Paper Citation Record · LEDGER

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection

As of 8 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 1 inbound Pith citation observation for arXiv:2510.14792.

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

pith.paper-citation-record.v1
2510.14792 v4

Coverage vector

measured 66 of 66 reference resolution

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measured 67 of 67 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

66 of 66 outbound references displayed

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External citation measurements

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Outbound references

Observation 67c99223-9bb6-40b3-958b-eef35b68bb2a · outbound

This paper cites an unresolved cited work.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Unresolved cited work

Reference 2

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Observation 9fb82ad0-37a0-4ccf-938f-3b7dfca0ec9a · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection An image is worth 16x16 words: Transformers for image recognition at scale

Reference 4

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Observation 2216ac6a-b8b7-4b51-b2a0-c16b44e723d2 · outbound

This paper cites Smith, Wei-Chiu Ma, and Ranjay Krishna.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Smith, Wei-Chiu Ma, and Ranjay Krishna

Reference 7

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Observation 530313d8-f5d5-4d4e-a9c7-cea3a5c006fd · outbound

This paper cites Open vocabulary object detection with pseudo bounding-box labels.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Open vocabulary object detection with pseudo bounding-box labels

Reference 8

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

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Open-vocabulary object detection via vi- sion and language knowledge distillation

Reference 9

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Observation 59f105c5-3272-4eee-a9ff-7c0797a48d9c · outbound

This paper cites Hallusionbench: An advanced diagnostic suite for entangled language hallucination and visual illusion in large vision- language models.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Hallusionbench: An advanced diagnostic suite for entangled language hallucination and visual illusion in large vision- language models

Reference 10

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Observation e8d29ef8-7309-42bf-bb68-59cf56dda22c · outbound

This paper cites Girshick.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Girshick

Reference 11

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This paper cites Deep residual learning for image recog- nition.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Deep residual learning for image recog- nition

Reference 13

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This paper cites Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig

Reference 15

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This paper cites Llms meet vlms: Boost open vocabulary object detection with fine-grained descriptors.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Llms meet vlms: Boost open vocabulary object detection with fine-grained descriptors

Reference 16

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Observation 9eb55558-0da3-459a-83fe-e1055a451883 · outbound

This paper cites Contrastive feature masking open-vocabulary vision transformer.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Contrastive feature masking open-vocabulary vision transformer

Reference 17

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This paper cites Berg, Wan-Yen Lo, Piotr Doll ´ar, and Ross B.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Berg, Wan-Yen Lo, Piotr Doll ´ar, and Ross B

Reference 18

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This paper cites Learning background prompts to discover implicit knowledge for open vocabulary object detection.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Learning background prompts to discover implicit knowledge for open vocabulary object detection

Reference 19

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Unresolved cited work

Reference 20

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This paper cites Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll´ar, and C.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll´ar, and C

Reference 21

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This paper cites Class-agnostic object detection with multi-modal transformer.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Class-agnostic object detection with multi-modal transformer

Reference 23

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This paper cites LP-OVOD: open-vocabulary object detection by linear probing.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection LP-OVOD: open-vocabulary object detection by linear probing

Reference 24

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Belongie, Alan L

Reference 25

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Observation 25ad7e8e-12cd-4d5b-9ddd-0c3629fe0f54 · outbound

This paper cites Langsplat: 3d lan- guage gaussian splatting.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Langsplat: 3d lan- guage gaussian splatting

Reference 26

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This paper cites Learning transferable visual models from natural language supervision.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Learning transferable visual models from natural language supervision

Reference 27

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Khan, and Fahad Shahbaz Khan

Reference 28

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Girshick, and Jian Sun

Reference 29

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Visual cot: Advancing multi-modal language models with a comprehensive dataset and benchmark for chain-of-thought reasoning

Reference 30

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Observation 44d90eed-e159-425f-89de-b3dd5f9d3d35 · outbound

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

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Objects365: A large-scale, high-quality dataset for object detection

Reference 31

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Chi, Quoc V

Reference 34

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Visual chatgpt: Talking, drawing and editing with visual foundation models.CoRR, 2023a

Reference 35

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection CORA: adapting CLIP for open-vocabulary detection with region prompting and anchor pre-matching

Reference 36

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This paper cites Open- vocabulary SAM: segment and recognize twenty-thousand classes interactively.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Open- vocabulary SAM: segment and recognize twenty-thousand classes interactively

Reference 37

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection MMMU: A massive multi-discipline multimodal understanding and reasoning benchmark for expert AGI

Reference 38

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Unresolved cited work

Reference 39

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Open-vocabulary DETR with conditional matching

Reference 40

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Open-vocabulary object detection using captions

Reference 41

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Cyclic contrastive knowledge transfer for open-vocabulary object detection.CoRR, 2025a

Reference 42

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Cot-vla: Visual chain-of-thought reasoning for vision-language-action models

Reference 44

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Unresolved cited work

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Unresolved cited work

Reference 46

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Regionclip: Region-based language- image pretraining

Reference 47

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Detecting twenty-thousand classes using image-level supervision

Reference 48

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This paper cites We adopt the 1×training schedule for OV- COCO (Lin et al.,.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection We adopt the 1×training schedule for OV- COCO (Lin et al.,

Reference 49

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This paper cites Pseudo-label generation process.During our offline pseudo-label generation process, we lever- age SAM (Kirillov et al., 2023; Qin et al.,.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Pseudo-label generation process.During our offline pseudo-label generation process, we lever- age SAM (Kirillov et al., 2023; Qin et al.,

Reference 50

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This paper cites a photo of [OBJ].

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection a photo of [OBJ]

Reference 51

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This paper cites During training, model checkpoints are saved every 10,000 iter- ations for OV-COCO and every 30,000 iterations for OV-LVIS.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection During training, model checkpoints are saved every 10,000 iter- ations for OV-COCO and every 30,000 iterations for OV-LVIS

Reference 52

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This paper cites For semantic anchor construction, we filter out infrequent pseudo-labels using a minimum annotation threshold—set to 1,237 for OV-COCO and 1 for OV-LVIS.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection For semantic anchor construction, we filter out infrequent pseudo-labels using a minimum annotation threshold—set to 1,237 for OV-COCO and 1 for OV-LVIS

Reference 53

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This paper cites Due to the severe long-tail distribution, some rare categories contain fewer than five instances; such categories are removed during semantic anchor construction.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Due to the severe long-tail distribution, some rare categories contain fewer than five instances; such categories are removed during semantic anchor construction

Reference 54

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Unresolved cited work

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This paper cites By densely sampling point prompts across the image, SAM generates a diverse set of masks that capture object regions at varying levels of granularity.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection By densely sampling point prompts across the image, SAM generates a diverse set of masks that capture object regions at varying levels of granularity

Reference 58

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This paper cites This setup enables efficient vision-language alignment and achieves strong performance on tasks such as image captioning and visual question answer- ing (VQA) with minimal training.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection This setup enables efficient vision-language alignment and achieves strong performance on tasks such as image captioning and visual question answer- ing (VQA) with minimal training

Reference 59

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection This design allows the model to follow natural language instructions and generalize across diverse multimodal tasks

Reference 60

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This paper cites However, when applied to object-level understanding, recent studies (Zang et al., 2025; Fu et al.,.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection However, when applied to object-level understanding, recent studies (Zang et al., 2025; Fu et al.,

Reference 61

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This paper cites In our setting, where the MLLM is prompted on individual region proposals, it is essential to emphasize the target object while suppressing ir- relevant background information.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection In our setting, where the MLLM is prompted on individual region proposals, it is essential to emphasize the target object while suppressing ir- relevant background information

Reference 62

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This paper cites In practice, we validate that this strategy improves localization and reasoning in MLLMs (Bai et al., 2023), as shown in Table.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection In practice, we validate that this strategy improves localization and reasoning in MLLMs (Bai et al., 2023), as shown in Table

Reference 63

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection dog,” “knife,

Reference 64

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This paper cites Methods MS-COCO(Lin et al., 2014)Objects365(Shao et al., 2019b) AP (%) AP 50 (%) AP 75 (%) AP (%) AP 50 (%) AP 75 (%) Supervised (Gu et al.,.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Methods MS-COCO(Lin et al., 2014)Objects365(Shao et al., 2019b) AP (%) AP 50 (%) AP 75 (%) AP (%) AP 50 (%) AP 75 (%) Supervised (Gu et al.,

Reference 65

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MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Unresolved cited work

Reference 66

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Observation 6538adc5-190c-43d9-844c-1f86fad57a53 · outbound

This paper cites Kankanhalli, and Ying Shan.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Kankanhalli, and Ying Shan

Reference 2008

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Observation 594b1a58-3227-4837-98ff-f08f2d199481 · outbound

This paper cites Hayes, Elisa Ricci, Gabriela Csurka, and Riccardo V olpi.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Hayes, Elisa Ricci, Gabriela Csurka, and Riccardo V olpi

Reference 2014

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Observation ac309470-1164-431f-87d4-8b44e0629b10 · outbound

This paper cites a photo of{category}in the scene.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection a photo of{category}in the scene

Reference 2015

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Observation f06382dd-2f20-4bdc-8ad6-30d44c383ae2 · outbound

This paper cites Girshick.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Girshick

Reference 2016

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Observation 0244a37a-3d9e-4c7f-bdb4-457947a8a11a · outbound

This paper cites VLMs support novel class recognition in OVD through various techniques, such as pseudo-labeling.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection VLMs support novel class recognition in OVD through various techniques, such as pseudo-labeling

Reference 2017

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Observation 612f1ae3-368d-4f84-8d11-8fe8726368b5 · outbound

This paper cites Explor- ing region-word alignment in built-in detector for open-vocabulary object detection.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Explor- ing region-word alignment in built-in detector for open-vocabulary object detection

Reference 2018

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Observation ef5db736-1543-42fc-9929-ce4a968be38f · outbound

This paper cites Boosting segment anything model towards open-vocabulary learning.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Boosting segment anything model towards open-vocabulary learning

Reference 2019

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Observation 5d4af65b-e3ad-4f17-a5ed-68c90d7acc70 · outbound

This paper cites Learning to prompt for open-vocabulary object detection with vision-language model.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Learning to prompt for open-vocabulary object detection with vision-language model

Reference 2021

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Observation e1535c60-5bf2-4a68-828b-b4d0785338e0 · outbound

This paper cites Instagen: Enhancing object detection by training on synthetic dataset.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Instagen: Enhancing object detection by training on synthetic dataset

Reference 2022

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Observation e7f41c67-25f2-4d46-84fb-77781eca7e28 · outbound

This paper cites Zero-shot ob- ject detection.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Zero-shot ob- ject detection

Reference 2023

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Observation ed8c3fdd-b288-42b4-a18f-43ee2c15f00f · outbound

This paper cites an unresolved cited work.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Unresolved cited work

Reference 2024

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Observation 9e366de6-f153-4957-8ada-1b66f236641b · outbound

This paper cites Object-aware distillation pyramid for open-vocabulary object detection.

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection Object-aware distillation pyramid for open-vocabulary object detection

Reference 2025

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Pith citing papers

Observation 0438c3e1-e886-4764-9bd7-8e249fa6c60e · inbound

Open-Vocabulary Gaze Object Prediction: Benchmark and Method cites this paper.

Open-Vocabulary Gaze Object Prediction: Benchmark and Method MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection

Reference 5

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