Pith. sign in

Paper Citation Record · LEDGER

Continual Learning with Pre-Trained Models: A Survey

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 24 inbound Pith citation observations for arXiv:2401.16386.

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

pith.paper-citation-record.v1
2401.16386 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 24 of 24 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:22:23.613128Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T02:49:25.503928Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 63daa5a9-fa60-4254-aa5f-607e24452197 · inbound

Sparse Orthogonal Parameters Tuning for Continual Learning cites this paper.

Sparse Orthogonal Parameters Tuning for Continual Learning Continual Learning with Pre-Trained Models: A Survey

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-23T18:08:18.757997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-23T18:06:35.511653Z digest=sha256:b2dc4c98d5dcafa21940adf1c26973371c8e3d94a39273fb895966592ecd183c

Observation 2e33c22e-d8b4-4df0-9864-ae803d7609e0 · inbound

PEARL: Input-Agnostic Prompt Enhancement with Negative Feedback Regulation for Class-Incremental Learning cites this paper.

PEARL: Input-Agnostic Prompt Enhancement with Negative Feedback Regulation for Class-Incremental Learning Continual Learning with Pre-Trained Models: A Survey

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-11T15:34:40.691377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:34:40.691377Z digest=sha256:6db0896247ac4cda39618eefd24a3216faf0fd2d3b2cd88c940553d7647d74b8

Observation cca9855a-196d-4539-9043-d224fcdb7d25 · inbound

Continual Learning Using a Kernel-Based Method Over Foundation Models cites this paper.

Continual Learning Using a Kernel-Based Method Over Foundation Models Continual Learning with Pre-Trained Models: A Survey

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-11T11:22:36.078303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:22:36.078303Z digest=sha256:0b037a324928bb61c7e7aed08497fa42f8c27f9f70d626cdb5bdbf87865c5821

Observation e1eaa1cf-c5e1-4465-a000-e143b1a19a32 · inbound

Expert Routing with Synthetic Data for Continual Learning cites this paper.

Expert Routing with Synthetic Data for Continual Learning Continual Learning with Pre-Trained Models: A Survey

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-11T05:57:31.367933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:57:31.367933Z digest=sha256:9044f947304cea8d743fa620fd67323e6e137214e057ba16270988c43778871c

Observation a550fc61-d0e2-4884-9788-3909c313c737 · inbound

Merging Models on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging cites this paper.

Merging Models on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging Continual Learning with Pre-Trained Models: A Survey

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-10T20:03:11.269607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:03:11.269607Z digest=sha256:dabf0c1f5491d333f071cbfe898c016a734ebab929350a5daa77dc49455dadb6

Observation 7b85f8d2-41bd-481a-99ac-2707619a97d4 · inbound

Enhancing Pre-Trained Model-Based Class-Incremental Learning through Neural Collapse cites this paper.

Enhancing Pre-Trained Model-Based Class-Incremental Learning through Neural Collapse Continual Learning with Pre-Trained Models: A Survey

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-16T10:22:23.613128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:22:23.613128Z digest=sha256:f024180ccbf09a176fcf86efefd123299d5ff6f9af59439c9755c30f4ceb4269

Observation e4c1ca59-0009-4448-b13b-1ad5b0f7b431 · inbound

SplitLoRA: Balancing Stability and Plasticity in Continual Learning Through Gradient Space Splitting cites this paper.

SplitLoRA: Balancing Stability and Plasticity in Continual Learning Through Gradient Space Splitting Continual Learning with Pre-Trained Models: A Survey

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T13:15:59.559585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:15:59.559585Z digest=sha256:0c6603ae245d42da38ce9516fc222dabc9d9e4b9e34702bbf2e9d9bfa7111939

Observation af5d2f8f-10b9-46a4-b37a-c6e271f812b7 · inbound

CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental Learning cites this paper.

CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental Learning Continual Learning with Pre-Trained Models: A Survey

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T12:21:40.298290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:21:40.298290Z digest=sha256:21046ef987fd8e669654a60fc884d37b0aa9196147eed120a5d79a783f612355

Observation 22a8c8f8-8d82-43a1-8a12-e83656aba16c · inbound

Continual Speech Learning with Fused Speech Features cites this paper.

Continual Speech Learning with Fused Speech Features Continual Learning with Pre-Trained Models: A Survey

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T11:46:58.615690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:46:58.615690Z digest=sha256:42c57d0e8438d0e69d303fa0f6cd77b13f83c655e5185362454e7c6a576f63ec

Observation e758f1a4-1de9-4d13-9112-592ce0c88e90 · inbound

Dynamic Mixture of Progressive Parameter-Efficient Expert Library for Lifelong Robot Learning cites this paper.

Dynamic Mixture of Progressive Parameter-Efficient Expert Library for Lifelong Robot Learning Continual Learning with Pre-Trained Models: A Survey

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T10:21:13.972297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:21:13.972297Z digest=sha256:2cdcf525001c9ae4eaeac5669aa60ae2919d4eb894918faf5bad9228e37406a0

Observation 445e163a-4cbc-425f-af63-c632bb9cfd26 · inbound

LifelongPR: Lifelong point cloud place recognition based on sample replay and prompt learning cites this paper.

LifelongPR: Lifelong point cloud place recognition based on sample replay and prompt learning Continual Learning with Pre-Trained Models: A Survey

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-06T17:48:45.728830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:48:45.728830Z digest=sha256:3807dc83a4dbec0fc71c04f87680ae03be089bbdca53892e693133e2876bb580

Observation 7bf6e584-9e3f-4d36-8cd7-c3a05ed3029a · inbound

LTLZinc: a Benchmarking Framework for Continual Learning and Neuro-Symbolic Temporal Reasoning cites this paper.

LTLZinc: a Benchmarking Framework for Continual Learning and Neuro-Symbolic Temporal Reasoning Continual Learning with Pre-Trained Models: A Survey

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-06T14:53:03.803463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:53:03.803463Z digest=sha256:4954e875b2e923235421fefd03f05ad0e7ba4128f9405dcf3ec97225c5705689

Observation 3e70cd54-c9f0-43cc-9d4c-ed8bf1a4afb7 · inbound

Forward-Only Continual Learning cites this paper.

Forward-Only Continual Learning Continual Learning with Pre-Trained Models: A Survey

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-05T12:31:26.042244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:31:26.042244Z digest=sha256:7e74bdf348bad11e3431c46f932c51a7dd26f3adb70aef81237cb392604b6284

Observation 711f0166-de29-4d34-b105-2b9683d500bc · inbound

Collaborative Parameter Learning: Mitigating Forgetting via Parameter-Level Gradient Analysis cites this paper.

Collaborative Parameter Learning: Mitigating Forgetting via Parameter-Level Gradient Analysis Continual Learning with Pre-Trained Models: A Survey

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-16T09:37:41.625079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-16T09:34:23.475942Z digest=sha256:2223451f0b92fc224a2a7b6866dcdba5da0e10e28b0527f860ea4aa0b8b8149f

Observation d6b949e4-61b5-43ad-8053-728b07363198 · inbound

OrthoPhys: Physically Plausible Video Generation with Orthogonal-View Geometry Guidance cites this paper.

OrthoPhys: Physically Plausible Video Generation with Orthogonal-View Geometry Guidance Continual Learning with Pre-Trained Models: A Survey

Reference 10

Resolution
unresolved
no resolver link, observed 2026-07-13T22:30:15.744771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T22:30:15.744771Z digest=sha256:f3c969940f5941a55e176f5f714bccc1ea46b88cb55aeb73a0952c9eb395cc54

Observation d5f23034-14b4-45a4-a37e-358bdd969aa5 · inbound

A Faster Path to Continual Learning cites this paper.

A Faster Path to Continual Learning Continual Learning with Pre-Trained Models: A Survey

Reference 70

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:41:02.630246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T15:23:35.559682Z digest=sha256:0cbd4bebb4f59bdeced32b2c3d79194863e0fbdfaa4e8122772243b02d36dcb2

Observation 40b8f5c1-d8e9-429e-a159-f1d5bb769444 · inbound

HEDP: A Hybrid Energy-Distance Prompt-based Framework for Domain Incremental Learning cites this paper.

HEDP: A Hybrid Energy-Distance Prompt-based Framework for Domain Incremental Learning Continual Learning with Pre-Trained Models: A Survey

Reference 28

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T19:36:15.169382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-08T11:25:01.780099Z digest=sha256:8e7a0ba51fca990f554b2876996a38bc94db3a08b0748ca9f16c0e7f24096640

Observation 5cbffacb-97b6-474d-8372-6390898d1008 · inbound

Beyond Point-wise Neural Collapse: A Topology-Aware Hierarchical Classifier for Class-Incremental Learning cites this paper.

Beyond Point-wise Neural Collapse: A Topology-Aware Hierarchical Classifier for Class-Incremental Learning Continual Learning with Pre-Trained Models: A Survey

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T06:37:26.492340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-13T06:37:19.697078Z digest=sha256:48d3455449a85ad3d55f76ebf5561c42ce2bed6cbca0e98b0132c1f883c11870

Observation cfbac51c-3849-4950-aec5-ea180f3f36d0 · inbound

iGSP:Implicit Gradient Subspace Projection for Efficient Continual Learning of Vision-Language Models cites this paper.

iGSP:Implicit Gradient Subspace Projection for Efficient Continual Learning of Vision-Language Models Continual Learning with Pre-Trained Models: A Survey

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-20T07:18:06.825439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T07:17:49.088846Z digest=sha256:8049374ee1b72432052e494fb7a470f0a3b3efd8def839b129e7d8467305d1af

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

CMAP: Cross-Modal Adaptive Prompting for Multi-Domain Task-Incremental Learning cites this paper.

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-29T23:12:11.283075Z digest=sha256:2eaee67343673eb2c2c40c6d4ed9e9bf4d8b86218117641ab71c851131ef2f9b

Observation e90b80a3-6fa5-4069-99ed-21ee305f59f0 · inbound

A Functional Data Framework For Analyzing Shapes and Textures in Images cites this paper.

A Functional Data Framework For Analyzing Shapes and Textures in Images Continual Learning with Pre-Trained Models: A Survey

Reference 4

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T06:57:43.384887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-27T12:21:09.703003Z digest=sha256:0bdbdd49d6c47fd112ca84a2d53923450e0a3df58a1cf73beeadb4d084ea8861

Observation fb7833af-5fa9-4bf8-a18e-985b172c0ea0 · inbound

Token Factory: Efficiently Integrating Diverse Signals into Large Recommendation Models cites this paper.

Token Factory: Efficiently Integrating Diverse Signals into Large Recommendation Models Continual Learning with Pre-Trained Models: A Survey

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-04T02:49:25.506688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-26T18:49:39.851566Z digest=sha256:10af1346e13e15ea0003541bc6cb9d6280103ed0d8d08bc9cf97a5e28b514d39

Observation 72bb9a6e-8447-4ca8-9e98-c8af29fcc4fb · inbound

Token Factory: Efficiently Integrating Diverse Signals into Large Recommendation Models cites this paper.

Token Factory: Efficiently Integrating Diverse Signals into Large Recommendation Models Continual Learning with Pre-Trained Models: A Survey

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-02T10:53:50.794351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T10:53:50.794351Z digest=sha256:4fd8d01bc042b801ab5cb11053e9ce265ee48a507554711a69a6cf8cf5597454

Observation ebe66f86-75da-4625-bdfb-2a48ce876aa6 · inbound

Miles: Metric Learning with Expandable Subspace for Pre-Trained Model-Based Class-Incremental Learning cites this paper.

Miles: Metric Learning with Expandable Subspace for Pre-Trained Model-Based Class-Incremental Learning Continual Learning with Pre-Trained Models: A Survey

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-01T17:36:21.005158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:36:21.005158Z digest=sha256:deab626f9d3c244ed59b5afef031664a7f53c0ee36a2656d296d8fdb589b400b