sha256:b48ab2733ec337cba9b9cc4265cd64c614f5d275dfef785b6a0ae8263d37322c

Observation e9b9c288-eef1-4938-9c56-d91265993211 · outbound

This paper cites Roc and auc with a binary predictor: a potentially misleading metric.Journal of classification, 37(3):696–708, 2020.

ScoreShield: Differentially Private Release of Similarity Scores Roc and auc with a binary predictor: a potentially misleading metric.Journal of classification, 37(3):696–708, 2020

Reference 84

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source=pdf_text observed=2026-07-31T02:59:45.832739Z digest=sha256:3790bfba9c31762158117be3947e20f2992cd40778af554bd6cb744c8496dd49

Observation 37eb5082-7611-4d18-8f0f-333618451c15 · outbound

This paper cites Weak convergence of the sequence of successive approximations for nonexpansive mappings.

ScoreShield: Differentially Private Release of Similarity Scores Weak convergence of the sequence of successive approximations for nonexpansive mappings

Reference 85

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source=pdf_text observed=2026-07-31T02:59:45.836905Z digest=sha256:744132d2c4a46607693a731a160e34c1550d24351f7ea98346dfcc86aa949cdb

Observation a80e3485-c0d2-4da2-8472-071944571d2e · outbound

This paper cites an unresolved cited work.

ScoreShield: Differentially Private Release of Similarity Scores Unresolved cited work

Reference 86

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source=pdf_text observed=2026-07-31T02:59:45.841273Z digest=sha256:14108c0b71f364ee66e1c072b63a6f948f8c41c6fd6faa7669bcc5d9a6255e47

Observation e4d0c92b-415b-4c24-bdd7-5b2039029b5a · outbound

This paper cites Cats and dogs.

ScoreShield: Differentially Private Release of Similarity Scores Cats and dogs

Reference 87

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source=pdf_text observed=2026-07-31T02:59:45.845655Z digest=sha256:e0b81e21c66c94d112b313a25d979319f907c99d89728fa8d3a3044fdbdfe40d

Observation 0bd346fd-05d5-4527-9aac-87522cbec8b1 · outbound

This paper cites Principles of mathematical analysis.3rd ed., 1976.

ScoreShield: Differentially Private Release of Similarity Scores Principles of mathematical analysis.3rd ed., 1976

Reference 88

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Source-reported events for the cited work

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source=pdf_text observed=2026-07-31T02:59:45.850003Z digest=sha256:75ac0bfc13c7044ef12b8408d4878750f7e9506adb0d0853bc4b0047ea0d17da

Observation ddbc94b6-85b1-45e9-977e-1cafa42669f8 · outbound

This paper cites Sudakov-type minoration for gaussian chaos processes.Israel Journal of Mathematics, 79(2): 207–224, 1992.

ScoreShield: Differentially Private Release of Similarity Scores Sudakov-type minoration for gaussian chaos processes.Israel Journal of Mathematics, 79(2): 207–224, 1992

Reference 89

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no resolver link, observed 2026-07-31T02:59:45.854214Z

Source-reported events for the cited work

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source=pdf_text observed=2026-07-31T02:59:45.854214Z digest=sha256:797f8aa7334c037d6bbb7e80d89a187c663f0338c7826e29598764247dbf28c7

Observation a950dca8-a653-4551-958a-af8a6ec8922c · outbound

This paper cites Nearly optimal private lasso.Advances in Neural Information Processing Systems, 28, 2015.

ScoreShield: Differentially Private Release of Similarity Scores Nearly optimal private lasso.Advances in Neural Information Processing Systems, 28, 2015

Reference 90

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no resolver link, observed 2026-07-31T02:59:45.858501Z

Source-reported events for the cited work

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source=pdf_text observed=2026-07-31T02:59:45.858501Z digest=sha256:75c2f71ad2dc2a6b08327343d8ce2abe209929d42e09f5ddee1dbb534f79f1ec

Observation 51f08243-4939-4ea1-a4ec-c3fa51424ad1 · outbound

This paper cites EmbeddingGemma: Powerful and Lightweight Text Representations.

ScoreShield: Differentially Private Release of Similarity Scores EmbeddingGemma: Powerful and Lightweight Text Representations

Reference 91

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no resolver link, observed 2026-07-31T02:59:45.862555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T02:59:45.862555Z digest=sha256:2cfc5b733044cee4f809fe08c8a772e19d6e20959c9ef597591011bac829ae7d

Observation d92f8645-cadf-4685-a22c-e20d4d1f58cb · outbound

This paper cites On rings of operators.

ScoreShield: Differentially Private Release of Similarity Scores On rings of operators

Reference 92

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no resolver link, observed 2026-07-31T02:59:45.867623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T02:59:45.867623Z digest=sha256:d89407dad10664466607723310eb6f578561f0d5e3bf7dad015f1a259660dee4

Observation d3d4b4cd-f4b2-409c-b84f-0bf8e0d2fc6c · outbound

This paper cites Beyond per-question privacy: Multi-query differential privacy for rag systems.

ScoreShield: Differentially Private Release of Similarity Scores Beyond per-question privacy: Multi-query differential privacy for rag systems

Reference 93

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unresolved
no resolver link, observed 2026-07-31T02:59:45.872015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T02:59:45.872015Z digest=sha256:9d386c29dc17d793e835c5730adae92fd67be10fb0cbf6864df457fb45f8ab45

Observation ea5ff65f-9b70-4646-bebb-f39d11a49cc7 · outbound

This paper cites Private-rag: Answering multiple queries with llms while keeping your data private.arXiv preprint arXiv:2511.07637, 2025.

ScoreShield: Differentially Private Release of Similarity Scores Private-rag: Answering multiple queries with llms while keeping your data private.arXiv preprint arXiv:2511.07637, 2025

Reference 94

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no resolver link, observed 2026-07-31T02:59:45.876053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T02:59:45.876053Z digest=sha256:94c686746ab5719a0001d49c4cb2aee0fd54d0df49fadf90769441f8920a3ef9

Observation bd451cf7-dfbe-40ce-8287-55fa06186e09 · outbound

This paper cites Two-way partial auc and its properties.Statistical methods in medical research, 28(1):184–195, 2019.

ScoreShield: Differentially Private Release of Similarity Scores Two-way partial auc and its properties.Statistical methods in medical research, 28(1):184–195, 2019

Reference 95

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no resolver link, observed 2026-07-31T02:59:45.880064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T02:59:45.880064Z digest=sha256:3fc3ed62c412018e230696da77482999390be9fdbb4121e002cbe8285353796f

Observation f32824f2-64a3-4658-a2db-0a1f605d795c · outbound

This paper cites Privacy preserving collaborative filtering via the johnson-lindenstrauss transform.

ScoreShield: Differentially Private Release of Similarity Scores Privacy preserving collaborative filtering via the johnson-lindenstrauss transform

Reference 96

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no resolver link, observed 2026-07-31T02:59:45.884753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T02:59:45.884753Z digest=sha256:d812daf1cc564e6351861395e026cc5afabf2b705aede1227bc069214829a7f1

Observation 437dbac3-c650-4bb1-98de-4355d3d23b98 · outbound

This paper cites When all we need is a piece of the pie: A generic framework for optimizing two-way partial auc.

ScoreShield: Differentially Private Release of Similarity Scores When all we need is a piece of the pie: A generic framework for optimizing two-way partial auc

Reference 97

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unresolved
no resolver link, observed 2026-07-31T02:59:45.889162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T02:59:45.889162Z digest=sha256:e8e1306efca879eb1472cd0c9133411cde732e6e085d7daa9fd2663b9fc06599

Pith citing papers

No inbound Pith citation observations are available.