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Paper Citation Record · LEDGER

TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2310.05905.

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

pith.paper-citation-record.v1
2310.05905 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:46:48.578203Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T14:19:53.549713Z

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 4ac2866b-b561-463e-9bf7-25e4235fce5d · inbound

Reinforced Refinement with Self-Aware Expansion for End-to-End Autonomous Driving cites this paper.

Reinforced Refinement with Self-Aware Expansion for End-to-End Autonomous Driving TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T04:46:48.578203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:46:48.578203Z digest=sha256:cd59b6e4304db1ba9cf7de81536c35955112172dec697c7630decf2bf5d1968b

Observation 4adfbc67-45c4-49ad-975e-7219f300b6bd · inbound

Continually Evolving Skill Knowledge in Vision Language Action Model cites this paper.

Continually Evolving Skill Knowledge in Vision Language Action Model TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-17T06:04:09.227685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-17T06:02:31.638120Z digest=sha256:de1cf78dd685ceeb8e3a117207c892e6fa4bd30056299d5eadfff4b6ab832b24

Observation e5d8a19b-aa6d-4916-b4eb-8b504b3e16c4 · inbound

CLARE: Continual Learning for Vision-Language-Action Models via Autonomous Adapter Routing and Expansion cites this paper.

CLARE: Continual Learning for Vision-Language-Action Models via Autonomous Adapter Routing and Expansion TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-21T15:54:14.481365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T15:53:44.767068Z digest=sha256:4b7eff88c11e1084e4c06ef0873e863f8052215401144fcbb3d96eb79cf60505

Observation e0a4b505-b59b-4fe0-a4de-61bcfe9b1cb2 · inbound

Towards Long-Lived Robots: Continual Learning VLA Models via Reinforcement Fine-Tuning cites this paper.

Towards Long-Lived Robots: Continual Learning VLA Models via Reinforcement Fine-Tuning TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-21T14:10:13.273322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T14:07:10.387869Z digest=sha256:3776faa3a655f14eb1b37a6442eb0117ede020e6dc7216efa890fe20848a61de

Observation 9a3591db-b648-4a7f-ac82-8bd942349592 · inbound

Revitalizing the Beginning: Avoiding Storage Dependency for Model Merging in Continual Learning cites this paper.

Revitalizing the Beginning: Avoiding Storage Dependency for Model Merging in Continual Learning TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models

Reference 38

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T08:01:31.589524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-12T01:22:29.333350Z digest=sha256:2f2c9270d13f4f5b14620e6cb52f131b4a7a59ad08d9f9fdbfbe1ebd5ef49401

Observation eda7bb71-ecfa-40f7-8af7-a2964496a5ae · inbound

Efficient Skill Grounding via Code Refactoring with Small Language Models cites this paper.

Efficient Skill Grounding via Code Refactoring with Small Language Models TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models

Reference 94

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T21:07:24.122091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T19:55:20.212198Z digest=sha256:07ebc8c62878fd115b4002433c82b6b22d9af7aa7d2ee2e7ea53d2c4df72ee78

Observation b146deac-d448-4363-96b2-279eab89708a · inbound

World Action Models Enable Continual Imitation Learning with Recurrent Generative Replays cites this paper.

World Action Models Enable Continual Imitation Learning with Recurrent Generative Replays TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-04T14:19:53.551521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T04:20:26.522615Z digest=sha256:64ddf56493ce2de49a3a3e69340fd58dd2733aef3eca6b2be5879f46e9458e24