SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels | Paper Citation Record

Observation 5d873e0d-43f7-4d2e-a762-822721deff8a · outbound

This paper cites Toy Models of Superposition.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Toy Models of Superposition

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.039331Z

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Observation 10bcbc85-fb11-43f5-9cd0-e858750647b2 · outbound

This paper cites Steering Large Language Model Activations in Sparse Spaces.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Steering Large Language Model Activations in Sparse Spaces

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.044383Z

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Observation fd79aa5a-815d-4ed7-a171-251fa3319cfa · outbound

This paper cites Attention is all you need,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Attention is all you need,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.049429Z

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Observation 7b110dab-1baa-4650-b9ba-a11555bd46eb · outbound

This paper cites Deja Vu: Contextual sparsity for efficient LLMs at inference time,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Deja Vu: Contextual sparsity for efficient LLMs at inference time,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.053890Z

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Observation fca7d58e-0a52-4ee3-99f0-7b6aa64a066c · outbound

This paper cites PIT: Optimization of dynamic sparse deep learning models via permutation invariant transformation,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels PIT: Optimization of dynamic sparse deep learning models via permutation invariant transformation,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.058066Z

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Observation c2a5e8a4-0b0e-4996-a1c9-fdf317cc822f · outbound

This paper cites LLM in a flash: Efficient large language model inference with limited memory,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels LLM in a flash: Efficient large language model inference with limited memory,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.062260Z

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Observation 273ee46f-1f9c-418b-b3b6-16cd2aae8b35 · outbound

This paper cites PowerInfer: Fast large language model serving with a consumer-grade GPU,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels PowerInfer: Fast large language model serving with a consumer-grade GPU,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.066861Z

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Observation 57cc3a2f-510a-4154-936f-42009b093336 · outbound

This paper cites PowerInfer-2: Fast Large Language Model Inference on a Smartphone.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels PowerInfer-2: Fast Large Language Model Inference on a Smartphone

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.070796Z

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Observation 761ce794-93f6-423d-9d73-2a46c94157e0 · outbound

This paper cites Telling your secrets without page faults: Stealthy page table-based attacks on enclaved execution,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Telling your secrets without page faults: Stealthy page table-based attacks on enclaved execution,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.075830Z

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Observation cdf3eefa-7e06-4aa6-a894-84abd5d03b9c · outbound

This paper cites Controlled-channel attacks: Determin- istic side channels for untrusted operating systems,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Controlled-channel attacks: Determin- istic side channels for untrusted operating systems,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.080570Z

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Observation d88ff3b0-96c5-4660-a760-5ee102c77758 · outbound

This paper cites HIDE: An infrastructure for efficiently protecting information leakage on the address bus,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels HIDE: An infrastructure for efficiently protecting information leakage on the address bus,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.085451Z

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Observation 95ef01ef-4515-4c94-9454-b1a942471ce2 · outbound

This paper cites An off-chip attack on hardware enclaves via the memory bus,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels An off-chip attack on hardware enclaves via the memory bus,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.090002Z

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Observation 5702f6a0-05dc-44b0-a6c5-a62f69c51de6 · outbound

This paper cites Transparent domain extensions: Breaking Intel TEE implementations via DDR5 memory bus interposition,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Transparent domain extensions: Breaking Intel TEE implementations via DDR5 memory bus interposition,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.094491Z

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Observation 57be9270-011b-4bdb-b3ad-6550620bbddc · outbound

This paper cites Unsupervised feature selection towards pattern discrimination power,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Unsupervised feature selection towards pattern discrimination power,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.099130Z

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Observation cc0ec2c6-3f23-41a8-9cbb-a37cc96decb9 · outbound

This paper cites Understanding deep image representa- tions by inverting them,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Understanding deep image representa- tions by inverting them,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.103843Z

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Observation f512f1df-e0b4-45b8-a509-66018ee21b74 · outbound

This paper cites Prompt inversion attack against collaborative inference of large language models,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Prompt inversion attack against collaborative inference of large language models,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.108508Z

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Observation b9837138-f605-4cb3-9bf3-930abcdee00c · outbound

This paper cites Depth gives a false sense of privacy: LLM internal states inversion,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Depth gives a false sense of privacy: LLM internal states inversion,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.113362Z

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Observation e57b9167-4424-4e8b-a13d-6c655a77d36b · outbound

This paper cites Language model inversion,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Language model inversion,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.118112Z

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Observation 2e6771a7-5e11-4f52-9332-11eb7702f379 · outbound

This paper cites Linux kernel virtual machine.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Linux kernel virtual machine

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.123050Z

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Observation d35f7e37-27b0-4171-8e66-5f7fe6b71de5 · outbound

This paper cites QEMU, a fast and portable dynamic translator,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels QEMU, a fast and portable dynamic translator,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.127912Z

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Observation 7360f858-a547-4c4a-949d-1992c596c878 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels LoRA: Low-Rank Adaptation of Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.132583Z

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Observation f29d0af7-28a0-4a62-994c-ee19b1c950a6 · outbound

This paper cites The lazy neuron phenomenon: On emergence of activation sparsity in Transformers,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels The lazy neuron phenomenon: On emergence of activation sparsity in Transformers,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.137831Z

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Observation 7879e60c-da60-439b-ad24-41cebf40c861 · outbound

This paper cites ReLU$^2$ Wins: Discovering Efficient Activation Functions for Sparse LLMs.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels ReLU$^2$ Wins: Discovering Efficient Activation Functions for Sparse LLMs

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.142851Z

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Observation a97131da-d442-4562-91e2-dabea9ae269c · outbound

This paper cites ReLU strikes back: Exploiting activation sparsity in large language models,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels ReLU strikes back: Exploiting activation sparsity in large language models,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.147869Z

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Observation ca5583f5-aec6-44af-86e2-ebf31dfebbe1 · outbound

This paper cites Efficient LLM inference using dynamic input pruning and cache-aware masking,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Efficient LLM inference using dynamic input pruning and cache-aware masking,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.152646Z

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Observation d73493a2-aee1-409d-8ce4-583df14135ee · outbound

This paper cites Training-free activation sparsity in large language models,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Training-free activation sparsity in large language models,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.157210Z

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Observation aabfa77b-5b1a-4084-b6b7-f320e85707a3 · outbound

This paper cites Intel ® Software Guard Extensions programming reference,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Intel ® Software Guard Extensions programming reference,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.162324Z

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Observation dfc45626-dcab-48ed-93ed-772c10d71db6 · outbound

This paper cites SEVurity: No security without integrity: Breaking integrity-free memory encryption with minimal assumptions,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels SEVurity: No security without integrity: Breaking integrity-free memory encryption with minimal assumptions,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.171922Z

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Observation f5faf41d-23b3-4be5-8c68-eb41127bf8a5 · outbound

This paper cites Exploiting unprotected I/O operations in AMD’s secure encrypted virtualization,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Exploiting unprotected I/O operations in AMD’s secure encrypted virtualization,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.176596Z

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Observation 8f0399e4-a210-4202-b924-36d30da38809 · outbound

This paper cites TDXdown: Single-stepping and instruction counting attacks against Intel TDX,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels TDXdown: Single-stepping and instruction counting attacks against Intel TDX,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.181128Z

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Observation ed5a070f-f425-4505-a1c5-2f583bc64cdf · outbound

This paper cites TDXRay: Microarchitectural side-channel analysis of Intel TDX for real-world workloads,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels TDXRay: Microarchitectural side-channel analysis of Intel TDX for real-world workloads,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.185861Z

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Observation bea6c108-9b80-46dd-9c28-ebbe7175f734 · outbound

This paper cites AMD SEV-SNP,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels AMD SEV-SNP,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.190501Z

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Observation 17870dc9-61fe-4721-94d0-7adc5bc9f5ae · outbound

This paper cites Intel® Trust Domain Extensions,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Intel® Trust Domain Extensions,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.195157Z

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Observation daef0a48-b250-4ea4-98fb-c9cc586e01da · outbound

This paper cites Intel® Trust Domain Extensions (Intel® TDX) module base archi- tecture specification,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Intel® Trust Domain Extensions (Intel® TDX) module base archi- tecture specification,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.199755Z

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Observation 1e0c5b9c-44d4-4f9f-b3a7-3b5fdbcd37f6 · outbound

This paper cites QEMU system emulation user’s guide.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels QEMU system emulation user’s guide

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.203786Z

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Observation 73290c48-ad1a-49ff-b01c-8a2619883586 · outbound

This paper cites DarkneTZ: Towards model privacy at the edge using trusted execution environments,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels DarkneTZ: Towards model privacy at the edge using trusted execution environments,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.208016Z

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Observation 109cd24f-4542-4ad5-957b-948ba67e61a1 · outbound

This paper cites Guaran- TEE: Towards attestable and private ML with CCA,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Guaran- TEE: Towards attestable and private ML with CCA,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.212067Z

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Observation 23f9841e-467f-40cd-bdc1-ea5e9dea6b07 · outbound

This paper cites ASGARD: Protecting on- device deep neural networks with virtualization-based trusted execution environments,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels ASGARD: Protecting on- device deep neural networks with virtualization-based trusted execution environments,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.215941Z

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Observation 207c62cc-b304-41d5-9294-587c835cb9d9 · outbound

This paper cites PipeLLM: Fast and confidential large language model services with speculative pipelined encryption,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels PipeLLM: Fast and confidential large language model services with speculative pipelined encryption,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.219823Z

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Observation 05815b93-037c-40ca-b475-c927bfffa6c0 · outbound

This paper cites TZ-LLM: Protecting on-device large language models with Arm TrustZone,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels TZ-LLM: Protecting on-device large language models with Arm TrustZone,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.223571Z

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Observation 6c071ed7-d9cd-4ece-9cd6-209bf3fd5abb · outbound

This paper cites Enabling more private generative AI,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Enabling more private generative AI,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.227427Z

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Observation d54abf44-3654-4f5f-815a-4c731ab9e917 · outbound

This paper cites Confidential inference via trusted virtual machines,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Confidential inference via trusted virtual machines,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.236703Z

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Observation afe8c81b-dd9f-4464-89fa-0cfbb01e108c · outbound

This paper cites Confidential AI,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Confidential AI,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.338080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8eb1e61b-a2a6-445a-bd67-a85baef58149 · outbound

This paper cites Confidential LLM inference: Performance and cost across CPU and GPU TEEs,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Confidential LLM inference: Performance and cost across CPU and GPU TEEs,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.324151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e4abd677-0450-45d9-95d4-47059da02b79 · outbound

This paper cites Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.255492Z

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Observation f6f2e986-8999-4255-a836-30f29156d4c9 · outbound

This paper cites I know what you asked: Prompt leakage via KV-cache sharing in multi-tenant LLM serving,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels I know what you asked: Prompt leakage via KV-cache sharing in multi-tenant LLM serving,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.309776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2b0c42bd-19b9-49a0-9378-214fd0c3b6f9 · outbound

This paper cites I know what you said: Unveiling hardware cache side-channels in local large language model inference,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels I know what you said: Unveiling hardware cache side-channels in local large language model inference,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.276388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e3c81788-1891-4778-a757-d0d2874536f6 · outbound

This paper cites Learning to embed categorical features without embedding tables for recommendation,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Learning to embed categorical features without embedding tables for recommendation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.235548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1d093d84-d08f-4004-9145-7437ecda2100 · outbound

This paper cites Efficient memory side-channel protection for embedding generation in machine learning,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Efficient memory side-channel protection for embedding generation in machine learning,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.193493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4b976453-5ec4-4ba4-a1db-2987afe53d7d · outbound

This paper cites virtio: Towards a de-facto standard for virtual I/O devices,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels virtio: Towards a de-facto standard for virtual I/O devices,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.179324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 858f4463-fd5c-45aa-b2b4-7559a8f873c3 · outbound

This paper cites Virtual I/O device (VIRTIO) version 1.2,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Virtual I/O device (VIRTIO) version 1.2,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.165255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6c212a3d-b851-4ffd-ba04-3c3a233afb0b · outbound

This paper cites Implementing dm-verity,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Implementing dm-verity,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.151763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 470efed9-4ebc-43fe-b129-bf3cf01112c4 · outbound

This paper cites Intel trust domain extensions (TDX) security review,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Intel trust domain extensions (TDX) security review,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.138259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation eeb6ad1e-8cad-445b-a72f-35afd6fe339f · outbound

This paper cites Shadow in the cache: Unveiling and mitigating privacy risks of KV-cache in LLM inference,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Shadow in the cache: Unveiling and mitigating privacy risks of KV-cache in LLM inference,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.123977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4ec6d934-30c6-47d6-85fd-05955a57a80c · outbound

This paper cites LLMmap: Fingerprinting for large language models,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels LLMmap: Fingerprinting for large language models,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.109056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 11fd0aa4-3fbd-449c-aa48-9145852ee155 · outbound

This paper cites Reverse engineering convolutional neural networks through side-channel information leaks,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Reverse engineering convolutional neural networks through side-channel information leaks,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.093908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 863bf77b-d28d-4b5b-b0a3-90ecd1a96f58 · outbound

This paper cites Cache telepathy: Leveraging shared resource attacks to learn DNN architectures,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Cache telepathy: Leveraging shared resource attacks to learn DNN architectures,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.079818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a1d7f3ed-f907-4143-a9ce-3e9e22e8b793 · outbound

This paper cites DeepTheft: Stealing DNN model architectures through power side channel,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels DeepTheft: Stealing DNN model architectures through power side channel,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.065398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ec827df2-7a9b-43bd-ba12-a244db1373d4 · outbound

This paper cites TDXploit: Novel techniques for single-stepping and cache attacks on Intel TDX,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels TDXploit: Novel techniques for single-stepping and cache attacks on Intel TDX,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.050728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7ba97e26-05cc-4e72-9a73-c1bde52d3b36 · outbound

This paper cites Downey,The little book of semaphores.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Downey,The little book of semaphores

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:32.017917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 41f0df57-809c-4dd1-9668-cc547bafc773 · outbound

This paper cites A law of next-token prediction in large language models,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels A law of next-token prediction in large language models,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.924393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 509255af-2807-4b2f-8c24-708e33413096 · outbound

This paper cites OPT: Open pre-trained Transformer language models,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels OPT: Open pre-trained Transformer language models,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.811409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e708f52d-2b91-42e3-8ba3-7371aeb4344a · outbound

This paper cites Sparse large language models with ReLU activation,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Sparse large language models with ReLU activation,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.716837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 750c1c57-8470-4b53-a71b-02a37eb519cc · outbound

This paper cites Nemotron-3-8B-Base-4k,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Nemotron-3-8B-Base-4k,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.667717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a33c1167-b6eb-4fb0-a10e-1aa7c8adeddc · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.354527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19573997-1609-4ce4-8a92-bd38b6456023 · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Gemma: Open Models Based on Gemini Research and Technology

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.359124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16a00a21-9606-4667-afc8-fe5432233130 · outbound

This paper cites Skytrax airline reviews,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Skytrax airline reviews,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.654055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c68454e2-704a-4dd9-bb08-30883027ee06 · outbound

This paper cites MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.368341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf35c5bb-fe3d-444f-9b9b-e094bcea3e90 · outbound

This paper cites Neural Legal Judgment Prediction in English.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Neural Legal Judgment Prediction in English

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.373095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23b79c69-b143-453d-9c70-b2c50139d841 · outbound

This paper cites Private prompts,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Private prompts,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.638347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation caaf656e-902a-45f7-9a41-dc54e2c97eee · outbound

This paper cites System prompt leakage,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels System prompt leakage,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.623692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d7fee51f-832f-43d1-8efc-528c756bac3c · outbound

This paper cites Extracting prompts by inverting LLM outputs,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Extracting prompts by inverting LLM outputs,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.608658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0e966bf3-98aa-4cf2-b725-efd0cc294a10 · outbound

This paper cites The early bird catches the leak: Unveiling timing side channels in LLM serving systems,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels The early bird catches the leak: Unveiling timing side channels in LLM serving systems,

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.389400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd1c589c-65c5-4ad4-a46f-386c73719985 · outbound

This paper cites System Prompt Extraction Attacks and Defenses in Large Language Models.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels System Prompt Extraction Attacks and Defenses in Large Language Models

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.393348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2719c873-2e7c-4bce-9014-a2dfdbcff1d5 · outbound

This paper cites LaMP: When large language models meet personalization,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels LaMP: When large language models meet personalization,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.594064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0ed58c0d-e8e2-4625-ab8a-bb7cb9d8a0c9 · outbound

This paper cites Democratizing large language models via personalized parameter-efficient fine-tuning,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Democratizing large language models via personalized parameter-efficient fine-tuning,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.579858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 64083830-4222-4225-8409-0a910a184d5e · outbound

This paper cites From Persona to Personalization: A Survey on Role-Playing Language Agents.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels From Persona to Personalization: A Survey on Role-Playing Language Agents

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.405128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b7e5270-1b41-406d-b2b4-f3fe9f4fa776 · outbound

This paper cites Personalized generation in large model era: A 15 survey,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Personalized generation in large model era: A 15 survey,

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.566459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d6a6f192-481c-4aa4-9f90-c5ba66f1e655 · outbound

This paper cites llama.cpp: LLM inference in C/C++,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels llama.cpp: LLM inference in C/C++,

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.552209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9edcc483-927f-484b-bd18-2de38ef24495 · outbound

This paper cites Using the Linux kernel Tracepoints.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Using the Linux kernel Tracepoints

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.538439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 106b3d84-c195-4be6-88c5-18e8cf8ab65f · outbound

This paper cites Linux extended BPF (eBPF) tracing tools,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Linux extended BPF (eBPF) tracing tools,

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.523728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5f1a750e-324b-4f2e-9c96-dd9d63f81553 · outbound

This paper cites BLEU: a method for automatic evaluation of machine translation,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels BLEU: a method for automatic evaluation of machine translation,

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.509492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a64fa16e-7fd8-4d99-a787-4ab276d03c32 · outbound

This paper cites Wikimedia downloads.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Wikimedia downloads

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.494694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 62d3bd97-868c-455c-a338-aedbb064983d · outbound

This paper cites dm-crypt,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels dm-crypt,

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.481189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2d34e499-0056-4836-9f7b-95298ea6d0ad · outbound

This paper cites Software protection and simulation on oblivious RAMs,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Software protection and simulation on oblivious RAMs,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.468699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 83b263c8-0007-4062-a7f4-1742cb452185 · outbound

This paper cites Raccoon: Closing digital side-channels through obfuscated execution,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Raccoon: Closing digital side-channels through obfuscated execution,

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.455512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 12254499-2815-4953-ad18-1719ecdee092 · outbound

This paper cites HOP: Hardware makes obfuscation practical,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels HOP: Hardware makes obfuscation practical,

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.442633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d1e40524-5c47-4a44-bcbb-c574ec274e29 · outbound

This paper cites FlexGen: high-throughput generative inference of large language models with a single GPU,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels FlexGen: high-throughput generative inference of large language models with a single GPU,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.428321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 80f3a6fa-43ff-44ea-afad-f8a9f2847927 · outbound

This paper cites InfiniGen: Efficient generative inference of large language models with dynamic KV cache manage- ment,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels InfiniGen: Efficient generative inference of large language models with dynamic KV cache manage- ment,

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.413552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3d1a0f03-aaa2-4e98-ba0e-91008b5efaa6 · outbound

This paper cites Improving throughput-oriented LLM inference with CPU computations,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Improving throughput-oriented LLM inference with CPU computations,

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.399034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 68de6935-94b4-4f5d-97f1-61bc9a8c29e6 · outbound

This paper cites DeepCache: Revisiting cache side-channel attacks in deep neural networks exe- cutables,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels DeepCache: Revisiting cache side-channel attacks in deep neural networks exe- cutables,

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.383853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9b503032-d680-49d8-ae41-fb22e00e5cab · outbound

This paper cites Phantom: Practical oblivious computation in a secure processor,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Phantom: Practical oblivious computation in a secure processor,

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.369053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 461f1ab4-99b2-4548-95f6-29a4453166b2 · outbound

This paper cites FLUSH+RELOAD: A high resolution, low noise, L3 cache side-channel attack,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels FLUSH+RELOAD: A high resolution, low noise, L3 cache side-channel attack,

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.354308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2c5e32fc-4a59-4918-9ae1-9d1f37a3df95 · outbound

This paper cites Flush+Flush: a fast and stealthy cache attack,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Flush+Flush: a fast and stealthy cache attack,

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.339352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0529289f-7362-4ce4-97a8-d8f28941d472 · outbound

This paper cites Activation functions considered harmful: Recovering neural network weights through controlled channels,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Activation functions considered harmful: Recovering neural network weights through controlled channels,

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.325052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4893246a-31ef-433c-836c-dc639ee409d8 · outbound

This paper cites Hy- perTheft: Thieving model weights from TEE-shielded neural networks via ciphertext side channels,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Hy- perTheft: Thieving model weights from TEE-shielded neural networks via ciphertext side channels,

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.310572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8cb8e342-b8b4-4d2d-b201-fde3b9ed8889 · outbound

This paper cites Reverse-engineering deep neural networks using floating-point timing side-channels,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Reverse-engineering deep neural networks using floating-point timing side-channels,

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.295792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 63514bc9-0b75-4cf1-9a03-ec0f2cda7925 · outbound

This paper cites Relocate-V ote: Using sparsity information to exploit ciphertext side- channels,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels Relocate-V ote: Using sparsity information to exploit ciphertext side- channels,

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.281551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0bc2f1d1-4098-4c58-a31b-0b9f854ec8c3 · outbound

This paper cites InputSnatch: Stealing Input in LLM Services via Timing Side-Channel Attacks.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels InputSnatch: Stealing Input in LLM Services via Timing Side-Channel Attacks

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-08T04:21:30.504440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b9ded1a-f7f7-4fde-aedb-ea44741c04cf · outbound

This paper cites MoEfication: Transformer feed-forward layers are mixtures of experts,.

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels MoEfication: Transformer feed-forward layers are mixtures of experts,

Reference 101

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:21:31.267284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers