Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment | Paper Citation Record

Observation d5f70058-0b95-4466-a41d-bca2488068d0 · outbound

This paper cites The claude 3 model family: Opus, sonnet, haiku.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment The claude 3 model family: Opus, sonnet, haiku

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.363085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 207d9e11-ab14-42e4-9ca5-33313ec77f83 · outbound

This paper cites an unresolved cited work.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Unresolved cited work

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.378372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 52b85ff4-ec21-4d2d-956c-f225c163f446 · outbound

This paper cites Qwen3-VL Technical Report.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Qwen3-VL Technical Report

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-20T14:08:20.931018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 78e87847-3488-489d-8fc4-cc3c16ab413d · outbound

This paper cites Yi: Open foundation models by 01.ai.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Yi: Open foundation models by 01.ai

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:08:20.289410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 7476436a-c55a-4f3d-9ce7-b243ba11ec31 · outbound

This paper cites Spinning Language Models: Risks of Propaganda-As-A-Service and Countermeasures , url=.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Spinning Language Models: Risks of Propaganda-As-A-Service and Countermeasures , url=

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T14:08:20.299638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 3444519f-be4e-4d93-967b-f66582565795 · outbound

This paper cites Extracting training data from diffusion models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Extracting training data from diffusion models

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.366901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation b9046128-0542-4384-8df3-3ac6aa95e2bd · outbound

This paper cites The secret sharer: Evalu- ating and testing unintended memorization in neu- ral networks.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment The secret sharer: Evalu- ating and testing unintended memorization in neu- ral networks

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.370802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation ee084fca-654e-419c-9fa7-06e76b9f215e · outbound

This paper cites Brown, Dawn Song, Úlfar Erlings- son, Alina Oprea, and Colin Raffel.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Brown, Dawn Song, Úlfar Erlings- son, Alina Oprea, and Colin Raffel

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.372847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 44fdad9f-4020-4660-948f-8353761311eb · outbound

This paper cites Gan-leaks: A taxonomy of membership inference at- tacks against generative models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Gan-leaks: A taxonomy of membership inference at- tacks against generative models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.357305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 2140d36b-aa01-45ea-b3c1-96c6a6156b37 · outbound

This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality.See https://vicuna.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality.See https://vicuna

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.353476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation fef601b6-1a3e-4ab3-b3e3-b50a66a21d2b · outbound

This paper cites Choquette-Choo, Florian Tramer, Nicholas Carlini, and Nicolas Papernot.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Choquette-Choo, Florian Tramer, Nicholas Carlini, and Nicolas Papernot

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.326437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation b37a7a27-3bac-43db-ab50-6fadc7c356f1 · outbound

This paper cites InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-05-20T14:08:20.897403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation a7ee9512-36e1-4874-b0b2-8b1dd9dcb094 · outbound

This paper cites BERT : Pre-training of Deep Bidirectional Transformers for Language Understanding.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment BERT : Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 14

Resolution: verified exact; doi, observed 2026-05-20T14:08:20.302705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 458721fd-689f-4cd9-8791-9a1b3a6397dd · outbound

This paper cites Do membership inference attacks work on large language models? InFirst Conference on Language Modeling.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Do membership inference attacks work on large language models? InFirst Conference on Language Modeling

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.361018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 6f51ca35-e414-4d2e-9ca6-e7a32df6f7c0 · outbound

This paper cites Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:08:20.925754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 3326f827-9b4f-497c-9634-95f229ad0545 · outbound

This paper cites Llama- adapter v2: Parameter-efficient visual instruction model.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Llama- adapter v2: Parameter-efficient visual instruction model

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.359214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation f7dc437c-167a-401d-b5d6-554ec5c206a4 · outbound

This paper cites LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-05-20T14:08:20.922528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 3cf1fd5b-f1c6-4b8d-8d62-9c701192d38c · outbound

This paper cites Vision-language models for medical report generation and visual question answering: a review.Frontiers in Artificial Intelligence, 7, November 2024.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Vision-language models for medical report generation and visual question answering: a review.Frontiers in Artificial Intelligence, 7, November 2024

Reference 19

Resolution: verified exact; doi, observed 2026-05-20T14:08:20.284763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 786fae30-2e03-436e-808e-9ad1b6f4a0c4 · outbound

This paper cites LOGAN: Membership Inference Attacks Against Generative Models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment LOGAN: Membership Inference Attacks Against Generative Models

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-20T14:08:20.928481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation f302b152-8ffe-4fd8-b63b-9484e7f48e5d · outbound

This paper cites Dietterich.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Dietterich

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.365079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 0ebddce3-021c-4017-9d95-d366b6ef1c58 · outbound

This paper cites Monte carlo and reconstruction membership in- ference attacks against generative models.Proceedings on Privacy Enhancing Technologies.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Monte carlo and reconstruction membership in- ference attacks against generative models.Proceedings on Privacy Enhancing Technologies

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.368890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation f2dfb342-0169-47fc-97c5-d6a79e596ee2 · outbound

This paper cites Defenses to membership inference attacks: A survey.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Defenses to membership inference attacks: A survey

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.374973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 8e4fda93-65b8-405a-9e03-100ea4d3e007 · outbound

This paper cites M 4i: Multi-modal models member- ship inference.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment M 4i: Multi-modal models member- ship inference

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.349760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 0cafd12b-b189-443d-916a-e259bce524b2 · outbound

This paper cites BLIVA: A Simple Multimodal LLM for Better Handling of Text-Rich Visual Questions.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment BLIVA: A Simple Multimodal LLM for Better Handling of Text-Rich Visual Questions

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:08:20.912443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation bd0e4cbd-b54b-4bce-a456-7a8b27ba4e98 · outbound

This paper cites Membership inference at- tacks against vision-language models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Membership inference at- tacks against vision-language models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.351549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation a266ab13-7d51-468e-bc02-4284aa43f67a · outbound

This paper cites Scaling language-image pre- training via masking.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Scaling language-image pre- training via masking

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.376721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation b3c0534c-7c62-4f43-9360-6e0506a1b97d · outbound

This paper cites Membership inference attacks against large vision-language models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Membership inference attacks against large vision-language models

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.345734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 61670034-d039-4c95-beda-6519c2f38e61 · outbound

This paper cites Membership leakage in label- only exposures.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Membership leakage in label- only exposures

Reference 29

Resolution: malformed identifier; arxiv_id, observed 2026-05-20T14:08:20.937609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 3be7ff62-a0ce-4993-9e45-d7d30d81f132 · outbound

This paper cites Visual instruction tuning.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Visual instruction tuning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.347719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 95524098-67ef-46c9-8404-76f270119633 · outbound

This paper cites Encodermi: Membership inference against pre-trained encoders in contrastive learning.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Encodermi: Membership inference against pre-trained encoders in contrastive learning

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:08:20.322281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 526436aa-b908-4efc-8404-0a816a15f809 · outbound

This paper cites Arondight: Red Teaming Large Vision Language Models with Auto-generated Multi-modal Jailbreak Prompts.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Arondight: Red Teaming Large Vision Language Models with Auto-generated Multi-modal Jailbreak Prompts

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:08:20.909416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation ef6bd352-f293-4a53-a21a-018bb1b20bcc · outbound

This paper cites Membership Inference Attacks by Exploiting Loss Trajectory.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Membership Inference Attacks by Exploiting Loss Trajectory

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:08:20.915762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 103732a1-4172-4488-a25e-11a74f7ce765 · outbound

This paper cites Understanding Membership Inferences on Well-Generalized Learning Models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Understanding Membership Inferences on Well-Generalized Learning Models

Reference 34

Resolution: metadata mismatch; local_arxiv, observed 2026-05-20T14:08:20.918725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation e018e779-7ce6-4261-ad5c-4e8199355ea9 · outbound

This paper cites Membership Inference on Word Embedding and Beyond.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Membership Inference on Word Embedding and Beyond

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:08:20.934285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation df0745d8-d577-4b00-8a21-644cce3b6883 · outbound

This paper cites Membership inference attacks against language models via neighbourhood comparison.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Membership inference attacks against language models via neighbourhood comparison

Reference 36

Resolution: verified exact; doi, observed 2026-05-20T14:08:20.318725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 970635a4-61bc-473e-8b96-4a01ed01218f · outbound

This paper cites Yifan Li, Yifan Du, Kun Zhou, Jinpeng Wang, Xin Zhao, and Ji-Rong Wen.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Yifan Li, Yifan Du, Kun Zhou, Jinpeng Wang, Xin Zhao, and Ji-Rong Wen

Reference 37

Resolution: metadata mismatch; doi, observed 2026-05-20T14:08:20.315247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation dfb02055-81e4-43b8-8975-c68a997bf222 · outbound

This paper cites An empirical analysis of memorization in fine-tuned autore- gressive language models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment An empirical analysis of memorization in fine-tuned autore- gressive language models

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.343990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 5756e435-5de6-4fdf-916a-306a9bd557ef · outbound

This paper cites Can llms keep a secret? testing privacy im- plications of language models via contextual integrity theory.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Can llms keep a secret? testing privacy im- plications of language models via contextual integrity theory

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.340246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 0d512d58-4c6a-489b-9d9a-5ff0e1f4e573 · outbound

This paper cites Wagner, and Saining Xie.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Wagner, and Saining Xie

Reference 40

Resolution: verified exact; doi, observed 2026-05-20T14:08:20.295614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 4bc9215d-c6db-4067-a3af-2ffb04475a47 · outbound

This paper cites GPT-4 Technical Report.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment GPT-4 Technical Report

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-05-20T14:08:20.906359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation c5dcd8a0-1ecd-4bba-ae02-34177f862ff6 · outbound

This paper cites Visual Adversarial Examples Jailbreak Aligned Large Language Models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Visual Adversarial Examples Jailbreak Aligned Large Language Models

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:08:20.903832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation b19f89ff-ee8e-4f26-83c6-e7c1ed68c9f6 · outbound

This paper cites Learning transferable vi- sual models from natural language supervision.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Learning transferable vi- sual models from natural language supervision

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.342021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 9fa88c90-b1cd-4b21-a4d4-291df90ff4d4 · outbound

This paper cites Self- comparison for dataset-level membership inference in large (vision-)language model.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Self- comparison for dataset-level membership inference in large (vision-)language model

Reference 44

Resolution: verified exact; doi, observed 2026-05-20T14:08:20.292923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 35c8cb8b-ad56-429c-bbbf-410c8d7a855c · outbound

This paper cites White-box vs black-box: Bayes optimal strategies for member- ship inference.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment White-box vs black-box: Bayes optimal strategies for member- ship inference

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.355527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation a452e7e4-bb1e-49b5-a747-2556dc913824 · outbound

This paper cites Improved zero-shot classification by adapting vlms with text descriptions.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Improved zero-shot classification by adapting vlms with text descriptions

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.336071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 631e3293-b32a-496f-9adf-90d3c875ed29 · outbound

This paper cites Ml- leaks: Model and data independent membership infer- ence attacks and defenses on machine learning models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Ml- leaks: Model and data independent membership infer- ence attacks and defenses on machine learning models

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.338297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation f79edc86-0980-49ee-a8e9-07b72d121b87 · outbound

This paper cites ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

Reference 48

Resolution: verified exact; local_arxiv, observed 2026-05-20T14:08:20.900418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 2fa9163d-028c-4556-9bd2-b7dce475596b · outbound

This paper cites Detecting pretraining data from large language models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Detecting pretraining data from large language models

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.334279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation efb3e29b-de05-4bd7-bc75-22eb5af910f5 · outbound

This paper cites author Stronati, M.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment author Stronati, M

Reference 50

Resolution: metadata mismatch; doi, observed 2026-05-20T14:08:20.280402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 10caf40b-a0a6-4cb1-bb01-23b157751c5a · outbound

This paper cites Informa- tion leakage in embedding models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Informa- tion leakage in embedding models

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.332523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 6f2fc61e-0799-46b0-9dbf-8b2c61580749 · outbound

This paper cites Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering , pages =.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering , pages =

Reference 52

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T14:08:20.306923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 416b4107-7ed2-494c-9e98-6d27fcd5480c · outbound

This paper cites Data augmentation using random image crop- ping and patching for deep cnns.IEEE Trans.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Data augmentation using random image crop- ping and patching for deep cnns.IEEE Trans

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:08:20.276066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 83c6b20c-67cc-453e-a362-ba32ad6e10bc · outbound

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

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment LLaMA: Open and Efficient Foundation Language Models

Reference 54

Resolution: verified exact; local_arxiv, observed 2026-05-20T14:08:20.893951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 967c2bf5-c7c9-4ddb-bc9b-4e2d9dc75b2c · outbound

This paper cites Freeman, Frédo Durand, Eli Shechtman, and Xun Huang.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Freeman, Frédo Durand, Eli Shechtman, and Xun Huang

Reference 55

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T14:08:20.312150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 4fca02a6-05f8-4a03-8a68-c2c12d842dfe · outbound

This paper cites CogVLM: Visual Expert for Pretrained Language Models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment CogVLM: Visual Expert for Pretrained Language Models

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-05-20T14:08:20.888325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation bc0ae459-9571-4f81-8216-49004f77ed1d · outbound

This paper cites On the importance of diffi- culty calibration in membership inference attacks.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment On the importance of diffi- culty calibration in membership inference attacks

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.328323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation ce40e591-c264-47d0-9f20-2eeae195db09 · outbound

This paper cites an unresolved cited work.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Unresolved cited work

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.330636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 86063288-5c08-41d7-9ffc-2b9f23ef74f0 · outbound

This paper cites Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:08:20.891338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 6d5f088d-89c1-4588-8ddd-5eb037f38e90 · outbound

This paper cites Privacy risk in machine learning: Analyz- ing the connection to overfitting.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Privacy risk in machine learning: Analyz- ing the connection to overfitting

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.322657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation f5bd13a2-8b44-4b41-a6c5-e5972c68b0c2 · outbound

This paper cites Yeats, Yang Ouyang, Martin Kuo, Jianyi Zhang, Hao (Frank) Yang, and Hai Li.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Yeats, Yang Ouyang, Martin Kuo, Jianyi Zhang, Hao (Frank) Yang, and Hai Li

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.324456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 252a987c-6474-4500-9386-b8dd1486ccef · outbound

This paper cites URL: https://openreview.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment URL: https://openreview

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T14:08:21.320510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation a7ca5b6c-4547-4fe3-8f44-af9831418c19 · outbound

This paper cites A Survey of Large Language Models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment A Survey of Large Language Models

Reference 63

Resolution: verified exact; local_arxiv, observed 2026-05-20T14:08:20.940492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation a82a8851-ae79-40b3-8a7b-1f90617ee495 · outbound

This paper cites Minigpt-4: Enhancing vision- language understanding with advanced large language 19 models.

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment Minigpt-4: Enhancing vision- language understanding with advanced large language 19 models

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:08:20.885170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers