Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations | Paper Citation Record

Observation 068ef811-52b6-40fc-b4a9-fa0082f8014f · outbound

This paper cites LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

Reference 1

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This paper cites Passivity and.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Passivity and

Reference 2

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This paper cites Andrew G.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Andrew G

Reference 3

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This paper cites Efficient processing of deep neural networks: A tutorial and survey.Proceedings of the IEEE, 105(12):2295–2329.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Efficient processing of deep neural networks: A tutorial and survey.Proceedings of the IEEE, 105(12):2295–2329

Reference 4

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This paper cites Neural record- ing and stimulation using wireless networks of microimplants.Nature Electronics, 4(8): 604–614.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Neural record- ing and stimulation using wireless networks of microimplants.Nature Electronics, 4(8): 604–614

Reference 5

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This paper cites Neural Dust: An Ultrasonic, Low Power Solution for Chronic Brain-Machine Interfaces.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Neural Dust: An Ultrasonic, Low Power Solution for Chronic Brain-Machine Interfaces

Reference 6

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This paper cites An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG.Nature Communications, 12(1):3095.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG.Nature Communications, 12(1):3095

Reference 7

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Observation 56a676ef-e49c-4115-97a9-c7b9eccd3946 · outbound

This paper cites Analog Versus Digital: Extrapolating from Electronics to Neurobiology.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Analog Versus Digital: Extrapolating from Electronics to Neurobiology

Reference 8

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This paper cites Memory devices and applications for in-memory computing.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Memory devices and applications for in-memory computing

Reference 9

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correction dated 2020-07-16. Source: crossref record 10.1038/s41565-020-0756-8->10.1038/s41565-020-0655-z:correction, observed 2026-07-11T02:58:13.774019+00:00. This notice travels one citation hop only.

Observation dbe19ee9-8482-466c-ab52-f63201c2a3e6 · outbound

This paper cites In-Memory Computing with Resistive Switching Devices.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations In-Memory Computing with Resistive Switching Devices

Reference 10

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This paper cites Attention is all you need.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Attention is all you need

Reference 11

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Observation edb36e2f-4cf8-4f2d-8846-7b1d1da95762 · outbound

This paper cites The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures

Reference 12

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Observation 4f0cb5f7-b6c5-4632-afd5-4c22b24ee9b4 · outbound

This paper cites Efficient transformers: A survey.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Efficient transformers: A survey

Reference 13

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Observation f46d7ae7-1f2d-46ba-a010-bb4b14c3f650 · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Efficiently Modeling Long Sequences with Structured State Spaces

Reference 14

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Observation 4913eed1-5382-4fc2-8b87-47dfbb71904a · outbound

This paper cites Mamba: Linear-time sequence modeling with selective state spaces.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Mamba: Linear-time sequence modeling with selective state spaces

Reference 15

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Observation dba4a181-e149-46c7-9d6e-d1938642f344 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 16

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This paper cites Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Reference 17

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Observation f7314b6f-69d1-4585-a98a-554cb3b590f5 · outbound

This paper cites Linear recurrent units for sequential recommendation.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Linear recurrent units for sequential recommendation

Reference 18

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This paper cites CausalMMM: Learning Causal Structure for Marketing Mix Modeling , url=.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations CausalMMM: Learning Causal Structure for Marketing Mix Modeling , url=

Reference 19

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Observation e03657c8-be2d-4fcc-8eba-96c9101c145d · outbound

This paper cites The Mamba in the Llama: Distilling and accelerating hybrid models.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations The Mamba in the Llama: Distilling and accelerating hybrid models

Reference 20

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Observation eb2e5a54-bcb5-4076-b50f-aa69b9cc0af4 · outbound

This paper cites On the parameterization and initialization of diagonal state space models.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations On the parameterization and initialization of diagonal state space models

Reference 21

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Observation 197ccdaf-9979-46c4-b0fe-fc43b61e2408 · outbound

This paper cites Fading memory and the problem of approximating nonlinear operators with Volterra series.IEEE Transactions on Circuits and Systems, 32(11):1150–1161.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Fading memory and the problem of approximating nonlinear operators with Volterra series.IEEE Transactions on Circuits and Systems, 32(11):1150–1161

Reference 22

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This paper cites an unresolved cited work.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Unresolved cited work

Reference 23

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Observation d55a5906-ea3a-4389-8343-e1b1e1fbf5b0 · outbound

This paper cites Chari and L.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Chari and L

Reference 24

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Observation 5359725d-8314-4029-9ef1-ed2f0cabb035 · outbound

This paper cites Warming up recurrent neural networks to maximise reachable multistability greatly improves learning.Neural Networks, 166:645–669.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Warming up recurrent neural networks to maximise reachable multistability greatly improves learning.Neural Networks, 166:645–669

Reference 25

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Observation 4f86494e-7e82-4112-a6d0-ce21b40f2427 · outbound

This paper cites Memory from the dynamics of intrinsic membrane currents.Proceedings of the National Academy of Sciences, 93(24):13481–13486.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Memory from the dynamics of intrinsic membrane currents.Proceedings of the National Academy of Sciences, 93(24):13481–13486

Reference 26

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Observation b58690fa-244e-4568-979e-86d3dcf58b4e · outbound

This paper cites Long short -term memory.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Long short -term memory

Reference 27

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Observation ff60ff39-9e59-4f00-ba2b-8a96e8f86127 · outbound

This paper cites Learning phrase representations using RNN encoder- decoder for statistical machine translation.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Learning phrase representations using RNN encoder- decoder for statistical machine translation

Reference 28

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Observation 13ef215c-8d9c-40e9-9626-faaf3d8c4e19 · outbound

This paper cites Learning long-term dependencies with gradient descent is difficult.IEEE Transactions on Neural Networks, 5(2):157–166.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Learning long-term dependencies with gradient descent is difficult.IEEE Transactions on Neural Networks, 5(2):157–166

Reference 29

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.087063Z

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Observation f586a840-4d76-4173-bf20-58323a4efcb4 · outbound

This paper cites On the difficulty of training recurrent neural networks.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations On the difficulty of training recurrent neural networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.742863Z

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Observation 05398f1b-a193-49f4-83e1-ec721500b70e · outbound

This paper cites Review of ASIC accelerators for deep neural network.Microprocessors and Microsystems, 89:104441.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Review of ASIC accelerators for deep neural network.Microprocessors and Microsystems, 89:104441

Reference 31

Resolution: malformed identifier; doi_truncated, observed 2026-06-30T22:25:06.081432Z

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Observation a1e779c5-c14a-406c-a7a5-35285d362ff2 · outbound

This paper cites Eyeriss v2: A flexible accelerator for emerging deep neural networks on mobile devices.IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 9(2):292–308.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Eyeriss v2: A flexible accelerator for emerging deep neural networks on mobile devices.IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 9(2):292–308

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:25:06.115882Z

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Observation 9ac0f50a-6dbf-4b12-b00a-cd976dbb1717 · outbound

This paper cites Tiny machine learning and on-device inference: A survey of applications, challenges, and future directions.Sensors, 25(10):3191.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Tiny machine learning and on-device inference: A survey of applications, challenges, and future directions.Sensors, 25(10):3191

Reference 33

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Observation ff70bbb9-4f2d-4ba2-b20d-e173899b1c71 · outbound

This paper cites MLPerf Tiny Benchmark.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations MLPerf Tiny Benchmark

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:05:46.340205Z

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Observation ce49e56d-2dae-49ab-86ee-1f8b3afe0e4e · outbound

This paper cites O’Reilly Media.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations O’Reilly Media

Reference 35

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Observation ad6b560c-6be7-4966-80b6-aaa2b9a50488 · outbound

This paper cites MCUNet: Tiny deep learning on IoT devices.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations MCUNet: Tiny deep learning on IoT devices

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.777942Z

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Observation 2cadeb7d-f1a7-45d7-af38-7a7b750d0d98 · outbound

This paper cites SpArSe: Sparse architecture search for CNNs on resource-constrained microcontrollers.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations SpArSe: Sparse architecture search for CNNs on resource-constrained microcontrollers

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.763797Z

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Observation 626148c6-a7b7-43d2-a832-2dfe89b8f354 · outbound

This paper cites Real-time computing without stable states: A new framework for neural computation based on perturbations.Neural Computation, 14(11):2531–2560.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Real-time computing without stable states: A new framework for neural computation based on perturbations.Neural Computation, 14(11):2531–2560

Reference 38

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.131585Z

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Observation df9e9953-9abd-46fb-b27f-2332f5f563a9 · outbound

This paper cites Loihi: A neuromorphic manycore processor with on-chip learning.IEEE Micro, 38(1):82–99.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Loihi: A neuromorphic manycore processor with on-chip learning.IEEE Micro, 38(1):82–99

Reference 39

Resolution: malformed identifier; arxiv_id, observed 2026-07-01T14:05:46.423649Z

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Observation 4c7dbc6b-6b53-4a85-b8a4-58f21e22f34d · outbound

This paper cites 2021 , journal =.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations 2021 , journal =

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T22:25:06.068430Z

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Observation b4856810-6e3c-4ce1-89d0-7271127f27f7 · outbound

This paper cites Neuromorphic electronic systems.Proceedings of the IEEE, 78(10):1629–1636.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Neuromorphic electronic systems.Proceedings of the IEEE, 78(10):1629–1636

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.764974Z

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Observation 6be5a423-9d43-4734-ab8c-8b16766cfa8f · outbound

This paper cites Neuromorphic electronic systems.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Neuromorphic electronic systems

Reference 42

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.054669Z

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Observation 92a90db8-5a25-4202-a816-9919ca58ffb3 · outbound

This paper cites Memristive crossbar arrays for brain-inspired computing.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Memristive crossbar arrays for brain-inspired computing

Reference 43

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.099718Z

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correction dated 2019-04-02. Source: crossref record 10.1038/s41563-019-0357-9->10.1038/s41563-019-0291-x:correction, observed 2026-07-11T02:56:55.487397+00:00. This notice travels one citation hop only.

Observation bf1dbedd-6288-4d4d-96f0-0385e2f18d1b · outbound

This paper cites Training and operation of an integrated neuromorphic network based on metal-oxide memristors.Nature, 521(7550):61–64.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Training and operation of an integrated neuromorphic network based on metal-oxide memristors.Nature, 521(7550):61–64

Reference 44

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.107974Z

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Observation cdc7fdcc-e5e7-4935-a47f-356684b07c10 · outbound

This paper cites Hardware implementation of deep network accelerators towards healthcare and biomedical applications.IEEE Transactions on Biomedical Circuits and Systems, 14(6):1138–1159.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Hardware implementation of deep network accelerators towards healthcare and biomedical applications.IEEE Transactions on Biomedical Circuits and Systems, 14(6):1138–1159

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:25:06.045384Z

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Observation 1075db93-0f18-49f3-ab3b-0c13d9dfcb96 · outbound

This paper cites Long short-term memory networks in memristor crossbar arrays.Nature Machine Intelligence, 1(1):49–57.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Long short-term memory networks in memristor crossbar arrays.Nature Machine Intelligence, 1(1):49–57

Reference 46

Resolution: malformed identifier; raw_fallback, observed 2026-07-07T14:13:48.783665Z

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Observation 45f7e1a8-decb-4bca-99c8-c0a49a90f383 · outbound

This paper cites A review of computing with spiking neural networks.Computers, Materials & Continua, 78(3):2909.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations A review of computing with spiking neural networks.Computers, Materials & Continua, 78(3):2909

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:25:06.151988Z

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Observation da77f1ab-b194-428e-ac2d-aec35ec37b5f · outbound

This paper cites Towards spike-based machine intelligence with neuromorphic computing.Nature, 575(7784):607–617.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Towards spike-based machine intelligence with neuromorphic computing.Nature, 575(7784):607–617

Reference 48

Resolution: malformed identifier; raw_fallback, observed 2026-07-07T14:13:48.781626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 47ebb289-9a4e-495b-a2df-27c755cd6903 · outbound

This paper cites Frontiers in Neuroscience16 (2022).

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Frontiers in Neuroscience16 (2022)

Reference 49

Resolution: malformed identifier; doi_truncated, observed 2026-06-30T22:25:06.105961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0bb72395-a0ec-402c-b44d-45df6c5ff8a6 · outbound

This paper cites Opportunities for neuromorphic computing algorithms and applications.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Opportunities for neuromorphic computing algorithms and applications

Reference 50

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.110120Z

Source-reported events for the cited work

correction dated 2022-03-11. Source: crossref record 10.1038/s43588-022-00223-2->10.1038/s43588-021-00184-y:correction, observed 2026-07-11T02:56:26.326139+00:00. This notice travels one citation hop only.

Observation 557845f1-4746-417e-907b-e51eeb884d94 · outbound

This paper cites Recurrent Neural Networks Hardware Implementation on FPGA.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Recurrent Neural Networks Hardware Implementation on FPGA

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:05:46.417360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4e31d65e-1cf6-4aa0-951e-9c1ca713581f · outbound

This paper cites Noise-mitigation strategies in physical feedforward neural networks.Chaos: An Interdisciplinary Journal of Nonlinear Science, 32(6):061106.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Noise-mitigation strategies in physical feedforward neural networks.Chaos: An Interdisciplinary Journal of Nonlinear Science, 32(6):061106

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.772673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5c541583-6aec-478c-9a6e-ea9a62290944 · outbound

This paper cites an unresolved cited work.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Unresolved cited work

Reference 53

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.156883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7a07c1b0-6e5c-49da-823e-711dd5584840 · outbound

This paper cites Training End-to-End Analog Neural Networks with Equilibrium Propagation.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Training End-to-End Analog Neural Networks with Equilibrium Propagation

Reference 54

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T14:05:46.397388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fb001b06-434a-434c-9719-131aff4f1d8e · outbound

This paper cites MIT press.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations MIT press

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.760193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 78ac3f01-c910-4271-b5d9-2c52539abf5b · outbound

This paper cites AML100 - near-zero power analogml processor.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations AML100 - near-zero power analogml processor

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.794484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 70c9e5a5-1d51-477f-80ab-6ae8257a7583 · outbound

This paper cites NDP120 neural decision processor.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations NDP120 neural decision processor

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.753467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0d0d1611-62ba-43c3-949d-8587a8a1ebac · outbound

This paper cites Parallelizable memory recurrent units.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Parallelizable memory recurrent units

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:05:46.358272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 09512f1e-0e9b-4b51-a275-277cf0bcf856 · outbound

This paper cites ParaRNN: Unlocking parallel training of nonlinear RNNs for large language models.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations ParaRNN: Unlocking parallel training of nonlinear RNNs for large language models

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:05:46.361577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 26c25480-51e3-4532-8819-b2750ced36fc · outbound

This paper cites Parallelizing linear recurrent neural nets over sequence length.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Parallelizing linear recurrent neural nets over sequence length

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.772901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ea3cd35c-7d6a-40bf-90d0-b75f17d03fec · outbound

This paper cites Parallelizing Linear Recurrent Neural Nets Over Sequence Length.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Parallelizing Linear Recurrent Neural Nets Over Sequence Length

Reference 61

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:05:46.350670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b5025455-8ffb-4164-9a3c-4863384500be · outbound

This paper cites Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition

Reference 62

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:05:46.348401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ddfce801-466d-41a2-b8d3-3d518e7f532a · outbound

This paper cites Resurrecting Recurrent Neural Networks for Long Sequences.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Resurrecting Recurrent Neural Networks for Long Sequences

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:05:46.354431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation edef7844-89c2-4240-b99e-30fe384a7bb9 · outbound

This paper cites Were RNNs All We Needed?.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Were RNNs All We Needed?

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:05:46.364707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0a36af8b-7006-41a8-88b2-65759948ef48 · outbound

This paper cites On the Importance of Multistability for Horizon Generalization in Reinforcement Learning.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations On the Importance of Multistability for Horizon Generalization in Reinforcement Learning

Reference 65

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:05:46.370900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 76f8b1bc-7aa3-493c-a62f-74f70d5c727d · outbound

This paper cites Matching properties of MOS transistors.IEEE Journal of Solid-State Circuits, 24(5):1433–1439.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Matching properties of MOS transistors.IEEE Journal of Solid-State Circuits, 24(5):1433–1439

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:25:06.062910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b62d2bec-b89c-479a-b17c-7b2e1cf43af8 · outbound

This paper cites Device mismatch and tradeoffs in the design of analog circuits.IEEE Journal of Solid-State Circuits, 40(6):1212–1224.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Device mismatch and tradeoffs in the design of analog circuits.IEEE Journal of Solid-State Circuits, 40(6):1212–1224

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:25:06.121924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7b80375d-53fb-4424-a3ad-06aa36797ea0 · outbound

This paper cites Silicon diode temperature sensors—a review of applications.Sensors and Actuators A: Physical, 232:63–74.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Silicon diode temperature sensors—a review of applications.Sensors and Actuators A: Physical, 232:63–74

Reference 68

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.127998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9a802876-8172-472c-ba0f-8ce3ab368529 · outbound

This paper cites Long Range Arena: A Benchmark for Efficient Transformers.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Long Range Arena: A Benchmark for Efficient Transformers

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:05:46.377874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2b3a7574-2d0d-4765-90b9-3603ab479383 · outbound

This paper cites nanoGPT.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations nanoGPT

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.766915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cf107893-1a3e-4120-a076-e5c220cb1207 · outbound

This paper cites IEEE Access8, 199523–199538 (2020) https://doi.org/10.1109/ACCESS.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations IEEE Access8, 199523–199538 (2020) https://doi.org/10.1109/ACCESS

Reference 71

Resolution: malformed identifier; doi_truncated, observed 2026-06-30T22:25:06.036478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c9d59ce2-ac93-4369-84ce-3038009867c7 · outbound

This paper cites Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups.IEEE Signal Processing Magazine, 29(6):82–97.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups.IEEE Signal Processing Magazine, 29(6):82–97

Reference 72

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.125095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 03d1233a-e22e-44ce-bf32-0599baa99420 · outbound

This paper cites Small-footprint keyword spotting using deep neural networks.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Small-footprint keyword spotting using deep neural networks

Reference 73

Resolution: malformed identifier; doi_truncated, observed 2026-06-30T22:25:06.057015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f34b8478-32d4-4792-91d6-dd0c35c8c1a8 · outbound

This paper cites Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting

Reference 74

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:05:46.386076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b1ef004c-a7b0-4fd0-b515-5052b4138ea4 · outbound

This paper cites Alain de Cheveigné and Hideki Kawahara.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Alain de Cheveigné and Hideki Kawahara

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:25:06.097440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a9f0ec0c-ddcd-4e0e-a885-45cb40bdcc62 · outbound

This paper cites An 800 nW switched-capacitor feature extraction filterbank for sound classification.IEEE Transactions on Circuits and Systems I: Regular Papers, 68(4):1578–1588.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations An 800 nW switched-capacitor feature extraction filterbank for sound classification.IEEE Transactions on Circuits and Systems I: Regular Papers, 68(4):1578–1588

Reference 76

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T14:05:46.396273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c676b654-0630-49ea-8832-591496847cf9 · outbound

This paper cites an unresolved cited work.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Unresolved cited work

Reference 77

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:25:06.049336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1512c285-2e78-4d89-8501-ec212d118b86 · outbound

This paper cites Cadence Virtuoso Platform.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Cadence Virtuoso Platform

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.747169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c9fcdaf2-d1f0-4bf1-94e1-b59da2c98252 · outbound

This paper cites Oxford University Press, 3rd edition.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Oxford University Press, 3rd edition

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.774396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a11abce4-45db-4156-acd8-feebdb490422 · outbound

This paper cites McGraw-Hill.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations McGraw-Hill

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.730679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8839d302-7275-4f62-a462-ec4558583f0a · outbound

This paper cites The missing memristor found.Nature, 453(7191):80–83.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations The missing memristor found.Nature, 453(7191):80–83

Reference 81

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.103808Z

Source-reported events for the cited work

correction dated 2009-06-24. Source: crossref record 10.1038/nature08166->10.1038/nature06932:correction, observed 2026-07-11T03:18:14.065577+00:00. This notice travels one citation hop only.

Observation 2d332080-1db4-4457-9ada-995c658e6d4a · outbound

This paper cites Pattern classification by memristive crossbar circuits using ex situ and in situ training.Nature Communications, 4:2072.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Pattern classification by memristive crossbar circuits using ex situ and in situ training.Nature Communications, 4:2072

Reference 82

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.075610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c48b116a-dc1e-4218-bff2-29c3ac447305 · outbound

This paper cites A survey of quantization methods for efficient neural network inference.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations A survey of quantization methods for efficient neural network inference

Reference 83

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.146613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4865df16-9d75-489b-b15d-f89b2c69085c · outbound

This paper cites BinaryConnect: Training deep neural networks with binary weights during propagations.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations BinaryConnect: Training deep neural networks with binary weights during propagations

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.779723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e09bf5f6-cc08-426f-b25b-18ab3371648c · outbound

This paper cites Bina- rized neural networks.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Bina- rized neural networks

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.776397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5a69e090-51cc-4aa4-9f18-2c5e2aff84db · outbound

This paper cites Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets

Reference 86

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:05:46.390748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6f887867-14d7-4534-9925-7d061fc20ecf · outbound

This paper cites Hello Edge: Keyword Spotting on Microcontrollers.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Hello Edge: Keyword Spotting on Microcontrollers

Reference 87

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:05:46.394542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3860ac67-fdff-4188-b642-f9dae3df6eb1 · outbound

This paper cites A Fast Network Exploration Strategy to Profile Low Energy Consumption for Keyword Spotting.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations A Fast Network Exploration Strategy to Profile Low Energy Consumption for Keyword Spotting

Reference 88

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:05:46.405968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4299d4d6-f8ae-4221-95f7-71319c9b1732 · outbound

This paper cites Surrogate gradient learning in spiking neural networks.IEEE Signal Processing Magazine, 36(6):51–63.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Surrogate gradient learning in spiking neural networks.IEEE Signal Processing Magazine, 36(6):51–63

Reference 89

Resolution: malformed identifier; arxiv_id, observed 2026-07-01T14:05:46.426989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cccdb194-559a-447b-b728-e7450c14ca13 · outbound

This paper cites Recent advances in stochastic gradient descent in deep learning.Mathematics, 11(3):682.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Recent advances in stochastic gradient descent in deep learning.Mathematics, 11(3):682

Reference 90

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.065290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4daa0ceb-e6a1-4a8f-b7d5-db02b6798f82 · outbound

This paper cites Robust subthreshold logic for ultra-low power operation.IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 9(1):90–99.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Robust subthreshold logic for ultra-low power operation.IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 9(1):90–99

Reference 91

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.148738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8203aae2-14fc-4a43-8b52-ccf10d3c6dc3 · outbound

This paper cites 2005.864128.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations 2005.864128

Reference 92

Resolution: malformed identifier; doi_truncated, observed 2026-06-30T22:25:06.093466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f74966b7-7441-40d5-ac44-2ec56c151bc6 · outbound

This paper cites Addison-Wesley.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Addison-Wesley

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T14:13:48.785266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 86614126-ed9e-477c-ad72-faac7a00a6f2 · outbound

This paper cites CMOS Schmitt trigger design.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations CMOS Schmitt trigger design

Reference 94

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.079074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fc1b0c99-5de4-46a8-ad59-3bbc96c187f5 · outbound

This paper cites an unresolved cited work.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Unresolved cited work

Reference 95

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.144391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 863e2b60-59eb-4501-8901-072b03b58ca2 · outbound

This paper cites Hardware-software co-design of embedded systems.Proceedings of the IEEE, 82(7):967–989.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Hardware-software co-design of embedded systems.Proceedings of the IEEE, 82(7):967–989

Reference 96

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.071083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 64b67a21-972c-4888-ada2-630ba3195f5f · outbound

This paper cites Gradient-based learning applied to document recognition.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Gradient-based learning applied to document recognition

Reference 97

Resolution: verified exact; doi, observed 2026-06-30T22:25:06.159217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c07b18e1-c196-4365-a5f3-15f6d0920e80 · outbound

This paper cites an unresolved cited work.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Unresolved cited work

Reference 98

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Observation 2c33e206-5078-4268-9613-9810256df8a2 · outbound

This paper cites ListOps: A Diagnostic Dataset for Latent Tree Learning.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations ListOps: A Diagnostic Dataset for Latent Tree Learning

Reference 99

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:05:46.382723Z

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Observation 9acf718b-4203-42d2-9580-f709b7efc106 · outbound

This paper cites and McVicar, Matt and Battenberg, Eric and Nieto, Oriol , title =.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations and McVicar, Matt and Battenberg, Eric and Nieto, Oriol , title =

Reference 100

Resolution: metadata mismatch; doi, observed 2026-06-30T22:25:06.118252Z

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