Pith. sign in

Paper Citation Record · LEDGER

RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models

As of 10 August 2026, this Paper Citation Record lists 1 of 1 outbound references and 8 inbound Pith citation observations for arXiv:2508.02062.

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

pith.paper-citation-record.v1
2508.02062 v1

Coverage vector

measured 1 of 1 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:15:16.940030Z

measured 9 of 9 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:15:16.940030Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T21:00:09.616475Z

Reference resolution

1 of 1 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 83bfa36c-c890-4f31-b891-351aa34cd6e4 · outbound

This paper cites RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models.

RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T05:15:16.940030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:15:16.940030Z digest=sha256:ac3d670b4c3132da207d9b19e6528be77e589ec9b1fff67f7a7c95c1884ed05c

Pith citing papers

Observation 83bfa36c-c890-4f31-b891-351aa34cd6e4 · inbound

RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models cites this paper.

RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T05:15:16.940030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:15:16.940030Z digest=sha256:ac3d670b4c3132da207d9b19e6528be77e589ec9b1fff67f7a7c95c1884ed05c

Observation 6f9e3fb2-2f4b-4f51-8dde-23275b7f18c2 · inbound

MimicDroid: In-Context Learning for Humanoid Robot Manipulation from Human Play Videos cites this paper.

MimicDroid: In-Context Learning for Humanoid Robot Manipulation from Human Play Videos RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-04T18:51:36.024764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T18:51:36.024764Z digest=sha256:e47c6f22860e8745a0a9e213ab0c9c55734377bba5204c9fe474f17c509f714c

Observation 3f4b1469-c9b3-4625-86d8-ce2570eea0e5 · inbound

Bring My Cup! Personalizing Vision-Language-Action Models with Visual Attentive Prompting cites this paper.

Bring My Cup! Personalizing Vision-Language-Action Models with Visual Attentive Prompting RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-03T14:34:25.752891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:34:25.752891Z digest=sha256:3f024360db7c8577193125a964da678724f16cc56fc30a821d3d09359103080b

Observation 1896cdf3-5e22-4e8c-a9c6-7c1d7bb127fa · inbound

Escaping the Diversity Trap in Robotic Manipulation via Anchor-Centric Adaptation cites this paper.

Escaping the Diversity Trap in Robotic Manipulation via Anchor-Centric Adaptation RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models

Reference 69

Resolution
verified exact
arxiv_id, observed 2026-05-11T02:25:53.173759Z

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.

source=arxiv_source observed=2026-05-11T02:25:23.710842Z digest=sha256:e1e225006acbc7173e214ecadefb9e01f2566818e2018bb8acaf4d3721074a53

Observation 874b7ff4-3b2c-4cd7-aad1-ed0cdc6132af · inbound

FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation cites this paper.

FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models

Reference 61

Resolution
verified exact
arxiv_id, observed 2026-07-04T03:29:30.457937Z

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.

source=arxiv_source observed=2026-06-26T18:01:08.616612Z digest=sha256:f8603c3d48df1871a697c6f50feeea694f01c1123fdb2d60d87591ce7736b999

Observation 1e2ccc34-4f3d-4b58-9517-9a5a7bcdda26 · inbound

In-Context World Modeling for Robotic Control cites this paper.

In-Context World Modeling for Robotic Control RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T21:00:09.618256Z

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.

source=pdf_text observed=2026-06-25T19:12:22.513577Z digest=sha256:70901c18d1a4e810aca3f5675a89d9ebee713534991b25c067c4a6d11796dcae

Observation 40733947-80bb-4553-885e-9502c3b2e8d6 · inbound

In-Context World Modeling for Robotic Control cites this paper.

In-Context World Modeling for Robotic Control RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T13:29:51.643045Z

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.

source=pdf_text observed=2026-06-26T05:11:07.089829Z digest=sha256:087f00b9b232bf091757a82cbf01ec5ad82d09f3ac32088086f70dc4bd89c5be

Observation 991f3055-7b1e-4e86-b084-7f627d3266ab · inbound

In-Context World Modeling for Robotic Control cites this paper.

In-Context World Modeling for Robotic Control RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-07-12T12:05:57.682386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T12:05:57.682386Z digest=sha256:6c4218bef761fbba3e86a29022c72b066e0eebc67097f62209f704ac2943cd97