Paper Citation Record · LEDGER

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions

As of 14 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 2 inbound Pith citation observations for arXiv:2501.13230.

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

pith.paper-citation-record.v1
2501.13230 v2

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:26:51.531470Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:44:05.094528Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T07:00:59.298075Z

Reference resolution

41 of 41 outbound references displayed

verified exact5
verified fuzzy14
unresolved22
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 40254868-af61-4595-82d1-4d00fce682fa · outbound

This paper cites insertion points.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions insertion points

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:26:52.055865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 481d929d-8bc7-426a-a491-ccead943ea4b · outbound

This paper cites • For the full SSM block, we initialize ∆in over the i dimension, and Ajin over the n dimen- sion.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions • For the full SSM block, we initialize ∆in over the i dimension, and Ajin over the n dimen- sion

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:26:52.024278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ea9c9fa6-e3e5-4063-bfc1-e2807a2505a4 · outbound

This paper cites It’s raw! audio generation with state- space models.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions It’s raw! audio generation with state- space models

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:26:52.112525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 47283a48-a7b9-46f1-ac46-a759bea64667 · outbound

This paper cites language head.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions language head

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:26:51.980509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 478bd955-ecd5-49f8-bc58-12503b7b8c1a · outbound

This paper cites Conformer: Convolution-augmented Transformer for Speech Recognition.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Conformer: Convolution-augmented Transformer for Speech Recognition

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.213613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c554dafa-66c6-464a-bd1c-500b282021a7 · outbound

This paper cites Sequence-to-Sequence Speech Recognition with Time-Depth Separable Convolutions.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Sequence-to-Sequence Speech Recognition with Time-Depth Separable Convolutions

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.219809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a381d9fe-6280-4033-b4a0-36378c5228a6 · outbound

This paper cites bottleneck.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions bottleneck

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:26:52.035185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f22ac24a-fc5c-4ce8-b74f-671d993f34f0 · outbound

This paper cites Jamba: A Hybrid Transformer-Mamba Language Model.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Jamba: A Hybrid Transformer-Mamba Language Model

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.251178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 176ef7e3-2400-4465-ab3e-70a59b7074b7 · outbound

This paper cites Structured state space decoder for speech recognition and synthesis.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Structured state space decoder for speech recognition and synthesis

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:26:52.093965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation df6681ef-8fc2-4007-a688-bed46068e755 · outbound

This paper cites SiMBA: Simplified Mamba-Based Architecture for Vision and Multivariate Time series.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions SiMBA: Simplified Mamba-Based Architecture for Vision and Multivariate Time series

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.258302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95c0a0e9-5403-457c-947b-bc78613de0c0 · outbound

This paper cites Building temporal kernels with orthogonal polynomials.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Building temporal kernels with orthogonal polynomials

Reference 20

Resolution: verified exact; raw_fallback, observed 2026-08-10T16:26:51.733412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8b95ffd1-7229-4e99-8bb7-05507c265235 · outbound

This paper cites aTENNuate: Optimized Real-time Speech Enhancement with Deep SSMs on Raw Audio.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions aTENNuate: Optimized Real-time Speech Enhancement with Deep SSMs on Raw Audio

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.265564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fe7f344-838c-4851-87e7-69d5433c02a2 · outbound

This paper cites Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.269633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02f93389-3f82-4c2e-bc23-9fcb5497ebd2 · outbound

This paper cites DeepFilterNet: Perceptually Motivated Real-Time Speech Enhancement.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions DeepFilterNet: Perceptually Motivated Real-Time Speech Enhancement

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.272692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a401e92b-d1b4-450a-a361-0684a2fc54e2 · outbound

This paper cites Augmenting conformers with structured state-space sequence models for online speech recognition.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Augmenting conformers with structured state-space sequence models for online speech recognition

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-10T16:26:51.631310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c1f1e196-85fb-403d-8de7-2f81802bc833 · outbound

This paper cites Simplified State Space Layers for Sequence Modeling.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Simplified State Space Layers for Sequence Modeling

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.279156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fe17d3e-3baf-4861-bbab-7767aafc410e · outbound

This paper cites A Perceptually-Motivated Approach for Low-Complexity, Real-Time Enhancement of Fullband Speech.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions A Perceptually-Motivated Approach for Low-Complexity, Real-Time Enhancement of Fullband Speech

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-10T16:26:51.604605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d6ad49f1-1576-4ff7-be10-8a3344ea3ae5 · outbound

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

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.285156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07e1eb67-d4cc-4a65-8e94-d3a9736e30e7 · outbound

This paper cites Fully Convolutional Speech Recognition.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Fully Convolutional Speech Recognition

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-10T16:26:51.578469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 73fb0e76-a1e4-4669-9c13-1c7453e40420 · outbound

This paper cites Transformer transducer: A streamable speech recognition model with transformer en- coders and rnn-t loss.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Transformer transducer: A streamable speech recognition model with transformer en- coders and rnn-t loss

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:26:52.085157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5b0a3f1e-9142-4d2d-a72d-b739e95b65dc · outbound

This paper cites Mamba in Speech: Towards an Alternative to Self-Attention.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Mamba in Speech: Towards an Alternative to Self-Attention

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.484520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a02e35c-b2fc-4be8-974d-7350a544b2a2 · outbound

This paper cites Frcrn: Boosting feature representation using frequency recurrence for monaural speech enhancement.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Frcrn: Boosting feature representation using frequency recurrence for monaural speech enhancement

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:26:52.076061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1015b8d2-7ece-4a57-a734-659413faaad5 · outbound

This paper cites memoryless.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions memoryless

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:26:52.066340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 64bfd6db-67ae-43e3-abfe-466fa3ed46b5 · outbound

This paper cites an unresolved cited work.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:26:52.012527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2d7e44cf-3a53-44a3-9afd-175bcfa0eb24 · outbound

This paper cites The number of sub-states for the “neck” SSM block is always.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions The number of sub-states for the “neck” SSM block is always

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:26:52.001559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5d07a586-dbe9-4ba7-b1fd-9089ef54c2ea · outbound

This paper cites no weight decay.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions no weight decay

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:26:51.990454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 969687f3-b409-4f80-a56e-71c91ce58b7d · outbound

This paper cites language head.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions language head

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:26:51.969739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a81e7ed1-a964-4b76-8f73-a07baabd931d · outbound

This paper cites Hungry Hungry Hippos: Towards Language Modeling with State Space Models.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Hungry Hungry Hippos: Towards Language Modeling with State Space Models

Reference 1922

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.197501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9423b4d5-1e81-40dc-b6b1-5435789f8ca4 · outbound

This paper cites ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global Context.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global Context

Reference 1994

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.216685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1760add-4453-4426-bdfe-d425827bdf06 · outbound

This paper cites Quartznet: Deep automatic speech recog- nition with 1d time-channel separable convolutions.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Quartznet: Deep automatic speech recog- nition with 1d time-channel separable convolutions

Reference 2009

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:26:52.102925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8a3ae8b7-3363-491b-a3d2-444af0166315 · outbound

This paper cites An investigation of incorporating mamba for speech enhance- ment.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions An investigation of incorporating mamba for speech enhance- ment

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.186205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4b38d2a-3b74-4b56-98d4-86fd4a2115f8 · outbound

This paper cites Efficient Parallelization of a Ubiquitous Sequential Computation.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Efficient Parallelization of a Ubiquitous Sequential Computation

Reference 2016

Resolution: verified exact; local_arxiv, observed 2026-08-10T16:26:51.785060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ed85b004-f9b5-44d2-9a19-9834dcfa2bba · outbound

This paper cites GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.236548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af01479c-8fcb-4eac-b398-04bc55ec95f9 · outbound

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

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.190504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51fa32f4-9a85-4669-9bdf-734838b94520 · outbound

This paper cites Liquid Structural State-Space Models.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Liquid Structural State-Space Models

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.223969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c339b584-ed9a-496e-95a1-ffb37bbe914e · outbound

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

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Efficiently Modeling Long Sequences with Structured State Spaces

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.210214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5ecba48-2257-40b4-b525-62d4638b8abe · outbound

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

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.206978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e180b0e9-9e3d-419f-914c-ce3057c032ed · outbound

This paper cites Zamba: A Compact 7B SSM Hybrid Model.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Zamba: A Compact 7B SSM Hybrid Model

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.200812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86ade752-ea5f-4581-b3f1-bbb0e40554cf · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.231033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c165723e-c94f-4513-b455-9b180b322ba5 · outbound

This paper cites Real Time Speech Enhancement in the Waveform Domain.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Real Time Speech Enhancement in the Waveform Domain

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.193937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4236f818-97ec-4d1e-9e95-b4e16fa00720 · outbound

This paper cites contracted away.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions contracted away

Reference 2048

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:26:52.045557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation c51db2a0-4b10-4fc2-8c76-e60b3f0a74db · inbound

Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance cites this paper.

Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-06T11:44:05.094528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation edceabfc-705b-4446-b925-f7b622b06345 · inbound

UIPress: Bringing Optical Token Compression to UI-to-Code Generation cites this paper.

UIPress: Bringing Optical Token Compression to UI-to-Code Generation Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:00:59.301543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.