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Paper Citation Record · LEDGER

Phantom of Latent for Large Language and Vision Models

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2409.14713.

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

pith.paper-citation-record.v1
2409.14713 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:16:55.180265Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:48:56.182887Z

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 2b7e5b1f-8e55-450c-9c7b-1ecef7080308 · inbound

Enhanced Vision-Language Models for Diverse Sensor Understanding: Cost-Efficient Optimization and Benchmarking cites this paper.

Enhanced Vision-Language Models for Diverse Sensor Understanding: Cost-Efficient Optimization and Benchmarking Phantom of Latent for Large Language and Vision Models

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-10T23:16:55.180265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:16:55.180265Z digest=sha256:3f183968a0c3ae9553617f5378a6900e506472cf87a3e63be2ad134f06200a62

Observation 80ce1837-ed78-4b87-813f-131e2096cdab · inbound

GenRecal: Generation after Recalibration from Large to Small Vision-Language Models cites this paper.

GenRecal: Generation after Recalibration from Large to Small Vision-Language Models Phantom of Latent for Large Language and Vision Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T23:57:23.524940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:57:23.524940Z digest=sha256:4b3759091cdb8c6ffe82617787ecfdb8873032351687869b4ada1384e88d0ec6

Observation d4bbc1ec-b7f9-4911-915f-373b009559f4 · inbound

Agent Explorative Policy Optimization for Multimodal Agentic Reasoning cites this paper.

Agent Explorative Policy Optimization for Multimodal Agentic Reasoning Phantom of Latent for Large Language and Vision Models

Reference 89

Resolution
verified exact
arxiv_id, observed 2026-06-29T12:23:24.082384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-29T12:22:39.655615Z digest=sha256:2d62a3792cb0aaf484f170217397c0cb7ce5646e82ea0c5f84477f9c6bbe9d48

Observation 890a838d-269c-49a4-a9df-8bcc7c8d00ed · inbound

Zone of Proximal Policy Optimization: Teacher in Prompts, Not Gradients cites this paper.

Zone of Proximal Policy Optimization: Teacher in Prompts, Not Gradients Phantom of Latent for Large Language and Vision Models

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-07-03T20:48:56.184470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-27T01:08:52.981296Z digest=sha256:9f1ff3167b9814507f42e91e43de50ec2c7266604162031dc962e06e58616d7c

Observation 36754464-35c7-4a71-8e69-4da5d42dd323 · inbound

Evolution Fine-Tuning: Learning to Discover Across 371 Optimization Tasks cites this paper.

Evolution Fine-Tuning: Learning to Discover Across 371 Optimization Tasks Phantom of Latent for Large Language and Vision Models

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-06-30T09:24:32.776428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-30T09:15:22.900338Z digest=sha256:3d17b63b9c55e4c6b5c74f492382a2bfb1f2cfd9e5aff113407141b7e0cd8bad