Paper Citation Record · LEDGER

Quantizing Small-Scale State-Space Models for Edge AI

As of 7 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2506.12480.

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

pith.paper-citation-record.v1
2506.12480 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:54:51.842031Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

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

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:16:26.511282Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T19:16:26.738231Z

Reference resolution

29 of 29 outbound references displayed

verified exact2
verified fuzzy10
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fa06cd9d-d988-4b8e-b658-39fdb9d39c11 · outbound

This paper cites Hippo: Recurrent memory with optimal polynomial projections,.

Quantizing Small-Scale State-Space Models for Edge AI Hippo: Recurrent memory with optimal polynomial projections,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.693978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d0c18a7-0df3-4602-bb59-5cbe0b57f5a0 · outbound

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

Quantizing Small-Scale State-Space Models for Edge AI Efficiently Modeling Long Sequences with Structured State Spaces

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.699865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b17d758-defb-4923-b6e9-988d5e817406 · outbound

This paper cites Combining recurrent, convolutional, and continuous-time models with linear state space layers,.

Quantizing Small-Scale State-Space Models for Edge AI Combining recurrent, convolutional, and continuous-time models with linear state space layers,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.705368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d2d9f97-44de-48bb-834e-45fc45888192 · outbound

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

Quantizing Small-Scale State-Space Models for Edge AI On the parameterization and initialization of diagonal state space models,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:54:52.565587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ed49f1ab-a8a2-479c-b36c-3bf700b1cb8b · outbound

This paper cites Scalable event-by-event processing of neuromorphic sensory signals with deep state-space models,.

Quantizing Small-Scale State-Space Models for Edge AI Scalable event-by-event processing of neuromorphic sensory signals with deep state-space models,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:54:52.543931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2c873794-0ec1-4028-bd87-382b9bee5561 · outbound

This paper cites Exploring the Capability of Mamba in Speech Applications.

Quantizing Small-Scale State-Space Models for Edge AI Exploring the Capability of Mamba in Speech Applications

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.720742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f25c650-e206-41fe-b861-fc46de369581 · outbound

This paper cites Spiking structured state space model for monaural speech enhancement,.

Quantizing Small-Scale State-Space Models for Edge AI Spiking structured state space model for monaural speech enhancement,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:54:52.525127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a43c2f66-ef73-4836-9efe-dd675902c3ac · outbound

This paper cites EEG-SSM: Leveraging State-Space Model for Dementia Detection.

Quantizing Small-Scale State-Space Models for Edge AI EEG-SSM: Leveraging State-Space Model for Dementia Detection

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.731803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6dc916c7-50f8-43be-9a77-7872390b2d2a · outbound

This paper cites Harmamba: Effi- cient wearable sensor human activity recognition based on bidirectional selective ssm,.

Quantizing Small-Scale State-Space Models for Edge AI Harmamba: Effi- cient wearable sensor human activity recognition based on bidirectional selective ssm,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:54:52.505456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 025b60ee-f22d-4d8e-951d-b6adeaeee0c9 · outbound

This paper cites Optimis- ing tinyml with quantization and distillation of transformer and mamba models for indoor localisation on edge devices,.

Quantizing Small-Scale State-Space Models for Edge AI Optimis- ing tinyml with quantization and distillation of transformer and mamba models for indoor localisation on edge devices,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:54:52.486932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 980283df-2171-4839-9107-60c1f6986c66 · outbound

This paper cites Learning long sequences in spiking neural networks,.

Quantizing Small-Scale State-Space Models for Edge AI Learning long sequences in spiking neural networks,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.747420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be38abeb-abef-43b5-9430-0c7cfadd7053 · outbound

This paper cites Zero-shot temporal resolution domain adaptation for spiking neural networks,.

Quantizing Small-Scale State-Space Models for Edge AI Zero-shot temporal resolution domain adaptation for spiking neural networks,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.752659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb65a649-b50e-48f4-869a-aaab61050ee7 · outbound

This paper cites Quantization-Guided Training for Compact TinyML Models.

Quantizing Small-Scale State-Space Models for Edge AI Quantization-Guided Training for Compact TinyML Models

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:54:52.153291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4266aea4-5675-4bc6-9098-858a1d06f4ca · outbound

This paper cites Quantization and deployment of deep neural networks on microcontrollers,.

Quantizing Small-Scale State-Space Models for Edge AI Quantization and deployment of deep neural networks on microcontrollers,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:54:52.451616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2f302308-1508-417e-b3e6-2adb145af8d3 · outbound

This paper cites Quantization and training of neural networks for efficient integer-arithmetic-only inference,.

Quantizing Small-Scale State-Space Models for Edge AI Quantization and training of neural networks for efficient integer-arithmetic-only inference,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:54:52.432747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3273b9df-f2de-4f93-af79-1723fac99cd5 · outbound

This paper cites Q-S5: Towards Quantized State Space Models.

Quantizing Small-Scale State-Space Models for Edge AI Q-S5: Towards Quantized State Space Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.771442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f9dc540-850d-4776-9e5c-fda8eb03a6e2 · outbound

This paper cites Quamba: A Post-Training Quantization Recipe for Selective State Space Models.

Quantizing Small-Scale State-Space Models for Edge AI Quamba: A Post-Training Quantization Recipe for Selective State Space Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.776424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e7adc99-1ee2-4e1a-bfa9-18512458ba7a · outbound

This paper cites QMamba: Post-Training Quantization for Vision State Space Models.

Quantizing Small-Scale State-Space Models for Edge AI QMamba: Post-Training Quantization for Vision State Space Models

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:54:52.072991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 32b9c147-d553-493d-be7f-d9d153f8bcac · outbound

This paper cites Mamba-PTQ: Outlier Channels in Recurrent Large Language Models.

Quantizing Small-Scale State-Space Models for Edge AI Mamba-PTQ: Outlier Channels in Recurrent Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.786877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12a3829c-7622-4ccc-aea5-504d1b2d8590 · outbound

This paper cites A Diagonal Structured State Space Model on Loihi 2 for Efficient Streaming Sequence Processing.

Quantizing Small-Scale State-Space Models for Edge AI A Diagonal Structured State Space Model on Loihi 2 for Efficient Streaming Sequence Processing

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.792876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a101b84-bc95-42a6-b9ba-ea38023c9c27 · outbound

This paper cites Efficient neuromorphic signal processing with loihi 2,.

Quantizing Small-Scale State-Space Models for Edge AI Efficient neuromorphic signal processing with loihi 2,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:54:52.413917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 028c2a8c-1219-4463-9689-3fde4833d163 · outbound

This paper cites How to Train Your HiPPO: State Space Models with Generalized Orthogonal Basis Projections.

Quantizing Small-Scale State-Space Models for Edge AI How to Train Your HiPPO: State Space Models with Generalized Orthogonal Basis Projections

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.803736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e8f517e-0537-466f-8f9a-b62319b8c9b1 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

Quantizing Small-Scale State-Space Models for Edge AI Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.809409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fa48817-941c-4e5a-90f5-c0f6e27403f4 · outbound

This paper cites Simplified State Space Layers for Sequence Modeling.

Quantizing Small-Scale State-Space Models for Edge AI Simplified State Space Layers for Sequence Modeling

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.814566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90e3b0cb-98a9-45f9-a99f-47e01534f5ac · outbound

This paper cites S7: Selective and Simplified State Space Layers for Sequence Modeling.

Quantizing Small-Scale State-Space Models for Edge AI S7: Selective and Simplified State Space Layers for Sequence Modeling

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.820447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b88b1a6c-e316-4847-806c-cab3d7a98a54 · outbound

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

Quantizing Small-Scale State-Space Models for Edge AI Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.826680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0363298d-112c-4f03-98fb-5478d92e1396 · outbound

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

Quantizing Small-Scale State-Space Models for Edge AI Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:51.831747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36b5e03f-10d1-4720-b537-7e93559a30be · outbound

This paper cites Tinyml-based classifi- cation in an ecg monitoring embedded system,.

Quantizing Small-Scale State-Space Models for Edge AI Tinyml-based classifi- cation in an ecg monitoring embedded system,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:54:52.396336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation beae7c46-6074-4ce8-8f1b-5656b7e3443d · outbound

This paper cites Long-term stable electromyography classification using canonical correlation analysis,.

Quantizing Small-Scale State-Space Models for Edge AI Long-term stable electromyography classification using canonical correlation analysis,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:54:52.378498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

Observation 6008856d-fae7-4f17-bea6-b8f967ccbfdd · inbound

QS4D: Quantization-aware training for efficient hardware deployment of structured state-space sequential models cites this paper.

QS4D: Quantization-aware training for efficient hardware deployment of structured state-space sequential models Quantizing Small-Scale State-Space Models for Edge AI

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:16:26.890021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.