Paper Citation Record · LEDGER

InfographicVQA

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2104.12756.

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

pith.paper-citation-record.v1
2104.12756 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:17:27.900588Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:49:18.047840Z

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 c16c13f3-b74c-486a-8ff6-11fc527d18b9 · inbound

OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning cites this paper.

OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning InfographicVQA

Reference 119

Resolution: verified exact; arxiv_id, observed 2026-05-17T20:33:26.875269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cbbfbcab-553b-455a-a67e-1aded7501099 · inbound

Survey on Question Answering over Visually Rich Documents: Methods, Challenges, and Trends cites this paper.

Survey on Question Answering over Visually Rich Documents: Methods, Challenges, and Trends InfographicVQA

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-10T22:17:27.900588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81917d7c-899a-4039-8374-d040546404e5 · inbound

FLARE: Fully Integration of Vision-Language Representations for Deep Cross-Modal Understanding cites this paper.

FLARE: Fully Integration of Vision-Language Representations for Deep Cross-Modal Understanding InfographicVQA

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-22T19:52:01.886765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 27d21c87-cfb0-4cf0-9ce8-3a1f3b7b226f · inbound

Circle-RoPE: Cone-like Decoupled Rotary Positional Embedding for Large Vision-Language Models cites this paper.

Circle-RoPE: Cone-like Decoupled Rotary Positional Embedding for Large Vision-Language Models InfographicVQA

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-22T14:21:39.835811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ec357329-5c77-4802-9e4d-91fd25aa5219 · inbound

Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models cites this paper.

Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models InfographicVQA

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-04T08:15:55.113951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc315a0f-de32-4254-b33f-c504ef33e642 · inbound

IGenBench: Benchmarking the Reliability of Text-to-Infographic Generation cites this paper.

IGenBench: Benchmarking the Reliability of Text-to-Infographic Generation InfographicVQA

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-03T12:06:36.929511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a8f2ebf-1202-40bd-8ece-d5a17c6b85cd · inbound

Kimi K2.5: Visual Agentic Intelligence cites this paper.

Kimi K2.5: Visual Agentic Intelligence InfographicVQA

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-10T16:09:05.339546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 060bf5c0-ab02-4e9d-8812-72eed8a0eecd · inbound

Reconstructing Content with Collaborative Attention for Universal Multimodal Representation Learning cites this paper.

Reconstructing Content with Collaborative Attention for Universal Multimodal Representation Learning InfographicVQA

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T19:41:33.549591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6977d310-e376-4565-881f-16f8d8fec6cc · inbound

Chart-RL: Policy Optimization Reinforcement Learning for Enhanced Visual Reasoning in Chart Question Answering with Vision Language Models cites this paper.

Chart-RL: Policy Optimization Reinforcement Learning for Enhanced Visual Reasoning in Chart Question Answering with Vision Language Models InfographicVQA

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:03:12.121069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3a7fc88e-2bdf-4c7c-ab6e-45ca67073d3d · inbound

Vision-Language Foundation Models for Comprehensive Automated Pavement Condition Assessment cites this paper.

Vision-Language Foundation Models for Comprehensive Automated Pavement Condition Assessment InfographicVQA

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:41:22.806700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a517b7d4-85fb-4cae-84c7-cb1cc995c878 · inbound

Entropy-Gradient Grounding: Training-Free Evidence Retrieval in Vision-Language Models cites this paper.

Entropy-Gradient Grounding: Training-Free Evidence Retrieval in Vision-Language Models InfographicVQA

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:16:10.969368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b10619f3-6942-44e7-afb2-1f900912b75c · inbound

Enginuity: A Dataset and Benchmark for Vision-Language Understanding of Engineering Diagrams cites this paper.

Enginuity: A Dataset and Benchmark for Vision-Language Understanding of Engineering Diagrams InfographicVQA

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T02:26:26.239047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2a552759-cfe3-49c6-a22b-78088ce85eb0 · inbound

MODE: Modality-Decomposed Expert-Level Mixed-Precision Quantization for MoE Multimodal LLMs cites this paper.

MODE: Modality-Decomposed Expert-Level Mixed-Precision Quantization for MoE Multimodal LLMs InfographicVQA

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T17:08:43.719131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5a9c32be-0c02-4617-93f7-9729fd6f1cfb · inbound

PerceptionDLM: Parallel Region Perception with Multimodal Diffusion Language Models cites this paper.

PerceptionDLM: Parallel Region Perception with Multimodal Diffusion Language Models InfographicVQA

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:49:18.049881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c35469fc-3a31-4e53-a0a4-01e99de5bbe6 · inbound

Combating Textual Noise and Redundancy: Entropy-Aware Dense Visual Token Pruning cites this paper.

Combating Textual Noise and Redundancy: Entropy-Aware Dense Visual Token Pruning InfographicVQA

Reference 46

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T14:48:32.359688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 42c284ec-8a14-49c4-8d1a-f6c3308df46d · inbound

Mage-VL: An Efficient Codec-Native Streaming Multimodal Foundation Model cites this paper.

Mage-VL: An Efficient Codec-Native Streaming Multimodal Foundation Model InfographicVQA

Reference 127

Resolution: unresolved; no resolver link, observed 2026-07-31T06:20:14.121564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.