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Paper Citation Record · LEDGER

VisNumBench: Evaluating Number Sense of Multimodal Large Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2503.14939.

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

pith.paper-citation-record.v1
2503.14939 v2

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 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:18:45.699326Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T21:06:50.827087Z

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 b9bf60ec-d0b4-4ef7-a010-e50bf0495250 · inbound

Self-Rewarding Vision-Language Model via Reasoning Decomposition cites this paper.

Self-Rewarding Vision-Language Model via Reasoning Decomposition VisNumBench: Evaluating Number Sense of Multimodal Large Language Models

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-18T21:06:50.831375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T21:03:31.606674Z digest=sha256:f13f177c4689d784bc69046ad3234c7f66122fdd60803005292dcd89e2ef78c4

Observation 49e3d848-5bca-4379-ba46-518088999649 · inbound

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study cites this paper.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study VisNumBench: Evaluating Number Sense of Multimodal Large Language Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-05T15:18:45.699326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:18:45.699326Z digest=sha256:b298ba8e9517c9f01f8e938711059bb1d8688caacc3194099c73a06fc5e628c5

Observation 5abb1eeb-95bc-4bca-945c-42d17cb041ee · inbound

Injecting Distributional Awareness into MLLMs via Reinforcement Learning for Deep Imbalanced Regression cites this paper.

Injecting Distributional Awareness into MLLMs via Reinforcement Learning for Deep Imbalanced Regression VisNumBench: Evaluating Number Sense of Multimodal Large Language Models

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T16:51:09.271975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-09T14:36:29.666730Z digest=sha256:0641a9264565205c4584263cb99f6dd3ef2c7c0f55995b390605632a96da48c9

Observation 2c0c079d-fb90-4256-bb07-1bdf85d06b5a · inbound

Injecting Distributional Awareness into MLLMs via Reinforcement Learning for Deep Imbalanced Regression cites this paper.

Injecting Distributional Awareness into MLLMs via Reinforcement Learning for Deep Imbalanced Regression VisNumBench: Evaluating Number Sense of Multimodal Large Language Models

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T05:51:26.163884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-12T04:52:09.685243Z digest=sha256:b0be64749cf4dde9526f76a025081196b6f6f9b401d877fd37175fd4181272b0

Observation 25aeae73-3d86-4246-861b-ef013b3ecebe · inbound

PDCR: Perception-Decomposed Confidence Reward for Vision-Language Reasoning cites this paper.

PDCR: Perception-Decomposed Confidence Reward for Vision-Language Reasoning VisNumBench: Evaluating Number Sense of Multimodal Large Language Models

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-14T19:22:50.586545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-14T19:20:32.435135Z digest=sha256:e45ce90736ad1b906b5ef7b9d82c0289c84fd680e2c8af83910a2c8dd908de0c