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Paper Citation Record · LEDGER

VisNumBench: Evaluating Number Sense of Multimodal Large Language Models

As of 21 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 2026-08-21T06:32:19.484+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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-18T21:03:31.606674Z digest=sha256:b429107ad488147c6bafc2a77bb511871622e0f11662d046e65301f00e23f94e

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=sha256:2add1c1a168fb8201f8fa3dcb1c8a390038fc37fc8187014d0c117dfd843051c

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-09T14:36:29.666730Z digest=sha256:9b85621bb762fd73f457a079a9a72cac2d6b4f6639899d91c31b4afb29094735

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-12T04:52:09.685243Z digest=sha256:736f8347a57268d4de759ab7bae6301b1f53403ffe6bfae2d2ee1b105da37cac

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-14T19:20:32.435135Z digest=sha256:55651125be8bccaf7a1a8edff700c349b109e6ba9cbada9fc31863eb74a39065