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Paper Citation Record · LEDGER

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity

As of 20 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:2506.11891.

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

pith.paper-citation-record.v1
2506.11891 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T01:18:54.697608Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T04:45:43.948266Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

32 of 32 outbound references displayed

  • verified exact5
  • verified fuzzy19
  • unresolved8
  • parse uncertain0
  • malformed identifier0
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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 707e414a-0c76-46b9-946b-1f90ce68815d · outbound

This paper cites Zoology: Measuring and Improving Recall in Efficient Language Models.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Zoology: Measuring and Improving Recall in Efficient Language Models

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:51.268320Z digest=sha256:cfeef987a0cf34528d444701e13fa69ba7d8f7cc7e3d7b6adbf3426dc0be0f2b

Observation 7bbc21c9-7119-43b7-abb3-f438eb7510ed · outbound

This paper cites Simple Linear Attention Language Models Balance the Recall-Throughput Tradeoff.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Simple Linear Attention Language Models Balance the Recall-Throughput Tradeoff

Reference 2

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 0b3719ce-f0b6-4eaf-a2af-62643e6e89ee · outbound

This paper cites Birth of a Transformer: A Memory Viewpoint.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Birth of a Transformer: A Memory Viewpoint

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:51.372635Z digest=sha256:9c1eb15f05dd4b37da683e408b35d0188b230e9e5b2e083302234f1ad710b416

Observation c7ad6197-2c7d-4432-9d5b-2249cf7b5a9e · outbound

This paper cites Theoretical limitations of multi-layer Transformer.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Theoretical limitations of multi-layer Transformer

Reference 4

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unresolved
no resolver link, observed 2026-08-07T01:18:51.437766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:18:51.437766Z digest=sha256:1c1e334c62b6236b12552991c2a436211de24ae6e5bf7e3b559bd6ea9baec83c

Observation 4b5481cb-1738-4eed-b226-e5e51b35f33a · outbound

This paper cites and Cholak, P.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity and Cholak, P

Reference 5

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unresolved
no resolver link, observed 2026-08-07T01:18:51.488460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:18:51.488460Z digest=sha256:b61bf0e5aebadf5910031942c7bceba76045178d14f7415668d67c5199e043ee

Observation a5256c5a-76b2-4c46-9c11-2ead426ea0a3 · outbound

This paper cites M., Orvieto, A., Walker, B., Salvi, C., and Lyons, T.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity M., Orvieto, A., Walker, B., Salvi, C., and Lyons, T

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:19:00.579600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:51.551693Z digest=sha256:3c7bb628c1ca2761a8edcb48c3c15c9db5b9237e6d002e40a44e2c841071935c

Observation 8123b028-75aa-47b6-9345-aeb23bdab025 · outbound

This paper cites A., and Verghese, G.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity A., and Verghese, G

Reference 7

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raw_fallback, observed 2026-08-07T01:19:00.254421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:51.678890Z digest=sha256:455271d6d0e19e15f3d5ef6dac0bce1eca8f866c430aa3af92f7955a7fefd9b8

Observation 1bf41d3e-4781-40e5-b191-6ce2dd27d672 · outbound

This paper cites and Gu, A.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity and Gu, A

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:51.812359Z digest=sha256:27b4bae8cee97074be7b25e26599c1da63d3869a9504e704d1537c3d2278f385

Observation 297efbdf-4f60-46b4-aec8-501bbf09b376 · outbound

This paper cites an unresolved cited work.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Unresolved cited work

Reference 9

Resolution
verified exact
doi, observed 2026-08-07T01:18:55.484251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:52.012023Z digest=sha256:65b61ea13b90dcd8b37c94bcb36f23215b2fb185583cc559495ee66ff726c819

Observation a2739399-629b-4728-9f42-bf0d7a5f3329 · outbound

This paper cites and Inglese, G.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity and Inglese, G

Reference 10

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verified exact
doi, observed 2026-08-07T01:18:55.278780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 5fd7a85a-bfcd-4b0d-acf6-d928af7f4be4 · outbound

This paper cites K., Zela, A., Hutter, F., and Pontil, M.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity K., Zela, A., Hutter, F., and Pontil, M

Reference 11

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:52.178137Z digest=sha256:b5ad14f77d387cc9a6ecbb6568fef1e5e027d111ae792023cc66349c3253ba17

Observation 29a4dee8-019a-4e9d-8d54-4c04f71579c0 · outbound

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

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 12

Resolution
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no resolver link, observed 2026-08-07T01:18:52.210178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:18:52.210178Z digest=sha256:d62a42b3ad8b9dce20e0e587e6e09bdf9ad59d0fd9520037e54b7c842a338dce

Observation 73232ade-f7a8-4e1a-8161-fc1cd4422213 · outbound

This paper cites HiPPO: Recurrent Memory with Optimal Polynomial Projections.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity HiPPO: Recurrent Memory with Optimal Polynomial Projections

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:52.337665Z digest=sha256:e9a6f09ad8b99454c45549297bc4aeb902bcb2902e32e06b8a56d8856e15fb01

Observation cb05c93e-adab-4d25-973a-0a274508b216 · outbound

This paper cites On the Parameterization and Initialization of Diagonal State Space Models.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity On the Parameterization and Initialization of Diagonal State Space Models

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-07T01:18:59.059969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:52.497716Z digest=sha256:4d82a026fe9c92490e9870b0b079170c5879a773685f99cc21c959f119427a76

Observation fa047d8a-0195-4537-a2b6-3c6c731beea2 · outbound

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

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Efficiently Modeling Long Sequences with Structured State Spaces

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-07T01:18:58.714298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:52.679987Z digest=sha256:bbec1008a70a38a7da9ca0905d8d205069b2360046e0bc6af82d5ba0fa7bc705

Observation 4229ad21-c131-4360-986a-0429a03145be · outbound

This paper cites Needle In A Haystack - Pressure Testing LLMs.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Needle In A Haystack - Pressure Testing LLMs

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:52.881342Z digest=sha256:4e34db9a7b91c1e66049460fc24e1c21284a2544edd961f5c3bf9cc6c30683f5

Observation e6944d5b-9532-436e-b258-34c5f15c2c30 · outbound

This paper cites Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention

Reference 17

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:53.011430Z digest=sha256:f114932940dd15bcf4cce9df8d0d3cb92754a245641baffc36c3e5b991f414cb

Observation 062f2e3d-b563-4b15-990c-5fcdceaf06ea · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Adam: A Method for Stochastic Optimization

Reference 18

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unresolved
no resolver link, observed 2026-08-07T01:18:53.146243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:18:53.146243Z digest=sha256:64b7c6d9757a3d70c66f686729ad852afe8c16d3adc908006a83f2b260c239b4

Observation 8f60cd69-7437-43db-aede-fb865bde057c · outbound

This paper cites On the Power of Convolution Augmented Transformer.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity On the Power of Convolution Augmented Transformer

Reference 19

Resolution
verified exact
doi, observed 2026-08-07T01:18:55.100291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:53.241637Z digest=sha256:70673009a5f945c9753cbbaa7a0d8f8441cbb64b814d8b9ccd08f1afe0923ce7

Observation 7151d90d-a523-4948-853e-ca844d525f2b · outbound

This paper cites Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-07T01:18:57.927896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:53.385624Z digest=sha256:3898b3ff8039d429bf271b761c15a25bd864fd64195ac9c7a006c71e6032870a

Observation 5555acb1-56fd-42b7-a003-7ae26b13118f · outbound

This paper cites Group Invariant Scattering.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Group Invariant Scattering

Reference 21

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no resolver link, observed 2026-08-07T01:18:53.543767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:18:53.543767Z digest=sha256:719e26822fac71c16679216693eb32b44521d70dfb8bdbed780e93dea3a32a59

Observation be6024fe-6e53-4250-a1dd-8f0e343d7cba · outbound

This paper cites The Illusion of State in State-Space Models.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity The Illusion of State in State-Space Models

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:18:57.649798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:53.703055Z digest=sha256:90a3ee4099c9a49aefff2fdd969b932118c44512466dcd9bd221f94086798f4e

Observation 81ac0e6a-df74-4434-a818-e74778b9998f · outbound

This paper cites In-context Learning and Induction Heads.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity In-context Learning and Induction Heads

Reference 23

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 6744fd59-1db4-4320-8ed8-a2102befb7c2 · outbound

This paper cites an unresolved cited work.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Unresolved cited work

Reference 24

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:53.894209Z digest=sha256:27096bd6145a9ff42754f8e62bd0c441fe9949f32b67a32dfda88fcae2603a22

Observation f011c0d9-d48e-48eb-ad30-906f59def822 · outbound

This paper cites One-layer transformers fail to solve the induction heads task.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity One-layer transformers fail to solve the induction heads task

Reference 25

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local_arxiv, observed 2026-08-07T01:18:55.752708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:53.950728Z digest=sha256:c98c1236d4920ccfc7a0747e8e01617a5099b7d3a72e8fcf0388ad58554e2309

Observation 3f5d5969-8196-4baa-8b4f-8bcf7000cc61 · outbound

This paper cites Transformers, Parallel Computation, and Logarithmic Depth.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Transformers, Parallel Computation, and Logarithmic Depth

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-07T01:18:56.909919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:54.031696Z digest=sha256:9f9e75dcbf9e41ceb0c8a67cdae7b06522b42f75fe49303c7f3ba0c89a094c57

Observation c0220d9f-1a40-4a10-8370-1331583aa12b · outbound

This paper cites The Expressive Capacity of State Space Models: A Formal Language Perspective.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity The Expressive Capacity of State Space Models: A Formal Language Perspective

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-07T01:18:56.596279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:54.143503Z digest=sha256:56208aa7b2a447dc6e28f3e09f2aa8f67a1b8c490c11597c26d6acd89bc283cc

Observation 3822dc92-25cd-477c-8a86-2f4182562099 · outbound

This paper cites Crucial Aspects of Zero-Order Hold LPV State-Space System Discretization.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Crucial Aspects of Zero-Order Hold LPV State-Space System Discretization

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:18:56.295051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:54.212257Z digest=sha256:9c675d35111c59dfd556fe50ea708dfa1a7584209ebb4c5854f1c3d744b7d3bd

Observation ea9c3a74-b52f-443a-ae52-132abb21d5bf · outbound

This paper cites High-Dimensional Probability: An Introduction with Applications in Data Science.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity High-Dimensional Probability: An Introduction with Applications in Data Science

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T01:18:54.327843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:18:54.327843Z digest=sha256:67765aed1c51943ae5326cdfb4fca9b6a8a64a570aa1d6a59302b5979b24dc02

Observation 2c63fab1-3e47-41ac-9e2f-fbe63b2ade47 · outbound

This paper cites Wavelets, Approximation, and Compression.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Wavelets, Approximation, and Compression

Reference 30

Resolution
verified exact
doi, observed 2026-08-07T01:18:54.894304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:54.467498Z digest=sha256:9c68ae3c4f0db782c36599241e93064718b786194d96f8455303b44b42c0ee61

Observation c8982e59-c5e1-4e65-ae60-5be53633e4d8 · outbound

This paper cites Inverse Approximation Theory for Nonlinear Recurrent Neural Networks.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Inverse Approximation Theory for Nonlinear Recurrent Neural Networks

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-07T01:18:56.019086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T01:18:54.601615Z digest=sha256:deade6d1ae62004d736c7dea3b382536eccb69c275c786b8e624a7ad5e73a5dd

Observation b039b66e-ad36-411e-b43a-790e91d05300 · outbound

This paper cites Pointer Value Retrieval: A new benchmark for understanding the limits of neural network generalization.

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity Pointer Value Retrieval: A new benchmark for understanding the limits of neural network generalization

Reference 32

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unresolved
no resolver link, observed 2026-08-07T01:18:54.697608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:18:54.697608Z digest=sha256:2ac419a8d2164ca8f952563e7bbb82d27c1c47ac5b29716fb3de15397a4d3bc8

Pith citing papers

Observation 51399198-7a80-4a43-acc2-639c9826d179 · inbound

Sessa: Selective State Space Attention cites this paper.

Sessa: Selective State Space Attention Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-10T04:50:23.002455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-10T04:45:43.948266Z digest=sha256:77fc1aac4ef901d9db99c95324072b5ed33eb91085354cbf25dd3c5037884f6a