Paper Citation Record · LEDGER

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning

As of 9 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2605.25708.

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

pith.paper-citation-record.v1
2605.25708 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T23:12:11.283075Z

measured 19 of 19 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 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

19 of 19 outbound references displayed

verified exact3
verified fuzzy0
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aa9aaf2b-dc30-4a13-9ac6-10c334968b92 · outbound

This paper cites Memory aware synapses: Learning what (not) to for- get.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Memory aware synapses: Learning what (not) to for- get

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 937e17b0-cf5a-4e8b-8fbb-f3ca63491092 · outbound

This paper cites Author and B.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Author and B

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb4f766f-8b18-4393-a345-48ed7751e4fd · outbound

This paper cites Don't Stop Learning: Towards Continual Learning for the CLIP Model.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Don't Stop Learning: Towards Continual Learning for the CLIP Model

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T23:14:01.249937Z

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.

Observation abb5f9ec-ffa8-4c87-ac18-aaee759273ba · outbound

This paper cites Iap: Improving continual learning of vision-language models via instance- aware prompting.IEEE Transactions on Image Process- ing,.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Iap: Improving continual learning of vision-language models via instance- aware prompting.IEEE Transactions on Image Process- ing,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 556542d7-bd2d-491e-9187-ab29ddc39826 · outbound

This paper cites MaPLe: Multi-modal prompt learn- ing.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning MaPLe: Multi-modal prompt learn- ing

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ad5a7d6-919e-4337-ad7e-d04ccd1b3f18 · outbound

This paper cites Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hass- abis, Claudia Clopath, Dharshan Kumaran, and Raia Had- sell.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hass- abis, Claudia Clopath, Dharshan Kumaran, and Raia Had- sell

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3c87025-31f9-4aae-83d6-0d7c6313251c · outbound

This paper cites Learning without forgetting.IEEE Transactions on Pat- tern Analysis and Machine Intelligence, 40(12):2935– 2947,.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Learning without forgetting.IEEE Transactions on Pat- tern Analysis and Machine Intelligence, 40(12):2935– 2947,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52d706d3-4c3e-4a4f-86ac-5ff8457770bf · outbound

This paper cites Replay to Remember (R2R): An Efficient Uncertainty-driven Unsupervised Continual Learning Framework Using Generative Replay.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Replay to Remember (R2R): An Efficient Uncertainty-driven Unsupervised Continual Learning Framework Using Generative Replay

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-06-29T23:14:01.244995Z

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.

Observation 92bccb65-bcb3-4d6a-91d8-4503f20c1e87 · outbound

This paper cites Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-06-29T23:14:01.246428Z

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.

Observation e4fdeacd-38cd-4b6d-a4a7-0520caf1d3bf · outbound

This paper cites an unresolved cited work.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Unresolved cited work

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dcbb4e1-f573-46b3-9483-6483abfb3276 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Learning transferable visual models from natural language supervi- sion

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff31f248-3d6a-4b5e-81d4-4c593ee21b5f · outbound

This paper cites an unresolved cited work.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9182c12f-f9a9-4741-aba1-b8d9beed97e2 · outbound

This paper cites Mind the interference: Retain- ing pre-trained knowledge in parameter-efficient continual learning of vision-language models.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Mind the interference: Retain- ing pre-trained knowledge in parameter-efficient continual learning of vision-language models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e99cd217-1141-419d-a3e3-830843f6fab5 · outbound

This paper cites S-Prompts learning with pre-trained trans- formers: An occam’s razor for domain incremental learn- ing.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning S-Prompts learning with pre-trained trans- formers: An occam’s razor for domain incremental learn- ing

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9511ddbd-0643-4c29-8169-7335367cb76a · outbound

This paper cites Morcos, Hongseok Namkoong, Ali Farhadi, and Ludwig Schmidt.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Morcos, Hongseok Namkoong, Ali Farhadi, and Ludwig Schmidt

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdd21a52-4af7-4c45-b0bd-eee2d0308312 · outbound

This paper cites Boosting continual learning of vision-language models via mixture-of-experts adapters.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Boosting continual learning of vision-language models via mixture-of-experts adapters

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abbd0ea4-53bd-42c4-892b-14231d49d00a · outbound

This paper cites Learning domain invariant prompt for vision- language models.Trans.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Learning domain invariant prompt for vision- language models.Trans

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09ae1768-92c7-412e-8a0c-65c84b378033 · outbound

This paper cites Pre- venting zero-shot transfer degradation in continual learn- ing of vision-language models.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Pre- venting zero-shot transfer degradation in continual learn- ing of vision-language models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-29T23:12:11.283075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c67b5b0c-17a2-45d1-b398-9d06c8e6a113 · outbound

This paper cites Continual Learning with Pre-Trained Models: A Survey.

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning Continual Learning with Pre-Trained Models: A Survey

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-29T23:14:01.242200Z

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.

Pith citing papers

No inbound Pith citation observations are available.