Paper Citation Record · LEDGER

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models

As of 22 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 7 inbound Pith citation observations for arXiv:2501.18954.

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

pith.paper-citation-record.v1
2501.18954 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T21:55:23.361176Z

measured 75 of 75 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:17:36.580979Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T03:46:33.282729Z

Reference resolution

68 of 68 outbound references displayed

verified exact0
verified fuzzy44
unresolved24
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e1573677-fb1b-4b81-b5fe-61fdc1448642 · outbound

This paper cites Nltk: the natural language toolkit.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Nltk: the natural language toolkit

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.933368Z

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Observation 47ec76e3-c514-4b0b-b9ee-a76b070087c2 · outbound

This paper cites End-to- end object detection with transformers.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models End-to- end object detection with transformers

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.922207Z

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Observation ffaa8454-edde-48f0-8aeb-cbebda13f315 · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 3

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Observation f7a62b63-cfb7-4405-af9c-40b0302fd257 · outbound

This paper cites Sharegpt4v: Improving large multi-modal models with better captions.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Sharegpt4v: Improving large multi-modal models with better captions

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.912272Z

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Observation 84399f18-64fb-43a7-ab53-df1d0b9172fb · outbound

This paper cites Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks

Reference 5

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Source-reported events for the cited work

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Observation 68873fa9-8add-4bbe-86b5-b98e519d44b3 · outbound

This paper cites Yolo-world: Real-time open- vocabulary object detection.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Yolo-world: Real-time open- vocabulary object detection

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.898006Z

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Observation 6e36856d-eaae-4521-94f2-71467bd0f696 · outbound

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

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Gonzalez, Ion Stoica, and Eric P

Reference 7

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Observation 901397cd-38b0-4712-8301-fbbd736bb35e · outbound

This paper cites Evaluating Large-Vocabulary Object Detectors: The Devil is in the Details.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Evaluating Large-Vocabulary Object Detectors: The Devil is in the Details

Reference 8

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Observation 44edde5d-1910-4bd9-818a-bb26ab22c5b4 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Imagenet: A large-scale hierarchical image database

Reference 9

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Observation e407b773-545a-425d-9a2a-bfe6decd759b · outbound

This paper cites Coarse-to-fine vision-language pre-training with fusion in the backbone.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Coarse-to-fine vision-language pre-training with fusion in the backbone

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.877896Z

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Observation 175448ee-958f-4fe1-a951-929a89ed7b21 · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 11

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Observation da140a42-570e-4172-b2cc-e20ac0e05163 · outbound

This paper cites Asag: Building strong one-decoder-layer sparse detectors via adaptive sparse anchor generation.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Asag: Building strong one-decoder-layer sparse detectors via adaptive sparse anchor generation

Reference 12

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Observation d8d29c7b-f8bd-4807-af7b-1f1079d04e04 · outbound

This paper cites Frozen-detr: Enhancing detr with image understanding from frozen foundation models.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Frozen-detr: Enhancing detr with image understanding from frozen foundation models

Reference 13

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Observation e2b73a3e-4a5c-4cb3-9251-8fc272f08d66 · outbound

This paper cites Open-vocabulary object detection via vision and language knowledge distillation.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Open-vocabulary object detection via vision and language knowledge distillation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.855042Z

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Observation 71a56cef-51ce-4b25-8fbd-b500139973c8 · outbound

This paper cites Lvis: A dataset for large vocabulary instance segmentation.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Lvis: A dataset for large vocabulary instance segmentation

Reference 15

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Observation d42e2777-51d9-42b8-b4ad-eb92e7620146 · outbound

This paper cites Mask r-cnn.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Mask r-cnn

Reference 16

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Observation 0b63dcd3-1a56-409b-b130-18fe2204f11c · outbound

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

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Gqa: A new dataset for real-world visual reasoning and compositional question answering

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.830403Z

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Observation d75afc4b-f51c-4786-af1e-61c751d28bff · outbound

This paper cites GPT-4o System Card.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models GPT-4o System Card

Reference 18

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Observation 928aa28c-d9e7-4b7e-9bd6-83bac3d42c6b · outbound

This paper cites T-rex2: Towards generic object detec- tion via text-visual prompt synergy.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models T-rex2: Towards generic object detec- tion via text-visual prompt synergy

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.820218Z

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Observation f7fff0fe-110f-4403-980e-52c9497ababb · outbound

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

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Mdetr- modulated detection for end-to-end multi-modal understand- ing

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.809160Z

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Observation 22f02348-d893-4d0b-9c76-0394a80040a3 · outbound

This paper cites Referitgame: Referring to objects in pho- tographs of natural scenes.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Referitgame: Referring to objects in pho- tographs of natural scenes

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.798966Z

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Observation 36ab6bc2-80a5-4269-82c7-8b948a420e03 · outbound

This paper cites F-vlm: Open-vocabulary object detection upon frozen vision and language models.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models F-vlm: Open-vocabulary object detection upon frozen vision and language models

Reference 22

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Observation 76bde895-cbad-43ba-996f-a18531bfe81c · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models LLaVA-OneVision: Easy Visual Task Transfer

Reference 23

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Observation 1178452f-d5c1-46a8-af4b-0188eb0c6efb · outbound

This paper cites Elevater: A benchmark and toolkit for evaluating language-augmented visual models.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Elevater: A benchmark and toolkit for evaluating language-augmented visual models

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.783598Z

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Observation b405fdf2-d4e0-4aac-adfd-102410a18cda · outbound

This paper cites Desco: Learning object recognition with rich language de- scriptions.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Desco: Learning object recognition with rich language de- scriptions

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.774357Z

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Observation 0778c048-4d9f-4952-b70b-342ad58ac51b · outbound

This paper cites Distilling detr with visual-linguistic knowledge for open-vocabulary object detection.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Distilling detr with visual-linguistic knowledge for open-vocabulary object detection

Reference 26

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This paper cites Grounded language-image pre-training.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Grounded language-image pre-training

Reference 27

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Observation e0d13269-2714-4591-9ff8-b2fe067bdcd5 · outbound

This paper cites Evaluating object hallucination in large vision-language models.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Evaluating object hallucination in large vision-language models

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.751470Z

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This paper cites Mon- key: Image resolution and text label are important things for large multi-modal models.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Mon- key: Image resolution and text label are important things for large multi-modal models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.742548Z

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Observation b73b9807-e4e7-4d0d-afe8-9b52010fdc72 · outbound

This paper cites Generative region-language pretraining for open-ended object detection.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Generative region-language pretraining for open-ended object detection

Reference 30

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Observation 6fe0c555-14ec-4412-900b-f6aebbac2119 · outbound

This paper cites Microsoft coco: Common objects in context.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Microsoft coco: Common objects in context

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.724447Z

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This paper cites Focal loss for dense object detection.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Focal loss for dense object detection

Reference 32

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This paper cites Gres: Gener- alized referring expression segmentation.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Gres: Gener- alized referring expression segmentation

Reference 33

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LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Visual instruction tuning

Reference 34

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This paper cites Improved baselines with visual instruction tuning.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Improved baselines with visual instruction tuning

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This paper cites Grounding dino: Marrying dino with grounded pre-training for open-set object detection.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Grounding dino: Marrying dino with grounded pre-training for open-set object detection

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.684444Z

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

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Swin transformer: Hierarchical vision transformer using shifted windows

Reference 37

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This paper cites Capdet: Unifying dense captioning and open-world detec- tion pretraining.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Capdet: Unifying dense captioning and open-world detec- tion pretraining

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.666285Z

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This paper cites Generation and comprehension of unambiguous object descriptions.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Generation and comprehension of unambiguous object descriptions

Reference 39

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This paper cites Coco-o: A benchmark for object detectors under natural distribution shifts.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Coco-o: A benchmark for object detectors under natural distribution shifts

Reference 40

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This paper cites Scaling open-vocabulary object detection.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Scaling open-vocabulary object detection

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.639857Z

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

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Flickr30k entities: Collecting region-to-phrase corre- spondences for richer image-to-sentence models

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.630943Z

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This paper cites Learn- ing transferable visual models from natural language super- vision.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Learn- ing transferable visual models from natural language super- vision

Reference 43

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This paper cites Objects365: A large-scale, high-quality dataset for object detection.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Objects365: A large-scale, high-quality dataset for object detection

Reference 44

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This paper cites Conceptual captions: A cleaned, hypernymed, im- age alt-text dataset for automatic image captioning.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Conceptual captions: A cleaned, hypernymed, im- age alt-text dataset for automatic image captioning

Reference 45

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This paper cites Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders

Reference 46

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This paper cites Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs

Reference 47

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This paper cites LLaMA: Open and Efficient Foundation Language Models.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 48

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This paper cites OV-DINO: Unified Open-Vocabulary Detection with Language-Aware Selective Fusion.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models OV-DINO: Unified Open-Vocabulary Detection with Language-Aware Selective Fusion

Reference 49

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Observation 3fe787cf-ccf6-4697-aa3f-ba1ea02fbf10 · outbound

This paper cites V3det: Vast vocabulary visual detection dataset.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models V3det: Vast vocabulary visual detection dataset

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.607473Z

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Observation 58a6c0de-f752-4992-b1d8-a769f3b7ce75 · outbound

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

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-09T21:55:23.311214Z

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Observation 8635b23c-e02a-49cd-8d03-bcc3efcfcb22 · outbound

This paper cites The all-seeing project v2: To- wards general relation comprehension of the open world.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models The all-seeing project v2: To- wards general relation comprehension of the open world

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.598662Z

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Observation 30fe3dfc-7868-4563-b9ae-62493519089c · outbound

This paper cites Grit: A gen- erative region-to-text transformer for object understanding.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Grit: A gen- erative region-to-text transformer for object understanding

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.589693Z

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Observation 379c936c-c3ec-4e99-a626-0661e3828ddd · outbound

This paper cites Aligning bag of regions for open- vocabulary object detection.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Aligning bag of regions for open- vocabulary object detection

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-09T21:55:23.321030Z

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Observation 49e41f53-ee25-4ceb-af31-9f6821eaa9fe · outbound

This paper cites Qwen2 Technical Report.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Qwen2 Technical Report

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-09T21:55:23.323886Z

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Observation e5bba39b-7a2a-4bf9-b6f4-4fd26499815e · outbound

This paper cites Detclip: Dictionary-enriched visual-concept paralleled pre- training for open-world detection.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Detclip: Dictionary-enriched visual-concept paralleled pre- training for open-world detection

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.576360Z

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Observation a6401795-8ca0-42d3-97ec-24b156b955eb · outbound

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

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Detclipv2: Scal- able open-vocabulary object detection pre-training via word- region alignment

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.567971Z

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Observation c740e57d-d35b-4a47-b774-49fe0eb0225c · outbound

This paper cites Detclipv3: To- wards versatile generative open-vocabulary object detection.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Detclipv3: To- wards versatile generative open-vocabulary object detection

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.559626Z

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Observation c8c4055f-d33d-4e3c-abf8-528817b67173 · outbound

This paper cites Modeling context in referring expres- sions.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Modeling context in referring expres- sions

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.551103Z

Source-reported events for the cited work

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Observation 186e798d-e220-45a8-9f39-441239d814b0 · outbound

This paper cites Hallucidoctor: Mitigating hallucinatory toxicity in visual instruction data.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Hallucidoctor: Mitigating hallucinatory toxicity in visual instruction data

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.542460Z

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Observation 11374560-06eb-44b7-92b9-335ce53c0f5b · outbound

This paper cites Sigmoid loss for language image pre-training.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Sigmoid loss for language image pre-training

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.533868Z

Source-reported events for the cited work

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Observation e2f4d276-e4cc-4a3c-a279-99e31ae5b901 · outbound

This paper cites Glipv2: Unifying localiza- tion and vision-language understanding.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Glipv2: Unifying localiza- tion and vision-language understanding

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.524614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 446fe260-9a89-40b8-8fed-ec76fc9d0af3 · outbound

This paper cites Dino: Detr with improved denoising anchor boxes for end-to-end object detection.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Dino: Detr with improved denoising anchor boxes for end-to-end object detection

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.515459Z

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Observation f8cf1f89-d93d-4b5e-a524-0f87991f34d2 · outbound

This paper cites Generating enhanced negatives for training language-based object detec- tors.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Generating enhanced negatives for training language-based object detec- tors

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.506604Z

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Observation 2a559df2-72fb-4529-82c1-3936457f60a1 · outbound

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

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models An Open and Comprehensive Pipeline for Unified Object Grounding and Detection

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-09T21:55:23.351984Z

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Observation b9aa56ca-f211-4658-a001-dc00bb9d5df4 · outbound

This paper cites Detecting twenty-thousand classes using image-level supervision.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Detecting twenty-thousand classes using image-level supervision

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.497229Z

Source-reported events for the cited work

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Observation 7bade701-8eca-4ae2-9985-41543c2c0371 · outbound

This paper cites Mova: Adapting mixture of vision experts to multimodal context.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models Mova: Adapting mixture of vision experts to multimodal context

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.488169Z

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Observation e1d54f5f-1378-46b5-98c1-321d736e2443 · outbound

This paper cites the man” and “umbrella.

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models the man” and “umbrella

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:55:23.478023Z

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Pith citing papers

Observation ae3df2a4-fd49-4207-9b4b-a7fc500f5417 · inbound

RF-DETR Object Detection vs YOLOv12 : A Study of Transformer-based and CNN-based Architectures for Single-Class and Multi-Class Greenfruit Detection in Complex Orchard Environments Under Label Ambiguity cites this paper.

RF-DETR Object Detection vs YOLOv12 : A Study of Transformer-based and CNN-based Architectures for Single-Class and Multi-Class Greenfruit Detection in Complex Orchard Environments Under Label Ambiguity LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T12:17:36.580979Z

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Observation f63d6b4c-fd85-4bc0-ad99-27228d92063a · inbound

VL-SAM-V2: Open-World Object Detection with General and Specific Query Fusion cites this paper.

VL-SAM-V2: Open-World Object Detection with General and Specific Query Fusion LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:25:42.436018Z

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Observation b9aa25c1-7b01-4448-b0df-06e09001edc1 · inbound

RAGSR: Regional Attention Guided Diffusion for Image Super-Resolution cites this paper.

RAGSR: Regional Attention Guided Diffusion for Image Super-Resolution LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T17:33:35.846198Z

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Observation 03db883a-530e-44f5-af38-8974a28cb22c · inbound

Reinforced Visual Perception with Tools cites this paper.

Reinforced Visual Perception with Tools LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T12:27:04.920344Z

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Observation 925712cc-f512-4634-8d6b-39ea59245400 · inbound

Revisiting Embodied Chain-of-Thought for Generalizable Robot Manipulation cites this paper.

Revisiting Embodied Chain-of-Thought for Generalizable Robot Manipulation LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:46:33.284362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 28f99f0d-5609-453e-9ea9-da3eb702dda7 · inbound

MissingBench-Verified: Probing Vision-Language Models' Inability to Detect Missing Object Parts cites this paper.

MissingBench-Verified: Probing Vision-Language Models' Inability to Detect Missing Object Parts LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-01T14:44:05.247859Z

Source-reported events for the cited work

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Observation 2170e321-15aa-4d70-867c-ce1a46fcb057 · inbound

Kitchen Robotic Manipulation utilizing Foundation Models cites this paper.

Kitchen Robotic Manipulation utilizing Foundation Models LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-08T00:49:13.593500Z

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