Pith. sign in

Paper Citation Record · LEDGER

Multi-modal single-cell foundation models via dynamic token adaptation

As of 17 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2504.13049.

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

pith.paper-citation-record.v1
2504.13049 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:19:57.112006Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

24 of 24 outbound references displayed

  • verified exact8
  • verified fuzzy1
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3c8c9ffd-406f-4605-a9df-d13360fc6d81 · outbound

This paper cites Ledsam, Agnieszka Grabska-Barwinska, Kyle R.

Multi-modal single-cell foundation models via dynamic token adaptation Ledsam, Agnieszka Grabska-Barwinska, Kyle R

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-16T12:19:57.006706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:19:57.006706Z digest=sha256:b7544c97d77f3b285426e7b7a61edfea1562b4b1c3128ad86bdfa278a7b5536d

Observation 294d53c5-23d0-48fd-8247-8c864e2c9cad · outbound

This paper cites Base-resolution models of transcription-factor binding reveal soft motif syntax.

Multi-modal single-cell foundation models via dynamic token adaptation Base-resolution models of transcription-factor binding reveal soft motif syntax

Reference 2

Resolution
verified exact
doi, observed 2026-08-16T12:19:57.300997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T12:19:57.013012Z digest=sha256:a55ee0dc46f3d4b230689b9409338c9b9cd80c1dceef6d6e5b73da211eba2c62

Observation 5824ec6d-c163-485b-85a7-6c84408a0665 · outbound

This paper cites Unifying Vision-and-Language Tasks via Text Generation.

Multi-modal single-cell foundation models via dynamic token adaptation Unifying Vision-and-Language Tasks via Text Generation

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-16T12:19:57.017796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:19:57.017796Z digest=sha256:5b69edcbabac50de57f7f2483d55c6820ac19b5809610468ffdb603ac24b07a8

Observation c516cee8-d959-4802-af87-f91b088f48c4 · outbound

This paper cites scGPT : Towards Building a Foundation Model for Single - Cell Multi -omics Using Generative AI.

Multi-modal single-cell foundation models via dynamic token adaptation scGPT : Towards Building a Foundation Model for Single - Cell Multi -omics Using Generative AI

Reference 4

Resolution
verified exact
doi, observed 2026-08-16T12:19:57.284933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T12:19:57.022516Z digest=sha256:8e713eb60ce54fe77e1fb52431761b8c5c1966d6cc874a43808841858303cf88

Observation 9daed6a5-3d48-43e7-9849-3ee62132092b · outbound

This paper cites Bell, Emanuele Bezzi, Batuhan Cakir, Jim Chaffer, Signe Chambers, J.

Multi-modal single-cell foundation models via dynamic token adaptation Bell, Emanuele Bezzi, Batuhan Cakir, Jim Chaffer, Signe Chambers, J

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T12:19:57.028484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:19:57.028484Z digest=sha256:289aea2ca249cd9ad5528b1a8d702e0843ce5de2d66ce256d4f4ded5aee26182

Observation 7fbc7f75-ac8c-4a6e-bbbd-5d73a7e33492 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Multi-modal single-cell foundation models via dynamic token adaptation BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-16T12:19:57.032771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:19:57.032771Z digest=sha256:d672100b6f5cf8b9180716518a7fa44317b44007e5620944899038f815b80e8b

Observation 1c28629a-1e19-4595-a06d-783e70317630 · outbound

This paper cites an unresolved cited work.

Multi-modal single-cell foundation models via dynamic token adaptation Unresolved cited work

Reference 7

Resolution
verified exact
doi, observed 2026-08-16T12:19:57.269318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T12:19:57.037942Z digest=sha256:2db7c63f1cf4f4383a9cabd70f3a3203175401f3c6590ece57167ae93a159a47

Observation e21b7129-c6a1-4d54-b791-c2930d37df6f · outbound

This paper cites Shuai, Parth Baokar, Ryan Chung, Ruchir Rastogi, Pooja Kathail, and Nilah M.

Multi-modal single-cell foundation models via dynamic token adaptation Shuai, Parth Baokar, Ryan Chung, Ruchir Rastogi, Pooja Kathail, and Nilah M

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-16T12:19:57.042108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:19:57.042108Z digest=sha256:a5e334936f22bb9622e079be7d04095aafc3908e5f7db785f6fe3fcc288380f2

Observation 6f792dd4-7511-4e3f-830f-f3f071b7530c · outbound

This paper cites an unresolved cited work.

Multi-modal single-cell foundation models via dynamic token adaptation Unresolved cited work

Reference 9

Resolution
verified exact
doi, observed 2026-08-16T12:19:57.245316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T12:19:57.046373Z digest=sha256:54cc3bcc547d933535caec03a1298cbec6b74666c6a2ee4e01a964ee86edcd4d

Observation 0b66da01-b82d-42a8-9daf-ec83a99bcaa4 · outbound

This paper cites Kelley, Yakir A.

Multi-modal single-cell foundation models via dynamic token adaptation Kelley, Yakir A

Reference 10

Resolution
verified exact
doi, observed 2026-08-16T12:19:57.230253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T12:19:57.050715Z digest=sha256:14f1ac96dcdbab183bd163780929f9fa313454d3e878fb089ccfa45bdcc04f56

Observation 25fe2909-b645-45e9-ab6f-8d9c7186d044 · outbound

This paper cites Knight-Schrijver, Hongorzul Davaapil, Semih Bayraktar, Alexander D.

Multi-modal single-cell foundation models via dynamic token adaptation Knight-Schrijver, Hongorzul Davaapil, Semih Bayraktar, Alexander D

Reference 11

Resolution
verified exact
doi, observed 2026-08-16T12:19:57.216124Z

Source-reported events for the cited work

correction dated 2023-04-11. Source: crossref record 10.1038/s44161-023-00269-z->10.1038/s44161-022-00183-w:correction, observed 2026-07-11T03:04:26.902115+00:00. This notice travels one citation hop only.

source=arxiv_source observed=2026-08-16T12:19:57.055162Z digest=sha256:7c65a1b4cb1541c13c010e2e8fed0f35c4692a0d2775aae9a332eded06c7a72f

Observation 49e49926-5bcd-4b9d-99f0-126254ad64c0 · outbound

This paper cites Dhodapkar, and David Van Dijk.

Multi-modal single-cell foundation models via dynamic token adaptation Dhodapkar, and David Van Dijk

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-16T12:19:57.059409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:19:57.059409Z digest=sha256:8182669bf4c396e2d01ccca41b15aaf6cb97041dac8f00b85cc8a97f047f5c57

Observation 6aa3a7a6-4781-48d1-8d27-435c02b011fc · outbound

This paper cites Efficient Fine-Tuning of Single-Cell Foundation Models Enables Zero-Shot Molecular Perturbation Prediction.

Multi-modal single-cell foundation models via dynamic token adaptation Efficient Fine-Tuning of Single-Cell Foundation Models Enables Zero-Shot Molecular Perturbation Prediction

Reference 13

Resolution
metadata mismatch
local_arxiv, observed 2026-08-16T12:19:57.463314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T12:19:57.063714Z digest=sha256:66dae6cc099faae0a962261b3e294adc1d1f2cf28ab693d0e80444f7a1d03316

Observation 99db4130-0c61-458b-b34e-ddeaffee15b3 · outbound

This paper cites Disruption of myocardial Gata4 and Tbx5 results in defects in cardiomyocyte proliferation and atrioventricular septation.

Multi-modal single-cell foundation models via dynamic token adaptation Disruption of myocardial Gata4 and Tbx5 results in defects in cardiomyocyte proliferation and atrioventricular septation

Reference 14

Resolution
verified exact
doi, observed 2026-08-16T12:19:57.192621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T12:19:57.068302Z digest=sha256:4ff6a29bbea571c7f698728336cf3e551fbfd1d64eb4105e9e04246f72643032

Observation ea13847c-b96d-49c2-b135-2fee4c1e2af2 · outbound

This paper cites DeepSpeed : System Optimizations Enable Training Deep Learning Models with Over 100 Billion Parameters.

Multi-modal single-cell foundation models via dynamic token adaptation DeepSpeed : System Optimizations Enable Training Deep Learning Models with Over 100 Billion Parameters

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-16T12:19:57.072493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:19:57.072493Z digest=sha256:6f50ebe5b82d2e436b247aac10694e54a1bb6bf6fa63255b5e6071a7dc51cc38

Observation b39d88ff-6ff2-43df-b62e-83a206400b96 · outbound

This paper cites Spiro, Shinya Tasaki, David A.

Multi-modal single-cell foundation models via dynamic token adaptation Spiro, Shinya Tasaki, David A

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-16T12:19:57.076579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:19:57.076579Z digest=sha256:9d5a856d751a675ebbfb6cd36a74f126d2338861b9caec3ddda21a714a10708b

Observation 0e87004c-2a93-46ac-97bb-665f0f9e149d · outbound

This paper cites Woodruff, Stephen Young, and Kim M.

Multi-modal single-cell foundation models via dynamic token adaptation Woodruff, Stephen Young, and Kim M

Reference 17

Resolution
verified exact
doi, observed 2026-08-16T12:19:57.169018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T12:19:57.080487Z digest=sha256:3f2aa0a71d7ac49642f28fa03ba534fd224a65bbefb7867b3b48c0bd03b1d49f

Observation a4c71c35-a7be-4d5a-b88f-6874edab68cc · outbound

This paper cites Theodoris, Ling Xiao, Anant Chopra, Mark D.

Multi-modal single-cell foundation models via dynamic token adaptation Theodoris, Ling Xiao, Anant Chopra, Mark D

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-16T12:19:57.084305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:19:57.084305Z digest=sha256:18a3b203474916e4401a728d8fa4ffbdd615cbf83084844a11cc6439a13b53d8

Observation 9491e515-35c9-41d1-b6ca-a3e04b96693b · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

Multi-modal single-cell foundation models via dynamic token adaptation HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-16T12:19:57.088330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:19:57.088330Z digest=sha256:86a879198fa41214a8791ab781f993140a4d396883aabda28de86727a0248700

Observation 549226a5-66e0-47ec-825d-df6c91aa24cd · outbound

This paper cites scBERT as a large-scale pretrained deep language model for cell type annotation of single-cell RNA -seq data.

Multi-modal single-cell foundation models via dynamic token adaptation scBERT as a large-scale pretrained deep language model for cell type annotation of single-cell RNA -seq data

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-16T12:19:57.092638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:19:57.092638Z digest=sha256:ca32b5d98be4332287f9978698b92e9835ef66fbfc36d34fd09619e7e7c4fd23

Observation 8ac426f1-d70c-4519-b472-3a026bc19b04 · outbound

This paper cites write newline.

Multi-modal single-cell foundation models via dynamic token adaptation write newline

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-16T12:19:57.097471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:19:57.097471Z digest=sha256:90b2f74ea829ae8d475609113d1c4ed9d1fe5abc050e0ede42753be54d07ab58

Observation 1828e020-2484-4381-91ae-b1ec7e172e80 · outbound

This paper cites @esa (Ref.

Multi-modal single-cell foundation models via dynamic token adaptation @esa (Ref

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-16T12:19:57.102853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:19:57.102853Z digest=sha256:e6bc0f0df903dc0d4622615acf74f1c0b9d8d8f2b1573015dfb5e5bc594df888

Observation 36a3b466-1f1b-42df-af5e-6103a55bc102 · outbound

This paper cites an unresolved cited work.

Multi-modal single-cell foundation models via dynamic token adaptation Unresolved cited work

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-16T12:19:57.107511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:19:57.107511Z digest=sha256:54ab8eb5ce892d96bdb95297d91baf36d2835377601d2117b989b6b28aa4cd56

Observation ce0429cf-4f46-4868-9ca3-54a417f7feec · outbound

This paper cites Ƙ [k6Xs-g4FNʑrE 6 km k ZΏ 5G I ƬE0 .' |Hҳ B nkQrZsGșOR(Z KxEoܿs>&'FRv oUr QNk!r ,= cL c u4IwõZǡ r_Kz51 . w |9=317zILJ^ nwό1Wym aaݱK:Z C1ǩE4u tv9׬ ?l) `+gbDD ×»N;_NoHXZ Z Č1&.

Multi-modal single-cell foundation models via dynamic token adaptation Ƙ [k6Xs-g4FNʑrE 6 km k ZΏ 5G I ƬE0 .' |Hҳ B nkQrZsGșOR(Z KxEoܿs>&'FRv oUr QNk!r ,= cL c u4IwõZǡ r_Kz51 . w |9=317zILJ^ nwό1Wym aaݱK:Z C1ǩE4u tv9׬ ?l) `+gbDD ×»N;_NoHXZ Z Č1&

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T12:19:57.510007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T12:19:57.112006Z digest=sha256:4697509da2cd6224dbe0b1490f50c25578a94c660e2843fb135d48b2e34af394

Pith citing papers

No inbound Pith citation observations are available.