Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T10:55:08.221003Z
Paper Citation Record · LEDGER
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services
As of 15 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2608.05036.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
55 of 55 outbound references displayed
- verified exact1
- verified fuzzy46
- unresolved7
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation bf89b759-c89a-4d9b-af5a-1f54a2f2d55e · outbound
This paper cites Turning your weakness into a strength: Watermarking deep neural networks by back- dooring.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Turning your weakness into a strength: Watermarking deep neural networks by back- dooring
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:09.302226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation ba6c8aa3-1f74-44d1-9351-7492a77c6d63 · outbound
This paper cites Model leeching: An extrac- tion attack targeting large language models, 2023.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Model leeching: An extrac- tion attack targeting large language models, 2023
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:09.283068Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation cc06f37e-b633-4b0f-9b54-d91e1087d3d0 · outbound
This paper cites Quantifying memorization across neural language mod- els.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Quantifying memorization across neural language mod- els
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:09.258237Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e57f6fbd-dd50-49b6-a183-d9926d6c04b6 · outbound
This paper cites Extracting training data from large language models.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Extracting training data from large language models
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:09.237817Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation d6931319-a011-4f51-9486-45fcd31df05e · outbound
This paper cites Exploring Connections Between Active Learning and Model Extraction.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Exploring Connections Between Active Learning and Model Extraction
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T10:55:08.291132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation df0af1e5-cb82-4afa-a2ea-ed6e7dcf3df7 · outbound
This paper cites MeaeQ: Mount model extraction attacks with efficient queries.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services MeaeQ: Mount model extraction attacks with efficient queries
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:09.217727Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 7bb5b9e4-b0f8-46bf-b747-c9c40db8f0c6 · outbound
This paper cites QLoRA: Efficient finetuning of quan- 12 tized LLMs.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services QLoRA: Efficient finetuning of quan- 12 tized LLMs
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:09.196144Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation ee8e2d25-0008-423e-a7c4-cfc851d16de6 · outbound
This paper cites Do membership inference attacks work on large language models? InFirst Conference on Language Modeling, 2024.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Do membership inference attacks work on large language models? InFirst Conference on Language Modeling, 2024
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:09.164281Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 250ef64d-862f-405a-b510-a2de7c22b0fa · outbound
This paper cites Membership inference at- tacks against fine-tuned large language models via self- prompt calibration.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Membership inference at- tacks against fine-tuned large language models via self- prompt calibration
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:09.137243Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c567ffa8-e147-4ace-a4a1-919adaf02be2 · outbound
This paper cites De- BERTaV3: Improving DeBERTa using ELECTRA-style pre-training with gradient-disentangled embedding shar- ing, 2021.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services De- BERTaV3: Improving DeBERTa using ELECTRA-style pre-training with gradient-disentangled embedding shar- ing, 2021
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:09.113203Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a1af4022-94c2-43ef-a46e-9698c3ff2eaa · outbound
This paper cites Extracted BERT model leaks more information than you think! InProceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 1530–1537, 2022.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Extracted BERT model leaks more information than you think! InProceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 1530–1537, 2022
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:09.090607Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5e5acf48-2a7a-4bd8-a59d-6ac389893788 · outbound
This paper cites an unresolved cited work.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T10:55:09.060862Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 465ecc2f-c3a6-4035-b79f-e0c314f3959f · outbound
This paper cites Parameter- efficient transfer learning for nlp.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Parameter- efficient transfer learning for nlp
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:09.037451Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 745361be-852a-40f0-91af-2fff291b7d7e · outbound
This paper cites LoRA: Low-Rank Adaptation of Large Language Models.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services LoRA: Low-Rank Adaptation of Large Language Models
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:55:08.006456Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 71236095-2778-4b57-a2da-7edd8cdd0f18 · outbound
This paper cites Editing models with task arithmetic.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Editing models with task arithmetic
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:09.013109Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation d3563dd1-28d3-43ff-ab52-70835d986749 · outbound
This paper cites High accuracy and high fidelity extraction of neural networks.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services High accuracy and high fidelity extraction of neural networks
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.993740Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e0405b9c-8b7c-4ab7-a59d-5a16546348cf · outbound
This paper cites Choquette-Choo, Varun Chandrasekaran, and Nicolas Papernot.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Choquette-Choo, Varun Chandrasekaran, and Nicolas Papernot
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.968169Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation d2fce507-54d4-4895-8c29-80f25eabe7d6 · outbound
This paper cites an unresolved cited work.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Unresolved cited work
Reference 18
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T10:55:08.950038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation ef2627b2-2910-4662-be5c-a6a01d5e7f5d · outbound
This paper cites an unresolved cited work.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Unresolved cited work
Reference 19
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T10:55:08.929249Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 3b2cdc1f-1d33-476c-92ec-c295957d3512 · outbound
This paper cites an unresolved cited work.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Unresolved cited work
Reference 20
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T10:55:08.908577Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation ef84724a-9f66-456c-a409-759f8a6bb2d5 · outbound
This paper cites The thieves on sesame street are polyglots—extracting multilingual models from mono- lingual APIs.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services The thieves on sesame street are polyglots—extracting multilingual models from mono- lingual APIs
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.887689Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 0157f41d-8d70-4cf4-8d96-04b7632037f5 · outbound
This paper cites A watermark for large language models.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services A watermark for large language models
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.866793Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 3bba45ed-7348-4306-9d21-396baf74f958 · outbound
This paper cites ClearStamp: A human-visible and robust model- ownership proof based on transposed model training.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services ClearStamp: A human-visible and robust model- ownership proof based on transposed model training
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.840400Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation caf9bd9e-5466-4b5d-b01f-9b7517b811cd · outbound
This paper cites The power of scale for parameter-efficient prompt tuning.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services The power of scale for parameter-efficient prompt tuning
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.822331Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 4d36ddb2-883a-4216-b995-82b93bcfa932 · outbound
This paper cites Prefix-tuning: Optimiz- ing continuous prompts for generation.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Prefix-tuning: Optimiz- ing continuous prompts for generation
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.803666Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 61c14818-43d7-4614-8de9-bf3350ef80c3 · outbound
This paper cites an unresolved cited work.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Unresolved cited work
Reference 26
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T10:55:08.784238Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b7be89bc-5396-4f87-9306-ed619ef021e3 · outbound
This paper cites DoRA: Weight- decomposed low-rank adaptation.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services DoRA: Weight- decomposed low-rank adaptation
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.764778Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e3b35890-43f2-4416-94ac-ff23b30fc76b · outbound
This paper cites Privacy-preserving low-rank adap- tation against membership inference attacks for latent diffusion models, 2024.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Privacy-preserving low-rank adap- tation against membership inference attacks for latent diffusion models, 2024
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.746817Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 410fdc59-d678-420e-a8b8-8a18fe8b44bc · outbound
This paper cites Dataset inference: Ownership resolution in ma- chine learning.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Dataset inference: Ownership resolution in ma- chine learning
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.730017Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1acd3929-8b06-4f26-bdac-20751288349b · outbound
This paper cites Membership inference attacks against language models via neighbourhood compari- son.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Membership inference attacks against language models via neighbourhood compari- son
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.713850Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation f8a16126-99dc-4145-9099-850edc0fda82 · outbound
This paper cites Meta Llama 3 model card.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Meta Llama 3 model card
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.699065Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 783939cb-2cbe-4c14-8e68-285b71064493 · outbound
This paper cites Quantifying privacy risks of masked language models using membership inference attacks.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Quantifying privacy risks of masked language models using membership inference attacks
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:55:08.102343Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b32db1e8-9b25-42b6-a3d3-6cf72d7677d4 · outbound
This paper cites Com- prehensive privacy analysis of deep learning: Passive and active white-box inference attacks against central- ized and federated learning.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Com- prehensive privacy analysis of deep learning: Passive and active white-box inference attacks against central- ized and federated learning
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.673614Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 91194cd0-a5ff-4fd8-8a9b-35bf9c8f81bc · outbound
This paper cites SoK: All you need to know about on-device ML model extraction—the gap between research and practice.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services SoK: All you need to know about on-device ML model extraction—the gap between research and practice
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.657239Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 9447d415-be0e-45e8-be1f-01c3a3888c81 · outbound
This paper cites Knockoff nets: Stealing functionality of black-box mod- els.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Knockoff nets: Stealing functionality of black-box mod- els
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.641346Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 48f68b75-9f8f-44d7-9cb7-580bc15fc57a · outbound
This paper cites Prediction poisoning: Utility-constrained defenses against model stealing attacks.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Prediction poisoning: Utility-constrained defenses against model stealing attacks
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.627358Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation cde308dd-d546-458f-b1d9-87915036261e · outbound
This paper cites Berkay Celik, and Ananthram Swami.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Berkay Celik, and Ananthram Swami
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.612076Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 4eb72dc9-36f0-42d7-80e5-5967fae0c297 · outbound
This paper cites Kornaropoulos, and Giuseppe Ateniese.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Kornaropoulos, and Giuseppe Ateniese
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.596100Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 97f9c3d5-67c7-495c-b1ef-0df46618216b · outbound
This paper cites DeepEclipse: How to break white-box DNN-watermarking schemes.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services DeepEclipse: How to break white-box DNN-watermarking schemes
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.580682Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 3e9f977b-a3f8-43ae-8d2d-393f7e700ae6 · outbound
This paper cites AdapterFusion: Non-destructive task composition for transfer learning.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services AdapterFusion: Non-destructive task composition for transfer learning
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.565193Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 3c3355e7-d2b6-4ff4-aa31-e943c0b3f9bb · outbound
This paper cites LoRA soups: Merging LoRAs for practical skill composition tasks.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services LoRA soups: Merging LoRAs for practical skill composition tasks
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.546741Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 48c65356-9b8c-4614-bbf5-bacf4187c02d · outbound
This paper cites Provably robust multi-bit watermarking for AI-generated text.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Provably robust multi-bit watermarking for AI-generated text
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.529795Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b21d19b1-4479-4898-9156-80a8939a8272 · outbound
This paper cites LoRA-Leak: Membership in- ference attacks against LoRA fine-tuned language mod- els, 2025.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services LoRA-Leak: Membership in- ference attacks against LoRA fine-tuned language mod- els, 2025
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.514976Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1f1b3d24-5439-49e9-b66f-3127bae6c5e0 · outbound
This paper cites Membership inference attacks against machine learning models.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Membership inference attacks against machine learning models
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.499104Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 04380860-20c3-4968-b26d-d86091489888 · outbound
This paper cites ModelGuard: Information-theoretic de- fense against model extraction attacks.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services ModelGuard: Information-theoretic de- fense against model extraction attacks
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.483805Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 9bde8f69-496f-4331-9dd1-c82c8da5b1f5 · outbound
This paper cites Reiter, and Thomas Ristenpart.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Reiter, and Thomas Ristenpart
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.464550Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c46ef9ec-0612-4343-8969-15d22398bd37 · outbound
This paper cites Embedding watermarks into deep neu- ral networks.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Embedding watermarks into deep neu- ral networks
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.446289Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 2d2b8201-6f0a-4a8c-8ee4-40759d0515d8 · outbound
This paper cites Imitation attacks and defenses for black-box machine translation systems.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Imitation attacks and defenses for black-box machine translation systems
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.430330Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation bb31895e-ce8e-4d2c-a281-ef597f8b6985 · outbound
This paper cites TIES-merging: Resolving inter- ference when merging models.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services TIES-merging: Resolving inter- ference when merging models
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.414045Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b984061f-71e3-4a9d-99f9-84a6f43df09c · outbound
This paper cites Re- thinking white-box watermarks on deep learning models under neural structural obfuscation.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Re- thinking white-box watermarks on deep learning models under neural structural obfuscation
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.396703Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1d736c9d-727f-4863-9a4e-e0fa1c627019 · outbound
This paper cites Data-Free Model-Related attacks: Unleashing the potential of generative AI.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Data-Free Model-Related attacks: Unleashing the potential of generative AI
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.380331Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 4653c068-e5a3-4e75-aed4-562e5f1ddad9 · outbound
This paper cites Inan, Gautam Kamath, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, and Huishuai Zhang.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Inan, Gautam Kamath, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, and Huishuai Zhang
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.364327Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 03d419bc-477a-4086-a75d-301725d9699b · outbound
This paper cites Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.346643Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 3b5bc6e9-b132-4885-839d-b4fd729b2e71 · outbound
This paper cites REMARK-LLM: A robust and efficient watermarking framework for gener- ative large language models.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services REMARK-LLM: A robust and efficient watermarking framework for gener- ative large language models
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:55:08.329061Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 0ab78037-6d2d-4f17-b20d-64227d2e267c · outbound
This paper cites family-level.
When Do PEFT Adaptations Leak Structure? Measuring Black-Box Structural Bounds in Public-Base Model Services family-level
Reference 55
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-06T10:55:08.309096Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Pith citing papers
No inbound Pith citation observations are available.