Paper Citation Record · LEDGER

VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2207.00221.

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

pith.paper-citation-record.v1
2207.00221 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:19:45.886327Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-07T20:44:09.047810Z

Reference resolution

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Outbound references

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Pith citing papers

Observation f76ee1ca-8be6-4b4d-8d62-c1543f2210fa · inbound

Decompose and Leverage Preferences from Expert Models for Improving Trustworthiness of MLLMs cites this paper.

Decompose and Leverage Preferences from Expert Models for Improving Trustworthiness of MLLMs VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-12T16:19:45.886327Z

Source-reported events for the cited work

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Observation a418555b-8f7d-4cb4-8f58-b38d546dc182 · inbound

Seeing Syntax: Uncovering Syntactic Learning Limitations in Vision-Language Models cites this paper.

Seeing Syntax: Uncovering Syntactic Learning Limitations in Vision-Language Models VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-11T18:17:18.657659Z

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Observation 06c6fe06-7548-4ce7-b2f1-1f808c4ebe90 · inbound

Progressive Multi-granular Alignments for Grounded Reasoning in Large Vision-Language Models cites this paper.

Progressive Multi-granular Alignments for Grounded Reasoning in Large Vision-Language Models VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-11T18:17:06.258515Z

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Observation 2df23896-35c7-4108-b3f5-1628aab206ea · inbound

Causal Graphical Models for Vision-Language Compositional Understanding cites this paper.

Causal Graphical Models for Vision-Language Compositional Understanding VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T17:10:44.372152Z

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Observation 7b581a1c-981d-4577-bf25-65524f03fa8f · inbound

Decomposing Complex Visual Comprehension into Atomic Visual Skills for Vision Language Models cites this paper.

Decomposing Complex Visual Comprehension into Atomic Visual Skills for Vision Language Models VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-07T14:05:41.725304Z

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Observation e405d9a0-45e7-4a0e-a115-2c5228d7f9f2 · inbound

What's Missing in Vision-Language Models? Probing Their Struggles with Causal Order Reasoning cites this paper.

What's Missing in Vision-Language Models? Probing Their Struggles with Causal Order Reasoning VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T12:00:18.753401Z

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Observation 42821a0d-6d10-4218-a568-1379fe734f45 · inbound

A Good CREPE needs more than just Sugar: Investigating Biases in Compositional Vision-Language Benchmarks cites this paper.

A Good CREPE needs more than just Sugar: Investigating Biases in Compositional Vision-Language Benchmarks VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T05:21:35.157557Z

Source-reported events for the cited work

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Observation e0bd20ed-6479-47b0-bb65-0026b8d5f9d2 · inbound

CF-VLM:CounterFactual Vision-Language Fine-tuning cites this paper.

CF-VLM:CounterFactual Vision-Language Fine-tuning VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:07.140504Z

Source-reported events for the cited work

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Observation 3ccfcbb2-0c3b-4b86-ac09-df84f94e9a8b · inbound

Do Vision-Language Models Have Internal World Models? Towards an Atomic Evaluation cites this paper.

Do Vision-Language Models Have Internal World Models? Towards an Atomic Evaluation VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T22:22:37.649660Z

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Observation b54f18df-cf1d-496b-8186-365b28cf9c0a · inbound

A Visual Leap in CLIP Compositionality Reasoning through Generation of Counterfactual Sets cites this paper.

A Visual Leap in CLIP Compositionality Reasoning through Generation of Counterfactual Sets VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:53.011960Z

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Observation 6460b670-f6d7-44a2-9ea5-af64b6d2838c · inbound

Can VLMs Reason Robustly? A Neuro-Symbolic Investigation cites this paper.

Can VLMs Reason Robustly? A Neuro-Symbolic Investigation VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-13T19:17:12.798847Z

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Observation a32aa503-64ed-4cca-ac3d-733737cd2430 · inbound

All in One: A Unified Synthetic Data Pipeline for Multimodal Video Understanding cites this paper.

All in One: A Unified Synthetic Data Pipeline for Multimodal Video Understanding VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 106

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:31:03.860342Z

Source-reported events for the cited work

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Observation 15c11f3d-0ed5-49cb-b08a-6ea5281eac64 · inbound

Concrete Jungle: Towards Concreteness Paved Contrastive Negative Mining for Compositional Understanding cites this paper.

Concrete Jungle: Towards Concreteness Paved Contrastive Negative Mining for Compositional Understanding VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:36:04.985463Z

Source-reported events for the cited work

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Observation 53fbf125-c7e9-4ec0-84c5-e10536b15f1c · inbound

DO-Bench: An Attributable Benchmark for Diagnosing Object Hallucination in Vision-Language Models cites this paper.

DO-Bench: An Attributable Benchmark for Diagnosing Object Hallucination in Vision-Language Models VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 43

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:36:36.527792Z

Source-reported events for the cited work

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Observation b19db82b-644c-4afe-bfda-2e8a4cad5b6b · inbound

Cross-Modal Masked Compositional Concept Modeling for Enhancing Visio-Linguistic Compositionality cites this paper.

Cross-Modal Masked Compositional Concept Modeling for Enhancing Visio-Linguistic Compositionality VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T14:28:31.484644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 32673b3f-e221-4c90-a8fa-5f2088c1bd37 · inbound

HyFL-CLIP: Hyperbolic Fine-Tuning of CLIP for Robust Long-Context Understanding cites this paper.

HyFL-CLIP: Hyperbolic Fine-Tuning of CLIP for Robust Long-Context Understanding VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 81

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T15:17:07.117700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b4105ae4-4d75-4c85-b84d-a6f71f50aedc · inbound

Is the Geometry Doing the Work? An Operating-Point Audit of Hierarchy in Hyperbolic Vision-Language Models cites this paper.

Is the Geometry Doing the Work? An Operating-Point Audit of Hierarchy in Hyperbolic Vision-Language Models VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 30

Resolution: metadata mismatch; local_arxiv, observed 2026-07-07T20:44:09.056579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a3a95dcf-3f05-4d4f-8d53-d081e05c16cb · inbound

Is the Geometry Doing the Work? An Operating-Point Audit of Hierarchy in Hyperbolic Vision-Language Models cites this paper.

Reference 30

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Observation 6a600bcf-6fe0-42fc-be01-71f7d9b3e9e3 · inbound

Is the Geometry Doing the Work? An Operating-Point Audit of Hierarchy in Hyperbolic Vision-Language Models cites this paper.

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T08:32:59.699718Z

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Observation d8815c50-dd81-4662-b334-57cfb1ad0e28 · inbound

Medical-Checklist: Assessing the Comprehension of Medical Images by Multimodal Models cites this paper.

Medical-Checklist: Assessing the Comprehension of Medical Images by Multimodal Models VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T06:09:22.367179Z

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Observation e4d9758e-34a0-445b-9616-93d4ca47a694 · inbound

EEG-EditBench: Probing Visual Information in EEG-Image Retrieval Models with Controlled Image Edits cites this paper.

EEG-EditBench: Probing Visual Information in EEG-Image Retrieval Models with Controlled Image Edits VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T00:14:11.250291Z

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Unavailable: canonical work link unavailable.