Vision-Language Grounding as Bidirectional Concept Correspondence | Paper Citation Record

Observation a42b76bf-1cfe-4317-8a5c-a46d102f6d8e · outbound

This paper cites Smith, Hannaneh Hajishirzi, Ross Girshick, Ali Farhadi, and Aniruddha Kembhavi.

Vision-Language Grounding as Bidirectional Concept Correspondence Smith, Hannaneh Hajishirzi, Ross Girshick, Ali Farhadi, and Aniruddha Kembhavi

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:40.224535Z

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Observation 0da74421-f914-4eba-b191-0ecc1b6324fb · outbound

This paper cites Molmo2: Open weights and data for vision-language models with video understanding and grounding, 2026.

Vision-Language Grounding as Bidirectional Concept Correspondence Molmo2: Open weights and data for vision-language models with video understanding and grounding, 2026

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.602120Z

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Observation 0d8618f7-da09-4da1-a378-680acfce865c · outbound

This paper cites Molmopoint: Better pointing for vlms with grounding tokens.arXiv preprint arXiv:2603.28069, 2026.

Vision-Language Grounding as Bidirectional Concept Correspondence Molmopoint: Better pointing for vlms with grounding tokens.arXiv preprint arXiv:2603.28069, 2026

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.608089Z

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Observation 66de1c08-f1cb-40b4-b1cb-e060113ae781 · outbound

This paper cites Modeling context in referring expressions.

Vision-Language Grounding as Bidirectional Concept Correspondence Modeling context in referring expressions

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.613911Z

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Observation e0b4e406-1737-4ae7-a2d3-9020be4852e4 · outbound

This paper cites Generation and comprehension of unambiguous object descriptions.

Vision-Language Grounding as Bidirectional Concept Correspondence Generation and comprehension of unambiguous object descriptions

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.618665Z

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Observation 9a4312cc-44bf-460c-a6c8-e2453b8ba94d · outbound

This paper cites Modeling context between objects for referring expression understanding.

Vision-Language Grounding as Bidirectional Concept Correspondence Modeling context between objects for referring expression understanding

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.624092Z

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Observation adabe624-e8d7-4177-bf97-0a44d01ee053 · outbound

This paper cites Referring relationships.

Vision-Language Grounding as Bidirectional Concept Correspondence Referring relationships

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:40.168590Z

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Observation 184ca318-d921-438b-b73f-68dc0a3b0876 · outbound

This paper cites Referitgame: Referring to objects in photographs of natural scenes.

Vision-Language Grounding as Bidirectional Concept Correspondence Referitgame: Referring to objects in photographs of natural scenes

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.634193Z

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Observation 43ee5f8e-a942-4e15-b378-19a5675e0c8a · outbound

This paper cites Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models.

Vision-Language Grounding as Bidirectional Concept Correspondence Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.639144Z

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Observation fe7e47d9-79fc-495d-b427-85e69978b255 · outbound

This paper cites Phrasecut: Language-based image segmentation in the wild.

Vision-Language Grounding as Bidirectional Concept Correspondence Phrasecut: Language-based image segmentation in the wild

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:40.129902Z

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Observation d7db2878-97fa-4012-ae06-1a882c876e72 · outbound

This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

Vision-Language Grounding as Bidirectional Concept Correspondence Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.650685Z

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Observation da33c1f9-b611-415c-8544-6be218767bee · outbound

This paper cites Sam 3: Segment anything with concepts, 2025.

Vision-Language Grounding as Bidirectional Concept Correspondence Sam 3: Segment anything with concepts, 2025

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.655891Z

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Observation a60519be-7c22-484e-adc7-3cdc25c8af31 · outbound

This paper cites Clark.Using Language.

Vision-Language Grounding as Bidirectional Concept Correspondence Clark.Using Language

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:40.100677Z

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Observation 5caf5415-ac91-4220-974f-016cfe5ffdd7 · outbound

This paper cites Clark and Susan E.

Vision-Language Grounding as Bidirectional Concept Correspondence Clark and Susan E

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:40.081751Z

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Observation 091329e9-49ff-4360-86a8-fe8c0a80beb3 · outbound

This paper cites Spatial mental models.

Vision-Language Grounding as Bidirectional Concept Correspondence Spatial mental models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:40.062604Z

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Observation 16eda70f-eb8d-4b3b-9c5e-1d806f96b16a · outbound

This paper cites Taylor and Barbara Tversky.

Vision-Language Grounding as Bidirectional Concept Correspondence Taylor and Barbara Tversky

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:40.042794Z

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Observation 20626ba8-a4d7-44bb-890a-8fdc547ece8b · outbound

This paper cites Selective Visual Representations Improve Convergence and Generalization for Embodied AI.

Vision-Language Grounding as Bidirectional Concept Correspondence Selective Visual Representations Improve Convergence and Generalization for Embodied AI

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.681678Z

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Observation e1d81fc1-253e-48a6-8da9-85276ba61ee0 · outbound

This paper cites Treisman and Garry Gelade.

Vision-Language Grounding as Bidirectional Concept Correspondence Treisman and Garry Gelade

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.687795Z

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Observation 1ad7fc1f-0fed-4657-9285-00786092948a · outbound

This paper cites Structure-mapping: A theoretical framework for analogy.Cognitive Science, 7(2):155–170, 1983.

Vision-Language Grounding as Bidirectional Concept Correspondence Structure-mapping: A theoretical framework for analogy.Cognitive Science, 7(2):155–170, 1983

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:40.004128Z

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Observation ece0bc17-9665-4074-b590-4da422e5336c · outbound

This paper cites Who are you referring to? coreference resolution in image narrations.

Vision-Language Grounding as Bidirectional Concept Correspondence Who are you referring to? coreference resolution in image narrations

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.981271Z

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Observation 58fd4ad6-37ad-4f50-a2a1-1e1cec8bc804 · outbound

This paper cites Understanding natural language.Cognitive Psychology, 3(1):1–191, 1972.

Vision-Language Grounding as Bidirectional Concept Correspondence Understanding natural language.Cognitive Psychology, 3(1):1–191, 1972

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.962247Z

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Observation 62a3f04f-6685-4013-9c57-60541eaf82a1 · outbound

This paper cites Levesque, Ernest Davis, and Leora Morgenstern.

Vision-Language Grounding as Bidirectional Concept Correspondence Levesque, Ernest Davis, and Leora Morgenstern

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.944755Z

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Observation 35e35cf0-2588-47d3-af40-f71304ec8583 · outbound

This paper cites Picturing ambiguity: A visual twist on the winograd schema challenge.

Vision-Language Grounding as Bidirectional Concept Correspondence Picturing ambiguity: A visual twist on the winograd schema challenge

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.926171Z

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Observation 37941aa8-3b7e-45aa-9aa0-9a10af435fc8 · outbound

This paper cites Qwen3.5: Towards native multimodal agents, February 2026.

Vision-Language Grounding as Bidirectional Concept Correspondence Qwen3.5: Towards native multimodal agents, February 2026

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.721658Z

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Observation bd57747f-0275-479e-a477-9c9d0f86943a · outbound

This paper cites Qwen3-VL-Seg: Unlocking Open-World Referring Segmentation with Vision-Language Grounding.

Vision-Language Grounding as Bidirectional Concept Correspondence Qwen3-VL-Seg: Unlocking Open-World Referring Segmentation with Vision-Language Grounding

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.728318Z

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Observation be17a4c4-c340-4bbc-9141-a727a01ad8a9 · outbound

This paper cites One trajectory, one token: Grounded video tokenization via panoptic sub- object trajectory.

Vision-Language Grounding as Bidirectional Concept Correspondence One trajectory, one token: Grounded video tokenization via panoptic sub- object trajectory

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.894655Z

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Observation 172d8766-b817-41d9-8805-e24e05b7de94 · outbound

This paper cites TrajTok: Learning Trajectory Tokens enables better Video Understanding.

Vision-Language Grounding as Bidirectional Concept Correspondence TrajTok: Learning Trajectory Tokens enables better Video Understanding

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-12T00:50:39.331928Z

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Observation 85ea8995-84c7-438a-8382-94d1a09a2c77 · outbound

This paper cites Youtu-vl: Unleashing visual potential via unified vision-language supervision.

Vision-Language Grounding as Bidirectional Concept Correspondence Youtu-vl: Unleashing visual potential via unified vision-language supervision

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.744971Z

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Observation 7a913f9e-ad34-49cb-a90b-375542c7f88f · outbound

This paper cites Grounded language-image pre-training.

Vision-Language Grounding as Bidirectional Concept Correspondence Grounded language-image pre-training

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.878393Z

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 fddb5876-cb24-4df8-a84f-4831cc1bafc9 · outbound

This paper cites Glipv2: Unifying localization and vision-language understanding.Advances in Neural Information Processing Systems, 35:36067–36080, 2022.

Vision-Language Grounding as Bidirectional Concept Correspondence Glipv2: Unifying localization and vision-language understanding.Advances in Neural Information Processing Systems, 35:36067–36080, 2022

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.861293Z

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Observation 77cd3d39-85d9-4e5d-bfdd-fba5d0e41a17 · outbound

This paper cites Synthetic visual genome.

Vision-Language Grounding as Bidirectional Concept Correspondence Synthetic visual genome

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.840478Z

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Observation b7ea31fb-e3d0-4c8b-b2b6-cece6cbc090d · outbound

This paper cites You, Daniel Ogbu, Chenhao Zheng, Weikai Huang, Yinuo Yang, Winson Han, Quan Kong, Rajat Saini, and Ranjay Krishna.

Vision-Language Grounding as Bidirectional Concept Correspondence You, Daniel Ogbu, Chenhao Zheng, Weikai Huang, Yinuo Yang, Winson Han, Quan Kong, Rajat Saini, and Ranjay Krishna

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.820974Z

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Observation 63783363-2965-4003-b570-7891af021b91 · outbound

This paper cites Mdetr-modulated detection for end-to-end multi-modal understanding.

Vision-Language Grounding as Bidirectional Concept Correspondence Mdetr-modulated detection for end-to-end multi-modal understanding

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.768528Z

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Observation fe798667-ef84-48ed-a666-839e5fe43cdd · outbound

This paper cites Detclip: Dictionary-enriched visual-concept paralleled pre-training for open-world detection.Advances in Neural Information Processing Systems, 35:9125–9138, 2022.

Vision-Language Grounding as Bidirectional Concept Correspondence Detclip: Dictionary-enriched visual-concept paralleled pre-training for open-world detection.Advances in Neural Information Processing Systems, 35:9125–9138, 2022

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.773695Z

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Observation 40b42858-ba0f-4a7b-9fa0-e971e9b9fbf7 · outbound

This paper cites Detclipv2: Scalable open-vocabulary object detection pre-training via word-region alignment.

Vision-Language Grounding as Bidirectional Concept Correspondence Detclipv2: Scalable open-vocabulary object detection pre-training via word-region alignment

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.775293Z

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Observation 33173060-5025-41e1-881b-8a7c7d4b9041 · outbound

This paper cites An Open and Comprehensive Pipeline for Unified Object Grounding and Detection.

Vision-Language Grounding as Bidirectional Concept Correspondence An Open and Comprehensive Pipeline for Unified Object Grounding and Detection

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.784349Z

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Observation 31b7c7f1-5b07-4da6-a806-cea59bd7fcfc · outbound

This paper cites Llmdet: Learning strong open-vocabulary object detectors under the supervision of large language models.

Vision-Language Grounding as Bidirectional Concept Correspondence Llmdet: Learning strong open-vocabulary object detectors under the supervision of large language models

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.757128Z

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Observation a3b87be8-b678-47c9-b383-978b091bd266 · outbound

This paper cites General object foundation model for images and videos at scale.

Vision-Language Grounding as Bidirectional Concept Correspondence General object foundation model for images and videos at scale

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.795494Z

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Observation de76a102-254c-4923-bf96-75629d0069b5 · outbound

This paper cites Generalized decoding for pixel, image, and language.

Vision-Language Grounding as Bidirectional Concept Correspondence Generalized decoding for pixel, image, and language

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.800990Z

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Observation 7746fd4f-a1ec-43c3-a507-0e0c2ba0844a · outbound

This paper cites A simple framework for open-vocabulary segmentation and detection.

Vision-Language Grounding as Bidirectional Concept Correspondence A simple framework for open-vocabulary segmentation and detection

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.805958Z

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Observation 18d6d323-6993-4d3a-91ce-66b7c7f404d9 · outbound

This paper cites Segment everything everywhere all at once.

Vision-Language Grounding as Bidirectional Concept Correspondence Segment everything everywhere all at once

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.689614Z

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Observation 61cbbf9c-bd7e-40c8-97a6-5cf21afd95ff · outbound

This paper cites Open- worldsam: Extending sam2 for universal image segmentation with language prompts.arXiv preprint arXiv:2507.05427, 2025.

Vision-Language Grounding as Bidirectional Concept Correspondence Open- worldsam: Extending sam2 for universal image segmentation with language prompts.arXiv preprint arXiv:2507.05427, 2025

Reference 42

Resolution: verified exact; raw_fallback, observed 2026-08-12T00:50:39.199874Z

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Observation 8d45cf05-1f07-4640-89a8-b4f3cd67e6fc · outbound

This paper cites Florence-2: Advancing a unified representation for a variety of vision tasks.

Vision-Language Grounding as Bidirectional Concept Correspondence Florence-2: Advancing a unified representation for a variety of vision tasks

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.820534Z

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Observation 179f56a2-0934-43a0-b6ba-5795bb5577b5 · outbound

This paper cites Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection.

Vision-Language Grounding as Bidirectional Concept Correspondence Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.824993Z

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Observation dcdd51bf-6c3a-4e16-a828-df52d40381e8 · outbound

This paper cites LISA: Reasoning Segmentation via Large Language Model.

Vision-Language Grounding as Bidirectional Concept Correspondence LISA: Reasoning Segmentation via Large Language Model

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.830162Z

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Observation 18dc40db-1ea0-41e8-8a1c-5957d02ea833 · outbound

This paper cites LISA++: An Improved Baseline for Reasoning Segmentation with Large Language Model.

Vision-Language Grounding as Bidirectional Concept Correspondence LISA++: An Improved Baseline for Reasoning Segmentation with Large Language Model

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.835625Z

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Observation ed570fb5-ef30-44b7-a58f-822870c20593 · outbound

This paper cites Glamm: Pixel grounding large multimodal model.

Vision-Language Grounding as Bidirectional Concept Correspondence Glamm: Pixel grounding large multimodal model

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.840703Z

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Observation aed20469-30a3-4f04-8de3-94dae3870694 · outbound

This paper cites Pointrend: Image segmentation as rendering.

Vision-Language Grounding as Bidirectional Concept Correspondence Pointrend: Image segmentation as rendering

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.846502Z

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Observation c85a48fb-934a-4c15-b4c3-4c7c9819ac59 · outbound

This paper cites V-net: Fully convolutional neural networks for volumetric medical image segmentation.

Vision-Language Grounding as Bidirectional Concept Correspondence V-net: Fully convolutional neural networks for volumetric medical image segmentation

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.625488Z

Source-reported events for the cited work

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Observation 6638bb39-258b-4120-8535-7e1d5ea2f75b · outbound

This paper cites COCONut-PanCap: Joint Panoptic Segmentation and Grounded Captions for Fine-Grained Understanding and Generation.

Vision-Language Grounding as Bidirectional Concept Correspondence COCONut-PanCap: Joint Panoptic Segmentation and Grounded Captions for Fine-Grained Understanding and Generation

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.856702Z

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Observation 36661101-d3c1-4bae-80ee-34586aece948 · outbound

This paper cites Gqa: A new dataset for real-world visual reasoning and compositional question answering.

Vision-Language Grounding as Bidirectional Concept Correspondence Gqa: A new dataset for real-world visual reasoning and compositional question answering

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.862099Z

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Observation 10385fd9-fdb0-4493-a342-4b2ea053479b · outbound

This paper cites Lawrence Zitnick, and Piotr Dollár.

Vision-Language Grounding as Bidirectional Concept Correspondence Lawrence Zitnick, and Piotr Dollár

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.867594Z

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Observation 66deab6a-78d7-4abc-8dcb-e8ae0b93c640 · outbound

This paper cites Coconut: Modernizing coco segmentation.

Vision-Language Grounding as Bidirectional Concept Correspondence Coconut: Modernizing coco segmentation

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.583042Z

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Observation 1ede06cf-8bff-4a53-a624-56b8f28a7dca · outbound

This paper cites High- quality entity segmentation.

Vision-Language Grounding as Bidirectional Concept Correspondence High- quality entity segmentation

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.566011Z

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 88e66ab2-807d-44f6-90c5-0ff28ddb4407 · outbound

This paper cites Semantic understanding of scenes through the ade20k dataset.International journal of computer vision, 127(3):302–321, 2019.

Vision-Language Grounding as Bidirectional Concept Correspondence Semantic understanding of scenes through the ade20k dataset.International journal of computer vision, 127(3):302–321, 2019

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.884016Z

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Observation 173dff5c-6072-4a51-aab6-80fcf0136bba · outbound

This paper cites GREC: Generalized Referring Expression Comprehension.

Vision-Language Grounding as Bidirectional Concept Correspondence GREC: Generalized Referring Expression Comprehension

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.888934Z

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Observation 23ee512f-4627-4f97-b5d8-1b16ba8376c4 · outbound

This paper cites Introducing GPT-5.4.

Vision-Language Grounding as Bidirectional Concept Correspondence Introducing GPT-5.4

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:50:39.535906Z

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 dc15b24f-9320-4aac-810b-8490493cc188 · outbound

This paper cites Segment anything.

Vision-Language Grounding as Bidirectional Concept Correspondence Segment anything

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T00:50:38.899194Z

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Unavailable: canonical work link unavailable.

Observation 6932e29d-e9b6-4979-baf5-59e71b848e38 · outbound

This paper cites Roboflow100-vl: A multi-domain object detection benchmark for vision-language models.

Vision-Language Grounding as Bidirectional Concept Correspondence Roboflow100-vl: A multi-domain object detection benchmark for vision-language models

Reference 59

Resolution: malformed identifier; no resolver link, observed 2026-08-12T00:50:38.904354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Outbound references

Pith citing papers