Paper Citation Record · LEDGER

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification

As of 5 August 2026, this Paper Citation Record lists 6 of 6 outbound references and 0 inbound Pith citation observations for arXiv:2605.24961.

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

pith.paper-citation-record.v1
2605.24961 v1

Coverage vector

measured 6 of 6 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T11:50:09.167866Z

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

6 of 6 outbound references displayed

verified exact0
verified fuzzy4
unresolved0
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 47c2ca74-17d5-4b77-9d93-b687a4cda25d · outbound

This paper cites EEGMamba: Bidirectional State Space Model with Mixture of Experts for EEG Multi-task Classification.

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification EEGMamba: Bidirectional State Space Model with Mixture of Experts for EEG Multi-task Classification

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T11:54:38.380194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dab88b64-2169-46fb-be20-58e7b2472c84 · outbound

This paper cites A standard SSM might overfit toT t.

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification A standard SSM might overfit toT t

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T08:26:06.005081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 932cec5f-4030-4481-82fc-d28634e8eb7b · outbound

This paper cites vanishing memory.

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification vanishing memory

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T08:26:06.007447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 88a46c13-9c27-4a6a-bc70-862790984eb1 · outbound

This paper cites For a set of kernels with maximum sizeK, the complexity is: OM CE =O(T·C·D·K)(53) SinceKis a small constant (e.g.,K= 7) and independent ofT, this operation is strictly linearO(T).

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification For a set of kernels with maximum sizeK, the complexity is: OM CE =O(T·C·D·K)(53) SinceKis a small constant (e.g.,K= 7) and independent ofT, this operation is strictly linearO(T)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T08:26:06.014784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 135b708e-348d-48c1-9d92-a8a1064be4f5 · outbound

This paper cites With state dimensionN, the complexity isO(T·D·N).

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification With state dimensionN, the complexity isO(T·D·N)

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T08:26:06.011996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a920b6e6-df60-42aa-b59b-cd0306945b2a · outbound

This paper cites w/o MCE”, “w/o TDSSE.

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification w/o MCE”, “w/o TDSSE

Reference 6

Resolution: malformed identifier; raw_fallback, observed 2026-07-09T08:26:06.009706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

No inbound Pith citation observations are available.