Paper Citation Record · LEDGER

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot

As of 9 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2506.09613.

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

pith.paper-citation-record.v1
2506.09613 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:48:41.453452Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T20:01:44.930772Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T22:15:51.495188Z

Reference resolution

52 of 52 outbound references displayed

verified exact1
verified fuzzy30
unresolved20
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9cea98ff-b878-4c08-8d9e-a2a3b53e28c8 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot LLaMA: Open and Efficient Foundation Language Models

Reference 1

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Source-reported events for the cited work

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Observation aef03aac-5fe3-4161-b7aa-fa143f91314c · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot OPT: Open Pre-trained Transformer Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T04:48:35.623804Z

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Observation 0202128a-4688-4cc8-9e55-0afcd235865f · outbound

This paper cites Bloom: A 176b-parameter open-access multilingual language model, 2023.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Bloom: A 176b-parameter open-access multilingual language model, 2023

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:48.460188Z

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Observation 56431f59-99ed-4377-b42b-9f328f065f3d · outbound

This paper cites LeCun, J.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot LeCun, J

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:48.239306Z

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Observation 210c07c2-a9fc-4596-80ff-3fa9ea607806 · outbound

This paper cites Hassibi and D.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Hassibi and D

Reference 5

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Source-reported events for the cited work

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Observation df0fb723-b776-4593-8b16-4a5c582d5c9f · outbound

This paper cites Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T04:48:36.105707Z

Source-reported events for the cited work

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Observation d4a81e14-ea20-41de-b1a9-76131cd86953 · outbound

This paper cites Llm-pruner: On the structural pruning of large language models.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Llm-pruner: On the structural pruning of large language models

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:48.113114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2d6a3b0c-f671-4d33-9b43-d8e76457944f · outbound

This paper cites SparseGPT: Massive language models can be accurately pruned in one-shot.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot SparseGPT: Massive language models can be accurately pruned in one-shot

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:47.969672Z

Source-reported events for the cited work

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Observation 95ff4177-cf66-45f7-b80c-e9c724366125 · outbound

This paper cites Learning both weights and connections for efficient neural network.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Learning both weights and connections for efficient neural network

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:47.815953Z

Source-reported events for the cited work

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Observation 21a56e8d-8ec5-4cf3-8ce1-beb59d90f6f4 · outbound

This paper cites Pruning filters for efficient convnets.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Pruning filters for efficient convnets

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:47.603299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f222710b-1cba-42f8-a193-0945f7366155 · outbound

This paper cites Channel pruning for accelerating very deep neural networks.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Channel pruning for accelerating very deep neural networks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:47.366225Z

Source-reported events for the cited work

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Observation 6e315756-2e63-49d7-b257-3724d5d1ccb7 · outbound

This paper cites Snip: Single-shot network pruning based on connection sensitivity.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Snip: Single-shot network pruning based on connection sensitivity

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:47.128241Z

Source-reported events for the cited work

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Observation d8f46d20-c313-459e-8312-28c23d0c1fcf · outbound

This paper cites Pruning neural networks without any data by iteratively conserving synaptic flow.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Pruning neural networks without any data by iteratively conserving synaptic flow

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:46.941950Z

Source-reported events for the cited work

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Observation 834abf57-261b-4fd6-85ac-29fe318cdc52 · outbound

This paper cites Optimal brain compression: A framework for accurate post- training quantization and pruning.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Optimal brain compression: A framework for accurate post- training quantization and pruning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:46.705601Z

Source-reported events for the cited work

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Observation a271ce28-54d2-4cca-bac9-939aad7a9d7e · outbound

This paper cites A Simple and Effective Pruning Approach for Large Language Models.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot A Simple and Effective Pruning Approach for Large Language Models

Reference 15

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Source-reported events for the cited work

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Observation 339ba2ff-90b6-4a28-939f-2ab428afc0d6 · outbound

This paper cites Alps: Improved optimiza- tion for highly sparse one-shot pruning for large language models.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Alps: Improved optimiza- tion for highly sparse one-shot pruning for large language models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:46.428231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f6957b5b-d683-46d6-8704-66b5acd802d6 · outbound

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

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 17

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Source-reported events for the cited work

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Observation 9bf9a43f-bfc0-4a30-9be6-7c5c7005d4b8 · outbound

This paper cites Transformers are SSMs: Generalized models and efficient algorithms through structured state space duality.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Transformers are SSMs: Generalized models and efficient algorithms through structured state space duality

Reference 18

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Source-reported events for the cited work

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Observation b374860f-cbb5-4ed0-ac31-2cafb6f65783 · outbound

This paper cites Falcon Mamba: The First Competitive Attention-free 7B Language Model.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Falcon Mamba: The First Competitive Attention-free 7B Language Model

Reference 19

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Source-reported events for the cited work

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Observation 5d12d4f0-bf0c-457e-8a1a-bdbb973e27c4 · outbound

This paper cites Attention is all you need.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Attention is all you need

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:46.203423Z

Source-reported events for the cited work

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Observation 05bae9f7-1211-4cf6-870e-2c4c208b096f · outbound

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

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Hippo: Recurrent memory with optimal polynomial projections

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:46.026927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2704437d-3373-420a-a5e9-87286f94e954 · outbound

This paper cites Efficiently modeling long sequences with structured state spaces.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Efficiently modeling long sequences with structured state spaces

Reference 22

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Source-reported events for the cited work

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Observation 16fffab3-86a4-497b-8f23-a4b05da60b64 · outbound

This paper cites Smith, Andrew Warrington, and Scott Linderman.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Smith, Andrew Warrington, and Scott Linderman

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:45.825758Z

Source-reported events for the cited work

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Observation 5bc91534-480e-489b-a1df-b5df7cce7024 · outbound

This paper cites Jamba: A hybrid transformer-mamba language model.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Jamba: A hybrid transformer-mamba language model

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:45.610811Z

Source-reported events for the cited work

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Observation c5f87c24-ede5-4183-ba96-f8f2899182f2 · outbound

This paper cites The Zamba2 Suite: Technical Report.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot The Zamba2 Suite: Technical Report

Reference 25

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Source-reported events for the cited work

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Observation 11f4c726-aab9-4f00-b71f-7a5a7c810f92 · outbound

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

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot SiMBA: Simplified Mamba-Based Architecture for Vision and Multivariate Time series

Reference 26

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Source-reported events for the cited work

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Observation 25719a15-1504-4c2e-84f1-b2e79e8d364b · outbound

This paper cites Hymba: A Hybrid-head Architecture for Small Language Models.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Hymba: A Hybrid-head Architecture for Small Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T04:48:38.651983Z

Source-reported events for the cited work

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Observation 1731b7b4-e650-45c9-a1bb-ee170c75e774 · outbound

This paper cites Woodfisher: Efficient second-order approximations for model compression.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Woodfisher: Efficient second-order approximations for model compression

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:45.437266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b812f7e2-66b3-4dc2-ae83-ad1bab4bd368 · outbound

This paper cites Fast as chita: Neural network pruning with combinatorial optimization.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Fast as chita: Neural network pruning with combinatorial optimization

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:45.265267Z

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Observation a4415ef5-dfca-4b30-9343-293fbb903135 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 30

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Source-reported events for the cited work

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Observation 47333e39-646e-47a9-821d-4014b40927d7 · outbound

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SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:48:45.079050Z

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Observation 2fac348a-30da-4891-b39c-dc1be7a6b1fc · outbound

This paper cites DarwinLM: Evolutionary Structured Pruning of Large Language Models.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot DarwinLM: Evolutionary Structured Pruning of Large Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T04:48:39.329408Z

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Observation 88da8fff-8cad-4446-9526-a02e2224d876 · outbound

This paper cites Slimgpt: Layer-wise structured pruning for large language models.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Slimgpt: Layer-wise structured pruning for large language models

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:44.867997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c88af3c6-328f-4974-acaa-cbfd211496a6 · outbound

This paper cites Structured optimal brain pruning for large language models.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Structured optimal brain pruning for large language models

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:44.692747Z

Source-reported events for the cited work

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Observation f08b5805-d3a8-43ea-9ad1-5ed25115a421 · outbound

This paper cites The iterative optimal brain surgeon: Faster sparse recovery by leveraging second-order information.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot The iterative optimal brain surgeon: Faster sparse recovery by leveraging second-order information

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:44.549993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e3a38d75-583f-4949-9cf0-04b8d1b54469 · outbound

This paper cites The combinatorial brain surgeon: Pruning weights that cancel one another in neural networks.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot The combinatorial brain surgeon: Pruning weights that cancel one another in neural networks

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:44.356833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 603867f9-d6a1-421e-aba4-196014211e14 · outbound

This paper cites Layer-adaptive state pruning for deep state space models.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Layer-adaptive state pruning for deep state space models

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:44.202175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 98d47ea2-815c-43c7-bdcd-841e197e5cec · outbound

This paper cites Pablo Muñoz, Jinjie Yuan, and Nilesh Jain.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Pablo Muñoz, Jinjie Yuan, and Nilesh Jain

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:43.986090Z

Source-reported events for the cited work

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Observation 581514c9-43b0-4a54-a1f2-aa6394ebb036 · outbound

This paper cites Ghattas, M.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Ghattas, M

Reference 39

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4c8d3c8b-17ec-4367-8a7e-2a9762ab5a23 · outbound

This paper cites Taghibakhshi, S.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Taghibakhshi, S

Reference 40

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Observation 20ba7394-1de0-4d23-aeac-27a7417ec6aa · outbound

This paper cites an unresolved cited work.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:48:43.819496Z

Source-reported events for the cited work

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Observation 4e7d9b20-e63d-4426-be6b-9d58565cffd9 · outbound

This paper cites One-shot sensitivity-aware mixed sparsity pruning for large language models.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot One-shot sensitivity-aware mixed sparsity pruning for large language models

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:43.618839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f865a566-1b6a-4288-8369-940a8fd018e0 · outbound

This paper cites Perplexity of fixed-length models.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Perplexity of fixed-length models

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:43.474580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8d641b5c-387a-4046-98e7-15efe74202aa · outbound

This paper cites Pointer sentinel mixture models.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Pointer sentinel mixture models

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:43.241072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 51abf22b-7086-49a6-91dc-0d0c2048f2ca · outbound

This paper cites The penn treebank: Annotating predicate argument structure.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot The penn treebank: Annotating predicate argument structure

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:43.009370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e883cf4b-8d72-459b-b2d0-a68ecaf4f0b7 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.JMLR, 21(140):1–67, 2020.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Exploring the limits of transfer learning with a unified text-to-text transformer.JMLR, 21(140):1–67, 2020

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:42.796738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2c8a5667-0c1e-4ed3-a64a-869163381d74 · outbound

This paper cites Piqa: Reasoning about physical commonsense in natural language.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Piqa: Reasoning about physical commonsense in natural language

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:42.609460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6d3e0bb3-0c26-48d9-b792-761965f770e5 · outbound

This paper cites Can a suit of armor conduct electricity? a new dataset for open book question answering.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Can a suit of armor conduct electricity? a new dataset for open book question answering

Reference 48

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Source-reported events for the cited work

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Observation 5b247c32-fadb-45ff-8fb2-ac4c732dc1ab · outbound

This paper cites WinoGrande: An Adversarial Winograd Schema Challenge at Scale.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot WinoGrande: An Adversarial Winograd Schema Challenge at Scale

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T04:48:41.169703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cec7676-169f-44eb-9750-7f9092b2d158 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T04:48:41.279381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2888060-8732-4748-a481-34d152a97240 · outbound

This paper cites mamba-minimal: A minimal pytorch implementation of mamba.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot mamba-minimal: A minimal pytorch implementation of mamba

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:48:42.426351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a56fa232-882b-4d7e-b582-5e54cbca2784 · outbound

This paper cites Long short-term memory.Neural Computation, 9(8):1735–1780, 1997.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot Long short-term memory.Neural Computation, 9(8):1735–1780, 1997

Reference 52

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T04:48:41.777647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

Observation d97a7b6d-7f86-4536-a789-1ba4e2371740 · inbound

Cross-Resolution Diffusion Models via Network Pruning cites this paper.

Cross-Resolution Diffusion Models via Network Pruning SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:15:51.501697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.