Paper Citation Record · LEDGER

Componential Prompt-Knowledge Alignment for Domain Incremental Learning

As of 18 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 2 inbound Pith citation observations for arXiv:2505.04575.

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

pith.paper-citation-record.v1
2505.04575 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:27:49.916237Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:08:17.573455Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T06:13:59.687129Z

Reference resolution

34 of 34 outbound references displayed

verified exact0
verified fuzzy32
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 57312602-1158-4dc9-b173-b19f4ce8b30b · outbound

This paper cites Prototype-sample relation distillation: towards replay-free continual learning.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Prototype-sample relation distillation: towards replay-free continual learning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.436348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 20a3bc19-bf7e-4fb4-bc4b-98042356e4c6 · outbound

This paper cites Mind: Multi-task incremental network distillation.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Mind: Multi-task incremental network distillation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.422606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 58b4f536-f35c-45ef-b81a-5dd37f91e2ee · outbound

This paper cites On the stability-plasticity dilemma in continual meta-learning: theory and algorithm.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning On the stability-plasticity dilemma in continual meta-learning: theory and algorithm

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.408953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 00f8ba25-bbe8-41b0-a16f-9110c16b4624 · outbound

This paper cites Cp-prompt: Composition-based cross-modal prompting for domain-incremental continual learning.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Cp-prompt: Composition-based cross-modal prompting for domain-incremental continual learning

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.394049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 503e8899-09e3-4b80-a814-11899523acf1 · outbound

This paper cites an unresolved cited work.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-15T23:27:50.380126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f624a722-aeff-4177-9d74-162365df9efd · outbound

This paper cites Greedy poisson rejection sampling.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Greedy poisson rejection sampling

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.364770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6c487a2e-b2c4-453a-bf99-f06fa35f94da · outbound

This paper cites Consistent prompting for rehearsal-free continual learning.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Consistent prompting for rehearsal-free continual learning

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.349929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 407cb215-5880-4ca0-b453-ba9fad2e8c8a · outbound

This paper cites Person re-identification method based on color attack and joint defence.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Person re-identification method based on color attack and joint defence

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.334399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e12fb1d5-e9cb-42fa-b746-337d3d34ee3d · outbound

This paper cites Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T23:27:49.801945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c24043d2-2d5f-48d1-8d0a-a23fbbfc9eaa · outbound

This paper cites The many faces of robustness: A critical analysis of out-of-distribution generalization.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning The many faces of robustness: A critical analysis of out-of-distribution generalization

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.320033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0cd9e18b-22f9-4381-853e-045568cff96d · outbound

This paper cites Gradual di- vergence for seamless adaptation: A novel domain in- cremental learning method.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Gradual di- vergence for seamless adaptation: A novel domain in- cremental learning method

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.305935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dcd1690a-5509-4c53-bcf1-8c7c6424288a · outbound

This paper cites and Choi, D.-W.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning and Choi, D.-W

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.292019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 97586b84-71bc-4f92-a8ef-46ae082c2b3b · outbound

This paper cites Overcoming catastrophic forgetting in neural networks.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Overcoming catastrophic forgetting in neural networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.277782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7e79c305-560c-4339-8b04-a47e487d8799 · outbound

This paper cites Clustering-based domain- incremental learning.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Clustering-based domain- incremental learning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.263293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bc29ca6c-4d4b-4110-9d88-82f2015a9ad1 · outbound

This paper cites Person- alized federated domain-incremental learning based on adaptive knowledge matching.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Person- alized federated domain-incremental learning based on adaptive knowledge matching

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.249067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7de416a8-3bcd-499a-aee0-ad7da4387b20 · outbound

This paper cites and Hoiem, D.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning and Hoiem, D

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.234885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a03910dc-3de9-4a26-a735-7150d99ac22b · outbound

This paper cites and Li, W.-J.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning and Li, W.-J

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.220596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 37624081-e36f-4ab0-9392-0b6b50c248f5 · outbound

This paper cites Stop: Integrated spatial-temporal dynamic prompting for video understanding.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Stop: Integrated spatial-temporal dynamic prompting for video understanding

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.206909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e0b0e866-a3df-4700-b57c-42583f449b24 · outbound

This paper cites J., Masana, M., Possegger, H., and Bischof, H.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning J., Masana, M., Possegger, H., and Bischof, H

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.193135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 237641c1-ddad-48b5-9479-fcc98af80b51 · outbound

This paper cites and Wolf, L.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning and Wolf, L

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.177940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0e791036-8cc3-4b54-96fe-7846e861a9bc · outbound

This paper cites Moment matching for multi-source domain adaptation.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Moment matching for multi-source domain adaptation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.163545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b11be6f2-5e4c-44c7-b3f1-e50d188db554 · outbound

This paper cites Learning prompt- enhanced context features for weakly-supervised video anomaly detection.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Learning prompt- enhanced context features for weakly-supervised video anomaly detection

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.149602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3ab767a9-6cd7-459b-87ec-660186c0e618 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Learning transferable visual models from natural language supervision

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.135453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 41f56964-dccd-406f-84b5-2e5dd9c8e8b3 · outbound

This paper cites Vision transformers with mixed-resolution tokenization.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Vision transformers with mixed-resolution tokenization

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.121322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2fa5031b-d826-4cf4-912b-760da7bdd317 · outbound

This paper cites and Wang, H.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning and Wang, H

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.107110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4bfb60f2-dfa4-46f9-ae41-9276ff5d9a87 · outbound

This paper cites Coda-prompt: Continual decomposed attention-based prompting for rehearsal-free continual learning.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Coda-prompt: Continual decomposed attention-based prompting for rehearsal-free continual learning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.092519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5e7160df-d53d-4cb8-979d-5819745c29e0 · outbound

This paper cites Non-exemplar domain incremental object detection via learning domain bias.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Non-exemplar domain incremental object detection via learning domain bias

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.078393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 32004d17-1a5a-44f9-95df-917db27a02aa · outbound

This paper cites Non-exemplar domain incremental learning via cross- domain concept integration.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Non-exemplar domain incremental learning via cross- domain concept integration

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.063864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7b5d10b8-3f3f-4f76-8700-d64e78aa9240 · outbound

This paper cites Not all images are worth 16x16 words: Dynamic transformers for efficient image recognition.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Not all images are worth 16x16 words: Dynamic transformers for efficient image recognition

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.048525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fa2c6bf2-a18d-462f-937c-ba31adf0a16e · outbound

This paper cites General incremental learn- ing with domain-aware categorical representations.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning General incremental learn- ing with domain-aware categorical representations

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.032111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4b1722b5-9240-48b4-a85b-e59bf83d4dcb · outbound

This paper cites Dask: Distribution rehearsing via adaptive style kernel learning for exemplar-free lifelong person re-identification.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Dask: Distribution rehearsing via adaptive style kernel learning for exemplar-free lifelong person re-identification

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.017286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation abc0c6f3-530c-4401-8d6d-5a12b3d9591c · outbound

This paper cites Mma-diffusion: Multimodal attack on diffusion models.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Mma-diffusion: Multimodal attack on diffusion models

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:50.001050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ea7a1e02-bcd0-48ee-9d21-427fcc3b9dc0 · outbound

This paper cites Scap: Transductive test-time adaptation via supportive clique-based attribute prompting.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Scap: Transductive test-time adaptation via supportive clique-based attribute prompting

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:49.986389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 69546968-e885-4ba2-930c-f5c95f77ffa2 · outbound

This paper cites Revisiting class-incremental learning with pre- trained models: Generalizability and adaptivity are all you need.

Componential Prompt-Knowledge Alignment for Domain Incremental Learning Revisiting class-incremental learning with pre- trained models: Generalizability and adaptivity are all you need

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:27:49.969092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation 0c1b2a03-2f2e-4060-82f6-33de957b6a60 · inbound

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis cites this paper.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Componential Prompt-Knowledge Alignment for Domain Incremental Learning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T18:08:17.573455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1a71fa6-3a3d-4851-badc-6583b36dbde4 · inbound

STAR-IOD: Scale-decoupled Topology Alignment with Pseudo-label Refinement for Remote Sensing Incremental Object Detection cites this paper.

STAR-IOD: Scale-decoupled Topology Alignment with Pseudo-label Refinement for Remote Sensing Incremental Object Detection Componential Prompt-Knowledge Alignment for Domain Incremental Learning

Reference 227

Resolution: verified exact; arxiv_id, observed 2026-05-21T06:13:59.688938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.