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Paper Citation Record · LEDGER

Few-Shot VQA with Frozen LLMs: A Tale of Two Approaches

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.11317.

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

pith.paper-citation-record.v1
2403.11317 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:19:28.012291Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T23:51:14.958583Z

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 9456c65a-abeb-453f-9fa3-3abb9d4f8dce · inbound

VideoICL: Confidence-based Iterative In-context Learning for Out-of-Distribution Video Understanding cites this paper.

VideoICL: Confidence-based Iterative In-context Learning for Out-of-Distribution Video Understanding Few-Shot VQA with Frozen LLMs: A Tale of Two Approaches

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-11T23:51:14.966231Z

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=2026-08-11T23:51:14.658083Z digest=sha256:1f95f271baf4bcce72ad49257b5789db421430a8676b581756c58ec62c1879ed

Observation ae1b858d-79f7-455e-9931-a432d0ef8c8d · inbound

FEALLM: Advancing Facial Emotion Analysis in Multimodal Large Language Models with Emotional Synergy and Reasoning cites this paper.

FEALLM: Advancing Facial Emotion Analysis in Multimodal Large Language Models with Emotional Synergy and Reasoning Few-Shot VQA with Frozen LLMs: A Tale of Two Approaches

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T20:19:28.012291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:19:28.012291Z digest=sha256:cf5f244370b19d0adfa371c3596a97f9ab2e61c3265579b4e9382161e5c8f280