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Paper Citation Record · LEDGER

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

As of 9 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 2026-08-09T06:31:02.800959+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
  • metadata mismatch0

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:51.268320Z digest=sha256:976a22d5fe8168b02057134a0bb29a958cf0c670705e9d2bc57d742720a316a0

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

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raw_fallback, observed 2026-08-07T01:19:01.073511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:51.321189Z digest=sha256:abbb0acdc377f6062cad2412ffc7e258053baaa8e6ae3e4f67715922983bf482

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:51.372635Z digest=sha256:7c27ddbe7fb74dedbbac012e38cca62e2a691a719a70e042750561d3d3f80aa8

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=sha256:1a100f75f3f75830c85183d0dd1928d98e4c32c253a61b72f3f3c20948f88971

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:fa21da002850359490087296800446213f55354e66b5e5f0ef23ee05e939e902

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:51.551693Z digest=sha256:f579e386b05f4491d48fb418198e09025caf4bf7f19f953f54b2472a2c7cc3c4

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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verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:51.678890Z digest=sha256:0eb5afbd280640b7aa3b210575375d4b73ca0c6a799e90e479c3c4df4dcb6c74

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:51.812359Z digest=sha256:cd724d37a68a9c7ba7157a0d5a9411e4ed0d092fac4e592a046eb27c704cb3bb

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:52.012023Z digest=sha256:0eab3f09dbaba3c9fc2e280e41739b28bd2b06c646b3b1870bb5d2cf9a1dede8

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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:52.178137Z digest=sha256:ed41a576ba5d8595a22ac8e7ceef3017a88346e1042f2ee79292928c7fa20479

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
unresolved
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=sha256:24c5db61b70ac2e11b8735ef2ab29131a107c962266435e47cef0ad59146e596

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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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:52.337665Z digest=sha256:f6ada8a4b4934df3935a0f560884ce442efdf7b92c5eefd1eef733b0869e02b0

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:52.497716Z digest=sha256:61a5e8b766a77d1fe444408fc97704ac20c96e32f226d55463a9a0a7e1dfdd43

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:52.679987Z digest=sha256:a928ca1f9ca5d64597ec6427fbebe78c2938e4d08e7dc30fa7f0a4ca3bd10a4c

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:52.881342Z digest=sha256:bf60b219f3c279736b91e05b1b5a5a3dc97bde445d57829a46fcb2b8dc5079fd

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:53.011430Z digest=sha256:7c7231ebf71a8a105ffcc8603249e5fd6dd311029f9b2b5d4298d2ad011d37f2

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

Resolution
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=sha256:0ec5adcc6ba2bd1b7a5c8505bbc32335306bd3311af173853c65960e08713c34

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 2026-08-09T06:31:02.800959+00:00.

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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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:53.385624Z digest=sha256:9c545032d7c551796bc8139b532d47382aadfd18b9533c4f50c76c4c5f462d11

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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unresolved
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=sha256:469d43b1ba370bcc2ebe27d96afc426c63e8ea1a4b0f958aeb4ea34c3ca391d7

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:53.703055Z digest=sha256:e3947f772782b7049ebeec13d2d471a293ed42a8cee56d292ebac3d05709cfa2

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:18:57.412416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:53.848311Z digest=sha256:47651475a55c08518016b93c5fe4e3a745accfbfecca6eeff2ac9778515033f4

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

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:53.894209Z digest=sha256:47b84654c38f7154385b0b0e7889ec10bce68d17c8bed6f3025fb85a5e640a48

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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verified exact
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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:53.950728Z digest=sha256:f5bea8642ef8d254007b1bbd881a8e50d398cc7918ad10c5ed5e918f3ceacdb5

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:54.031696Z digest=sha256:01fe2da70aa3a437b4714c1e931d0a54c30a1078efa8635fb5fefd45bdd90137

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:54.143503Z digest=sha256:b7a328150eb4dd8630cc973be82ad6a0ff268543c1771ec31e2f29d6269de5d4

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:54.212257Z digest=sha256:e4cab40cbb05b38fe7a54d8bc21bd55f777a51a07045b9a80ec5ed37a770e67c

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:d47c699cc86247d421f91393c47a12619351c95e803bf088a9fc4afddb4e8afc

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:54.467498Z digest=sha256:54c06b3cf590fdb30bd8d0dd954bc3c94a1010fb1e487a18c5dc86edcdcade06

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

Resolution
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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T01:18:54.601615Z digest=sha256:c0939ca1ef978c7d68741db46c87d05ac80848fd81c4c4d354475cf8ac55beae

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

Resolution
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=sha256:38a6f8bcc20303ea8dbfecf47ba7fb208df95c5b1705968cfe7bb2da5f956ef4

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T04:45:43.948266Z digest=sha256:6e7e7eec94e8f6303971e81b1d304400677257cbee7baa11b63089a8a0e02667