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Paper Citation Record · LEDGER

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing

As of 6 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2512.11826.

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

pith.paper-citation-record.v1
2512.11826 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T19:06:09.743363Z

measured 41 of 41 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

41 of 41 outbound references displayed

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Outbound references

Observation a3dd591f-c079-4042-97c4-3ae8232e15ba · outbound

This paper cites A survey of on-device machine learning: An algorithms and learning theory perspective,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing A survey of on-device machine learning: An algorithms and learning theory perspective,

Reference 1

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Observation c3ac1636-5a82-4cba-849c-7cc6fe5a9e7d · outbound

This paper cites Df-lnpu: A pipelined direct feedback alignment-based deep neural network learning processor for fast online learning,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Df-lnpu: A pipelined direct feedback alignment-based deep neural network learning processor for fast online learning,

Reference 2

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source=pdf_text observed=2026-08-03T19:06:07.510205Z digest=sha256:49cca08bed91ac19f215428961cf3e7dc7184706fecdc82fcb760b47d6549650

Observation 21712cc3-6b3e-4c40-9e10-d2c2d0a0a0a5 · outbound

This paper cites A neural network training processor with 8-bit shared exponent bias floating point and multiple-way fused multiply-add trees,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing A neural network training processor with 8-bit shared exponent bias floating point and multiple-way fused multiply-add trees,

Reference 3

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Observation 48d4b583-5050-419a-86e5-05abb6177c77 · outbound

This paper cites CHIMERA: A 0.92-TOPS, 2.2-TOPS/W edge AI accelerator with 2-MByte on-chip foundry resistive RAM for efficient training and inference,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing CHIMERA: A 0.92-TOPS, 2.2-TOPS/W edge AI accelerator with 2-MByte on-chip foundry resistive RAM for efficient training and inference,

Reference 4

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Observation e8943a7d-5e57-4566-bce2-229e370270c8 · outbound

This paper cites Trainer: An energy-efficient edge-device training processor supporting dynamic weight pruning,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Trainer: An energy-efficient edge-device training processor supporting dynamic weight pruning,

Reference 5

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Observation 4ab7f6a3-5e8f-46c3-aa6d-626c1e2537a9 · outbound

This paper cites A 28-nm 8-bit floating- point tensor core-based programmable cnn training processor with dynamic structured sparsity,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing A 28-nm 8-bit floating- point tensor core-based programmable cnn training processor with dynamic structured sparsity,

Reference 6

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source=pdf_text observed=2026-08-03T19:06:07.798109Z digest=sha256:e8abdd2180ae7c210131bb8cd29e94d6aa27b6ff6b1f920ee250a324bb67006e

Observation c408ff1b-67b0-420b-920e-42e4ba9bf6aa · outbound

This paper cites A 4.69-TOPS/W Training, 2.34-µJ/Image Inference On-Chip Training Accelerator With Inference- Compatible Backpropagation and Design Space Exploration in 28-nm CMOS,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing A 4.69-TOPS/W Training, 2.34-µJ/Image Inference On-Chip Training Accelerator With Inference- Compatible Backpropagation and Design Space Exploration in 28-nm CMOS,

Reference 7

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source=pdf_text observed=2026-08-03T19:06:07.874968Z digest=sha256:f6ab00a0c4c48bafd8cf7e5b08b3bd0d64c0a0c09ec61329319e7cba1dc04a9b

Observation ab4c7ff4-660a-43da-82e7-c1d3ad3bde30 · outbound

This paper cites An overview of energy-efficient hardware accelerators for on-device deep-neural-network training,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing An overview of energy-efficient hardware accelerators for on-device deep-neural-network training,

Reference 8

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Observation 91735ea5-3731-47f2-9107-454a63a24f36 · outbound

This paper cites Sp-pim: A super- pipelined processing-in-memory accelerator with local error prediction for area/energy-efficient on-device learning,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Sp-pim: A super- pipelined processing-in-memory accelerator with local error prediction for area/energy-efficient on-device learning,

Reference 9

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Observation 5b22fb24-2b14-4001-8223-a92b9f74bacb · outbound

This paper cites Tinytl: Reduce memory, not parameters for efficient on-device learning,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Tinytl: Reduce memory, not parameters for efficient on-device learning,

Reference 10

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source=pdf_text observed=2026-08-03T19:06:08.050497Z digest=sha256:9222d906c7a816f1b9c7e9f3ecd62146509e2fa898d607921bd7755ec274b0ed

Observation 096c8102-1c00-4cc4-9703-f425bce8eedf · outbound

This paper cites T-pim: An energy- efficient processing-in-memory accelerator for end-to-end on-device training,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing T-pim: An energy- efficient processing-in-memory accelerator for end-to-end on-device training,

Reference 11

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Observation 9c66d7e0-bde1-40ba-8aab-504d4c464b82 · outbound

This paper cites Scicnn: A 0-shot-retraining patient-independent epilepsy-tracking soc,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Scicnn: A 0-shot-retraining patient-independent epilepsy-tracking soc,

Reference 12

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source=pdf_text observed=2026-08-03T19:06:08.166306Z digest=sha256:18296bb1a87cd7dfe42fb69b0ac8154050e418d477318c151a607cc9d3dfcfa9

Observation bcce2e15-2a43-4716-ab43-3b5f04b73a12 · outbound

This paper cites A high accuracy and ultra-energy-efficient zero- shot-retraining seizure detection processor,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing A high accuracy and ultra-energy-efficient zero- shot-retraining seizure detection processor,

Reference 13

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source=pdf_text observed=2026-08-03T19:06:08.258423Z digest=sha256:6939a4df3053881b8b7137503502528a6b0b2ad4b0d3c5837f0eebb341bdf763

Observation cc09c5b7-7efb-402d-affb-0e9cbd0f52ca · outbound

This paper cites Energy-efficient reconfigurable xgboost inference accelerator with modular unit trees via selective node execution and data movement,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Energy-efficient reconfigurable xgboost inference accelerator with modular unit trees via selective node execution and data movement,

Reference 14

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Observation d61202ca-3410-493d-99b2-374f7791c3f2 · outbound

This paper cites Hybrid slc-mlc rram mixed-signal processing-in-memory architecture for transformer acceleration via gradient redistribution,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Hybrid slc-mlc rram mixed-signal processing-in-memory architecture for transformer acceleration via gradient redistribution,

Reference 15

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Observation 70f97823-1122-487f-b1aa-247676c72e90 · outbound

This paper cites On- device learning systems for edge intelligence: A software and hardware synergy perspective,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing On- device learning systems for edge intelligence: A software and hardware synergy perspective,

Reference 16

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Observation 7738e5f0-9880-4385-8e3b-025ca028f416 · outbound

This paper cites Experimentally validated memristive memory augmented neural network with efficient hashing and similarity search,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Experimentally validated memristive memory augmented neural network with efficient hashing and similarity search,

Reference 17

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Observation 386084c8-f9b2-464c-8585-f88e62a79e04 · outbound

This paper cites Sapiens: A 64-kb rram-based non-volatile associative memory for one-shot learning and inference at the edge,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Sapiens: A 64-kb rram-based non-volatile associative memory for one-shot learning and inference at the edge,

Reference 18

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Observation 1f4ae94d-2628-436b-9cda-630781764707 · outbound

This paper cites In-memory realization of in-situ few-shot continual learning with a dynamically evolving explicit memory,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing In-memory realization of in-situ few-shot continual learning with a dynamically evolving explicit memory,

Reference 19

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Observation f924e68e-b24f-4797-8b19-6629106f4596 · outbound

This paper cites Understanding of object detection based on cnn family and yolo,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Understanding of object detection based on cnn family and yolo,

Reference 20

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Observation 9134fafa-3221-4207-bc1a-9485b8499305 · outbound

This paper cites Optimization as a model for few-shot learning,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Optimization as a model for few-shot learning,

Reference 21

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Observation b73dc6f2-da7c-4b5f-a210-3a80035863e0 · outbound

This paper cites Hyperdimensional computing: An introduction to computing in distributed representation with high-dimensional random vectors,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Hyperdimensional computing: An introduction to computing in distributed representation with high-dimensional random vectors,

Reference 22

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Observation 511a1213-38a9-4d8e-ba74-3826e5e73fdd · outbound

This paper cites A theoretical perspective on hyperdimensional computing,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing A theoretical perspective on hyperdimensional computing,

Reference 23

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source=pdf_text observed=2026-08-03T19:06:08.982910Z digest=sha256:fe625606c10a14ed48baef135ffa8b295dbd65206666cef3a53593c5d2567143

Observation 5d8222f0-ff4f-4c59-868c-92252f62a211 · outbound

This paper cites Fsl-hdnn: A 5.7 tops/w end-to- end few-shot learning classifier accelerator with feature extraction and hyperdimensional computing,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Fsl-hdnn: A 5.7 tops/w end-to- end few-shot learning classifier accelerator with feature extraction and hyperdimensional computing,

Reference 24

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Observation 2dabcce1-8e53-4640-b0ed-fdb554422e86 · outbound

This paper cites Meta-transfer learning for few-shot learning,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Meta-transfer learning for few-shot learning,

Reference 25

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Observation 657eb3bc-93c5-448c-acc2-f6e691f0c582 · outbound

This paper cites Rethinking few-shot image classification: A good embedding is all you need?,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Rethinking few-shot image classification: A good embedding is all you need?,

Reference 26

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source=pdf_text observed=2026-08-03T19:06:09.198792Z digest=sha256:3b1f72e4d5ef892293a170acbbd75d6d8c23aa0869438f9d34e84a3d941f37b4

Observation 2c53dbeb-0d8f-4016-b3d7-9583ac6c0bbd · outbound

This paper cites Few-shot image classification: Just use a library of pre-trained feature extractors and a simple classifier,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Few-shot image classification: Just use a library of pre-trained feature extractors and a simple classifier,

Reference 27

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Observation 400edaa0-c532-4e79-a2c4-c1b953a6bfbc · outbound

This paper cites Patternet: explore and exploit filter patterns for efficient deep neural networks,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Patternet: explore and exploit filter patterns for efficient deep neural networks,

Reference 28

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Observation 7392078e-22b8-4407-bd76-379891dfdd5f · outbound

This paper cites Deep residual learning for image recognition,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Deep residual learning for image recognition,

Reference 29

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Observation f3659d98-5a16-489e-b5f0-780fd76f847e · outbound

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

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Learning multiple layers of features from tiny images,

Reference 30

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Observation 6572507a-eeeb-4d2f-b53f-1bcd2d62a740 · outbound

This paper cites Locality-based encoder and model quantization for efficient hyper- dimensional computing,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Locality-based encoder and model quantization for efficient hyper- dimensional computing,

Reference 31

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Observation a61aacd5-0831-4516-9715-02d8966d756b · outbound

This paper cites Study and analysis of various lfsr architectures,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Study and analysis of various lfsr architectures,

Reference 32

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Observation 9f5f9362-ee0f-4087-9e7c-fd2664388ae5 · outbound

This paper cites Branchynet: Fast inference via early exiting from deep neural networks,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Branchynet: Fast inference via early exiting from deep neural networks,

Reference 33

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source=pdf_text observed=2026-08-03T19:06:09.415023Z digest=sha256:6dd226c87462461b2d5c6d7605f5c768386b7ee62ae2b9a8bc8b9d7525d3ea86

Observation abc26422-a97a-4233-a060-39eedde16ca2 · outbound

This paper cites Locoexnet: Low-cost early exit network for energy efficient cnn accelerator design,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Locoexnet: Low-cost early exit network for energy efficient cnn accelerator design,

Reference 34

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Observation 23d2fc4a-44d8-4da8-8485-87cb89aed6b5 · outbound

This paper cites Early-exit deep neural network-a comprehensive survey,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Early-exit deep neural network-a comprehensive survey,

Reference 35

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Observation 29ec8857-a01d-41d2-a80f-48a26c90ed4d · outbound

This paper cites Adaptive deep neural network inference optimization with eenet,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Adaptive deep neural network inference optimization with eenet,

Reference 36

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Observation c43c6342-24ab-4f42-8746-25c181d36101 · outbound

This paper cites Tadam: Task dependent adaptive metric for improved few-shot learning,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Tadam: Task dependent adaptive metric for improved few-shot learning,

Reference 37

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Observation 9a64b7df-40d4-43c8-ad35-c1349c27dfc7 · outbound

This paper cites Automated flower classification over a large number of classes,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Automated flower classification over a large number of classes,

Reference 38

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Observation 1084d84c-3786-4f52-bb40-e1015fdff0fa · outbound

This paper cites Detection of traffic signs in real-world images: The german traffic sign detection 10 benchmark,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Detection of traffic signs in real-world images: The german traffic sign detection 10 benchmark,

Reference 39

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Observation 55eb8522-3fcf-483e-b254-09932fa0b960 · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Imagenet: A large-scale hierarchical image database,

Reference 40

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Observation e2002b8e-e870-41e2-af57-e34d52bbbb65 · outbound

This paper cites Deepscaletool: A tool for the accurate estimation of technology scaling in the deep-submicron era,.

FSL-HDnn: A 40 nm Few-shot On-Device Learning Accelerator with Integrated Feature Extraction and Hyperdimensional Computing Deepscaletool: A tool for the accurate estimation of technology scaling in the deep-submicron era,

Reference 41

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