Paper Citation Record · LEDGER

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels

As of 20 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 1 inbound Pith citation observation for arXiv:2505.13788.

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

pith.paper-citation-record.v1
2505.13788 v1

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:16:58.956248Z

measured 66 of 66 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T15:35:30.549656Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T15:36:33.974443Z

Reference resolution

65 of 65 outbound references displayed

verified exact0
verified fuzzy39
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 09dd84bc-e99a-4a68-a73f-d66b0237e582 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T20:16:58.696252Z

Source-reported events for the cited work

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Observation 1d63c4fd-c8bb-4d54-9981-0daeaea3f22b · outbound

This paper cites Language models are few-shot learners.Advances in Neural Information Process- ing Systems, 2020.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Language models are few-shot learners.Advances in Neural Information Process- ing Systems, 2020

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.874434Z

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Observation 416fac4e-da57-43a9-a434-2ea8d99542e1 · outbound

This paper cites Coco- stuff: Thing and stuff classes in context.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Coco- stuff: Thing and stuff classes in context

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.862042Z

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Observation 7f1fb598-e667-4965-96d5-90d1ea1ba6b6 · outbound

This paper cites Masked-attention mask transformer for universal image segmentation.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Masked-attention mask transformer for universal image segmentation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.850081Z

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Observation d15ef60e-8dbe-4eac-a076-3ddc0df88d7b · outbound

This paper cites Gonzalez, Ion Stoica, and Eric P.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Gonzalez, Ion Stoica, and Eric P

Reference 5

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Source-reported events for the cited work

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Observation e51618ff-1578-4644-8119-2a7b89ab50d2 · outbound

This paper cites Scaling instruction- finetuned language models.Journal of Machine Learning Research, 25(70):1–53, 2024.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Scaling instruction- finetuned language models.Journal of Machine Learning Research, 25(70):1–53, 2024

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T20:16:58.716142Z

Source-reported events for the cited work

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Observation d92fd4bc-b7b4-4111-b98f-3405b708bcf1 · outbound

This paper cites InstructBLIP: Towards general-purpose vision-language models with instruction tuning.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels InstructBLIP: Towards general-purpose vision-language models with instruction tuning

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.821046Z

Source-reported events for the cited work

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Observation eae0eda7-602a-4faa-b29d-c3e25a17db16 · outbound

This paper cites Vision-language transformer and query generation for refer- ring segmentation.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Vision-language transformer and query generation for refer- ring segmentation

Reference 8

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Source-reported events for the cited work

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Observation 1a74056c-a561-4845-b66e-2be5685b0bd3 · outbound

This paper cites Segnext: Rethink- ing convolutional attention design for semantic segmenta- tion.Advances in Neural Information Processing Systems, 35:1140–1156, 2022.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Segnext: Rethink- ing convolutional attention design for semantic segmenta- tion.Advances in Neural Information Processing Systems, 35:1140–1156, 2022

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.797079Z

Source-reported events for the cited work

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Observation 19ebaaa3-2ff0-4877-9359-db185a155d36 · outbound

This paper cites Vizwiz grand challenge: Answering visual questions from blind people.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Vizwiz grand challenge: Answering visual questions from blind people

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T20:16:58.731677Z

Source-reported events for the cited work

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Observation bcf17a96-50ac-4f76-864f-71763da138fc · outbound

This paper cites Partimagenet: A large, high- quality dataset of parts.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Partimagenet: A large, high- quality dataset of parts

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.770700Z

Source-reported events for the cited work

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Observation 7df6b6c8-d999-4f66-a59a-7899d8d1774f · outbound

This paper cites Segment any- thing.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Segment any- thing

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.756055Z

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Observation 863d9aef-d4b2-41dc-8ace-95a32f96da2c · outbound

This paper cites Lisa: Reasoning segmentation via large language model.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Lisa: Reasoning segmentation via large language model

Reference 13

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Observation 4e75f98f-0b70-4022-bfb4-3e0cf84c6352 · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 14

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Observation 73940d01-5787-4bff-85ea-6ef3212882e1 · outbound

This paper cites Textbooks Are All You Need II: phi-1.5 technical report.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Textbooks Are All You Need II: phi-1.5 technical report

Reference 15

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Observation a1633b25-78a9-4ad0-80da-509e450d59a6 · outbound

This paper cites Evaluating Object Hallucination in Large Vision-Language Models.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Evaluating Object Hallucination in Large Vision-Language Models

Reference 16

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Observation 67cc99a7-b38e-4e55-a6be-e8572b9dcf5c · outbound

This paper cites A real-time cross-modality correlation fil- tering method for referring expression comprehension.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels A real-time cross-modality correlation fil- tering method for referring expression comprehension

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.720683Z

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Observation 5ddddb08-c1a1-4a0f-bef9-93f07c7bac04 · outbound

This paper cites Microsoft coco: Common objects in context.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Microsoft coco: Common objects in context

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.709218Z

Source-reported events for the cited work

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Observation 9a237f9f-98aa-47a7-badc-941bc952a127 · outbound

This paper cites Gres: Gen- eralized referring expression segmentation.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Gres: Gen- eralized referring expression segmentation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.697485Z

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Observation 1d092265-6276-44b7-b4fb-6e48a3f90470 · outbound

This paper cites Visual instruction tuning.Advances in neural information processing systems, 36, 2023.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Visual instruction tuning.Advances in neural information processing systems, 36, 2023

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.684592Z

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Observation eff0206e-393d-4f22-9c06-8c4144e9c8c2 · outbound

This paper cites Improved baselines with visual instruction tuning.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Improved baselines with visual instruction tuning

Reference 21

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Observation 74ac52eb-a070-47db-b1c5-8beb11a367c3 · outbound

This paper cites Poly- former: Referring image segmentation as sequential poly- gon generation.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Poly- former: Referring image segmentation as sequential poly- gon generation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.663132Z

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Observation 68b6d641-7668-4151-ad63-7a44f01197ef · outbound

This paper cites Grounding dino: Marry- ing dino with grounded pre-training for open-set object de- tection.ECCV, 2024.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Grounding dino: Marry- ing dino with grounded pre-training for open-set object de- tection.ECCV, 2024

Reference 23

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Observation aa706191-db2f-45c3-9bbd-aa5100824b10 · outbound

This paper cites Mmbench: Is your multi-modal model an all-around player? InEuropean conference on computer vi- sion, pages 216–233.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Mmbench: Is your multi-modal model an all-around player? InEuropean conference on computer vi- sion, pages 216–233

Reference 24

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Observation 638043a9-af16-4de3-bc14-354e29fa3d0a · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Swin transformer: Hierarchical vision transformer using shifted windows

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T20:16:58.789570Z

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Observation 0591ee7d-26c4-4864-a719-bf7a4e449334 · outbound

This paper cites Decoupled weight de- cay regularization.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Decoupled weight de- cay regularization

Reference 26

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Observation 0f545b85-dd49-4eb7-baa9-9a7fef71fbe3 · outbound

This paper cites Learn to explain: Multimodal reasoning via thought chains for science question answering.Advances in Neural Information Processing Systems, 35:2507–2521,.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Learn to explain: Multimodal reasoning via thought chains for science question answering.Advances in Neural Information Processing Systems, 35:2507–2521,

Reference 27

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Observation 495f148b-aaee-47c4-975a-2dc6b11ac49c · outbound

This paper cites Generation and comprehension of unambiguous object descriptions.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Generation and comprehension of unambiguous object descriptions

Reference 28

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Observation c378a0cd-837e-4a34-8ecf-503387121e27 · outbound

This paper cites Mod- eling context between objects for referring expression under- standing.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Mod- eling context between objects for referring expression under- standing

Reference 29

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Observation d104872e-ec82-4836-94c7-a272f73ef646 · outbound

This paper cites Ground- ing multimodal large language models to the world.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Ground- ing multimodal large language models to the world

Reference 30

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Observation 92b54a11-894e-4f1e-8fb4-b30f3ffc4db1 · outbound

This paper cites Perceptiongpt: Effectively fusing visual perception into llm.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Perceptiongpt: Effectively fusing visual perception into llm

Reference 31

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Observation 96ad3284-1722-4692-a652-f040e8780eb8 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Learning transferable visual models from natural language supervi- sion

Reference 32

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Observation 78df9661-6317-4dbe-a284-58cccc982189 · outbound

This paper cites Vision language models are blind: Failing to translate detailed visual features into words.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Vision language models are blind: Failing to translate detailed visual features into words

Reference 33

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Observation 17f95633-155f-4e49-ada9-1bd882e23a5d · outbound

This paper cites Paco: Parts and attributes of common objects.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Paco: Parts and attributes of common objects

Reference 34

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Observation 85722242-5d7a-4c35-80c8-adf3ab1399b0 · outbound

This paper cites Learning to lo- calize objects improves spatial reasoning in visual-llms.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Learning to lo- calize objects improves spatial reasoning in visual-llms

Reference 35

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Observation 40476545-e1db-4d61-892a-86128a5eefaa · outbound

This paper cites Glamm: Pixel grounding large multimodal model.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Glamm: Pixel grounding large multimodal model

Reference 36

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Observation 632b7d50-0e95-40e9-a834-df1fcc34cd57 · outbound

This paper cites Sam 2: Segment anything in images and videos,.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Sam 2: Segment anything in images and videos,

Reference 37

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Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks

Reference 38

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Observation 6239ae00-5d23-438b-9e9f-3772eb0f898a · outbound

This paper cites Pixellm: Pixel reasoning with large multimodal model.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Pixellm: Pixel reasoning with large multimodal model

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.488989Z

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Observation 9ef68c60-9c4e-4480-86bc-f34013e8b54c · outbound

This paper cites Eyes wide shut? exploring the visual shortcomings of multimodal llms.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Eyes wide shut? exploring the visual shortcomings of multimodal llms

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.475176Z

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Observation 9a2f73ce-5b07-436c-8fa0-a10b80332c85 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 41

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This paper cites Smith, Daniel Khashabi, and Hannaneh Hajishirzi.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Smith, Daniel Khashabi, and Hannaneh Hajishirzi

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.463018Z

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Observation ca5d86b8-6261-4551-b0ac-0113d0e813f6 · outbound

This paper cites Cris: Clip- driven referring image segmentation.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Cris: Clip- driven referring image segmentation

Reference 43

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This paper cites Gsva: Generalized segmentation via multimodal large language models.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Gsva: Generalized segmentation via multimodal large language models

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.444246Z

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Observation 49981b7a-c443-49b5-8d62-85ba87fb1b9f · outbound

This paper cites Described object detection: Liberating ob- ject detection with flexible expressions.Advances in Neural Information Processing Systems, 36, 2023.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Described object detection: Liberating ob- ject detection with flexible expressions.Advances in Neural Information Processing Systems, 36, 2023

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.430194Z

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Observation bf6f09e9-e25a-4ad4-a635-392d2d4b58c6 · outbound

This paper cites u-LLaVA: Unifying Multi-Modal Tasks via Large Language Model.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels u-LLaVA: Unifying Multi-Modal Tasks via Large Language Model

Reference 46

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Observation 4a11fe01-d78f-439a-a348-5c2bcc1770d3 · outbound

This paper cites Universal instance percep- tion as object discovery and retrieval.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Universal instance percep- tion as object discovery and retrieval

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.416560Z

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Observation c0f872fa-63cf-4518-87fe-a4e545761500 · outbound

This paper cites Lavt: Language-aware vision transformer for referring image segmentation.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Lavt: Language-aware vision transformer for referring image segmentation

Reference 48

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Observation 4f0b568c-c5c1-44a7-b430-f2f978e0c9a7 · outbound

This paper cites Cross-modal self-attention network for referring image seg- mentation.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Cross-modal self-attention network for referring image seg- mentation

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.383640Z

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Observation eb512e66-fed9-4fae-a4e3-ec12d96fd7a8 · outbound

This paper cites Modeling context in referring ex- pressions.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Modeling context in referring ex- pressions

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.367796Z

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Observation 1c129d7c-e875-416b-853c-170fdfce50a0 · outbound

This paper cites Mattnet: Modular at- tention network for referring expression comprehension.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Mattnet: Modular at- tention network for referring expression comprehension

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.349089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b05a6990-4bb2-41d3-8a60-0c3e709790b7 · outbound

This paper cites InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T20:16:58.901751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ba8ef71-1fab-4795-afc3-334ac4aee03c · outbound

This paper cites Psalm: Pixelwise segmentation with large multi-modal model.ECCV, 2024.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Psalm: Pixelwise segmentation with large multi-modal model.ECCV, 2024

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.336296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 938ef0b2-7e23-4d15-ad74-a1309214d717 · outbound

This paper cites Semantic under- standing of scenes through the ade20k dataset.International Journal of Computer Vision, 127:302–321, 2019.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Semantic under- standing of scenes through the ade20k dataset.International Journal of Computer Vision, 127:302–321, 2019

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.314946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 66b180ee-7c13-4264-8123-5b927ead9590 · outbound

This paper cites Seqtr: A simple yet universal network for visual grounding.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Seqtr: A simple yet universal network for visual grounding

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.297994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2d64df02-9f33-4e03-9224-700845df341e · outbound

This paper cites MiniGPT-4: Enhancing vision-language understanding with advanced large language models.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels MiniGPT-4: Enhancing vision-language understanding with advanced large language models

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.280239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a9afa6c4-e6a8-4cd6-8197-f5fbcc5d9e04 · outbound

This paper cites Self-supervised multimodal learning: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Self-supervised multimodal learning: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.267109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cc76aa36-84ac-4c55-8617-f4d0e434c4f5 · outbound

This paper cites African Bush Elephant.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels African Bush Elephant

Reference 58

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T20:16:59.253827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0a367a30-0dd8-450b-9960-592763aefe07 · outbound

This paper cites Example: ”Corgi,” ”Macbook,” ”SUV”.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Example: ”Corgi,” ”Macbook,” ”SUV”

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.240731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f4753a50-ffbd-4c01-ab14-c275b8ae4886 · outbound

This paper cites Example: ”Dog,” ”Computer,” ”Car”.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Example: ”Dog,” ”Computer,” ”Car”

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.222331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fb9810c4-6277-45f4-b69a-2ea6d1c1eec5 · outbound

This paper cites an unresolved cited work.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Unresolved cited work

Reference 61

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:16:59.200238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 16aa896e-2974-4248-845d-4ba7c0797225 · outbound

This paper cites an unresolved cited work.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:16:59.183700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 725cc3dc-de9d-4460-9e94-aae57275f17c · outbound

This paper cites an unresolved cited work.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:16:59.170441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e5066cdb-9dd0-498d-950e-f4f2794c6898 · outbound

This paper cites an unresolved cited work.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:16:59.155350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 58c074a2-72e6-4b46-9b35-4cceb24ce2c5 · outbound

This paper cites (2) text answer: it should be one or a few coherent sentences connecting the objects in (1) that answer the question.

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels (2) text answer: it should be one or a few coherent sentences connecting the objects in (1) that answer the question

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:16:59.141753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation dd59e59a-2026-4416-91d0-e3cdf7aa25c2 · inbound

MINGLE: VLMs for Semantically Complex Region Detection in Urban Scenes cites this paper.

MINGLE: VLMs for Semantically Complex Region Detection in Urban Scenes Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-18T15:36:33.976759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.