Paper Citation Record · LEDGER

Frozen Transformers in Language Models Are Effective Visual Encoder Layers

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2310.12973.

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

pith.paper-citation-record.v1
2310.12973 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:27:47.850784Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T21:17:16.309288Z

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 44a79545-f84a-48d1-b7e1-3e371bc2b1f5 · inbound

A non-ergodic framework for understanding emergent capabilities in Large Language Models cites this paper.

A non-ergodic framework for understanding emergent capabilities in Large Language Models Frozen Transformers in Language Models Are Effective Visual Encoder Layers

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-10T22:27:47.850784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60c0cdfb-23a2-41a8-afea-2df919149701 · inbound

Embodied Intelligence for 3D Understanding: A Survey on 3D Scene Question Answering cites this paper.

Embodied Intelligence for 3D Understanding: A Survey on 3D Scene Question Answering Frozen Transformers in Language Models Are Effective Visual Encoder Layers

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-09T19:24:17.930017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39aa0589-0cce-45bf-95ad-a2044ceaac7c · inbound

Pre-Trained LLM is a Semantic-Aware and Generalizable Segmentation Booster cites this paper.

Pre-Trained LLM is a Semantic-Aware and Generalizable Segmentation Booster Frozen Transformers in Language Models Are Effective Visual Encoder Layers

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T23:28:15.348279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7df17b61-bd53-4908-bfe4-0825ff4c8666 · inbound

Language-Unlocked ViT (LUViT): Empowering Self-Supervised Vision Transformers with LLMs cites this paper.

Language-Unlocked ViT (LUViT): Empowering Self-Supervised Vision Transformers with LLMs Frozen Transformers in Language Models Are Effective Visual Encoder Layers

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:17:16.472633Z

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.