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Paper Citation Record · LEDGER

Modality-Aware Integration with Large Language Models for Knowledge-based Visual Question Answering

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.12728.

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

pith.paper-citation-record.v1
2402.12728 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 2026-08-15T06:32:42.880941+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T00:29:01.924017Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T19:36:08.125297Z

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 2a197725-cb20-4dfb-8efa-c94d7b9d4e32 · inbound

Continually Evolved Multimodal Foundation Models for Cancer Prognosis cites this paper.

Continually Evolved Multimodal Foundation Models for Cancer Prognosis Modality-Aware Integration with Large Language Models for Knowledge-based Visual Question Answering

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-10T00:29:01.924017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T00:29:01.924017Z digest=sha256:839dc5f4a59dd63054f66122e6ac18b3ffe0d593644d92e04fffeeccf9595f46

Observation 7e4e6017-ad7b-494b-b0ad-dd60d76c5e64 · inbound

Enhancing Large Language Models with Reliable Knowledge Graphs cites this paper.

Enhancing Large Language Models with Reliable Knowledge Graphs Modality-Aware Integration with Large Language Models for Knowledge-based Visual Question Answering

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:57.882503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:42:57.882503Z digest=sha256:9807f7522f7465a9f5d4a627105a1f1afedad77b2aa16fb73b1312cd2f84ce9c

Observation 59d06462-9fae-4aec-b7b7-9174518b19e5 · inbound

EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval cites this paper.

EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval Modality-Aware Integration with Large Language Models for Knowledge-based Visual Question Answering

Reference 259

Resolution
verified exact
arxiv_id, observed 2026-05-10T05:56:11.526118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-10T05:43:04.813867Z digest=sha256:3ee7bb03aa9b42d9655cf07c192fcd59de2b6c56686f4b1a0b50e5f3822a4cac

Observation bd25185a-4aab-40c4-b79b-1b75d9b76932 · inbound

MoG: Mixture of Experts for Graph-based Retrieval-Augmented Generation cites this paper.

MoG: Mixture of Experts for Graph-based Retrieval-Augmented Generation Modality-Aware Integration with Large Language Models for Knowledge-based Visual Question Answering

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-07-01T19:36:08.127217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-28T22:24:25.409345Z digest=sha256:be779f1ffeb0eed058cbf8b6fa2088a03827e36f9478e0d67c318baffde67948