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Paper Citation Record · LEDGER

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering

As of 23 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 0 inbound Pith citation observations for arXiv:2508.11163.

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

pith.paper-citation-record.v1
2508.11163 v1

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:08:56.016306Z

measured 63 of 63 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

63 of 63 outbound references displayed

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  • verified fuzzy50
  • unresolved11
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5b0db968-a1d8-4158-a435-27b175cad52c · outbound

This paper cites an unresolved cited work.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Unresolved cited work

Reference 1

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Observation a1d5839d-6069-48b8-aef6-e56f0c318c73 · outbound

This paper cites Zhu et al.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Zhu et al

Reference 3

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Observation 08e6f773-1aa7-4f83-9569-6074e4c61739 · outbound

This paper cites Zhang et al.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Zhang et al

Reference 4

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Observation 4b16924c-36a4-4ec3-825c-15569dcd5159 · outbound

This paper cites an unresolved cited work.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Unresolved cited work

Reference 5

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Source-reported events for the cited work

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Observation 6017cc38-da1b-40c0-a8b1-a9d9af6bbf3f · outbound

This paper cites VFM-Guided Semi-Supervised Detection Transformer under Source-Free Constraints for Remote Sensing Object Detection.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering VFM-Guided Semi-Supervised Detection Transformer under Source-Free Constraints for Remote Sensing Object Detection

Reference 8

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Source-reported events for the cited work

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Observation cf743924-0c9e-45ff-a10a-82b61482944c · outbound

This paper cites Unbiased teacher for semi-supervised object detection,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Unbiased teacher for semi-supervised object detection,

Reference 12

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Source-reported events for the cited work

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Observation d118dfa8-d8b3-4d32-8567-8fbecf22c042 · outbound

This paper cites Ema: A process model of appraisal dynamics,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Ema: A process model of appraisal dynamics,

Reference 13

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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.

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Observation 9f1e6999-659f-400c-8b34-ef68b5515d16 · outbound

This paper cites Periodically exchange teacher-student for source-free object detection,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Periodically exchange teacher-student for source-free object detection,

Reference 14

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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.

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Observation 8c8a06ef-5a7a-40b9-85d7-67f3f2dd3822 · outbound

This paper cites Dynamic retraining-updating mean teacher for source-free object detection,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Dynamic retraining-updating mean teacher for source-free object detection,

Reference 15

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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.

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Observation ba95433c-c5da-45c5-bece-6c1763151707 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering DINOv2: Learning Robust Visual Features without Supervision

Reference 16

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Source-reported events for the cited work

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Observation a6d5bfdd-a456-4850-8f24-c3a97adea4ac · outbound

This paper cites Segment anything,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Segment anything,

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 90463b8e-3465-4fee-aabc-8063b95f0300 · outbound

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

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Grounding dino: Marrying dino with grounded pre- training for open-set object detection,

Reference 18

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Source-reported events for the cited work

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Observation 0a7b7443-86fb-44ac-9d7e-c10dc25b3796 · outbound

This paper cites Remoteclip: A vision language foundation model for remote sensing,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Remoteclip: A vision language foundation model for remote sensing,

Reference 19

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Observation ba9accba-9751-4a32-b693-0f4ef1893e87 · outbound

This paper cites Some methods for classification and analysis of multi- variate observations,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Some methods for classification and analysis of multi- variate observations,

Reference 20

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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.

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Observation d756470b-7048-4f77-909a-25c397d40e17 · outbound

This paper cites Sinkhorn distances: Lightspeed computation of optimal transport,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Sinkhorn distances: Lightspeed computation of optimal transport,

Reference 21

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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.

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Observation 6c62b12f-61f7-4246-bdcd-7ac6b9be3ab4 · outbound

This paper cites xView: Objects in Context in Overhead Imagery.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering xView: Objects in Context in Overhead Imagery

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e84be0a3-9319-4576-be70-64ed9001e616 · outbound

This paper cites Dota: A large-scale dataset for object detection in aerial images,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Dota: A large-scale dataset for object detection in aerial images,

Reference 23

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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.

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Observation 29a5d085-0eb4-4968-937b-6ab94e57eb7b · outbound

This paper cites Object detection in optical remote sensing images: A survey and a new benchmark,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Object detection in optical remote sensing images: A survey and a new benchmark,

Reference 24

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Source-reported events for the cited work

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Observation bc02a563-2b7e-4553-bfd7-c0b9c8a8990e · outbound

This paper cites Hierarchical and robust convolutional neural network for very high-resolution remote sensing object detection,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Hierarchical and robust convolutional neural network for very high-resolution remote sensing object detection,

Reference 25

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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.

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Observation f89c323e-11c5-466b-b737-27426b917fc9 · outbound

This paper cites Ship detection in sar images based on an improved faster r-cnn,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Ship detection in sar images based on an improved faster r-cnn,

Reference 26

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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.

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Observation c6cc4694-31da-4b37-bad5-4f7c94122d3c · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 27

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

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Observation 3153427c-c16e-47df-8919-e143079f7eaa · outbound

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

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering End-to-end object detection with transformers,

Reference 28

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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.

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Observation bdf64abe-1dc4-445f-a0e4-6f399950d098 · outbound

This paper cites Exploring sequence feature alignment for domain adaptive detection transformers,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Exploring sequence feature alignment for domain adaptive detection transformers,

Reference 29

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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.

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Observation 1c39e030-bfa7-487b-9de4-a26f8d0079e1 · outbound

This paper cites Da- detr: Domain adaptive detection transformer with information fusion,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Da- detr: Domain adaptive detection transformer with information fusion,

Reference 30

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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.

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Observation 7e0b38b1-36d0-494d-b64c-d068623aa8cb · outbound

This paper cites Focal loss for dense object detection,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Focal loss for dense object detection,

Reference 31

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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.

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Observation b2cf6f44-c05d-45d0-88e4-3ec5d63188fb · outbound

This paper cites Dualda-net: Dual-head rectification for cross-domain object detection of remote sensing,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Dualda-net: Dual-head rectification for cross-domain object detection of remote sensing,

Reference 32

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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.

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Observation 75281da4-ba1d-4341-8f96-a4d397d2f05a · outbound

This paper cites Remote sensing teacher: Cross-domain detection transformer with learnable frequency- enhanced feature alignment in remote sensing imagery,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Remote sensing teacher: Cross-domain detection transformer with learnable frequency- enhanced feature alignment in remote sensing imagery,

Reference 33

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verified fuzzy
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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.

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Observation 39a5dc6f-ad85-4a29-8284-98cae13be987 · outbound

This paper cites Balanced teacher for source-free ob- ject detection,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Balanced teacher for source-free ob- ject detection,

Reference 34

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verified fuzzy
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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.

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Observation 1047e026-db06-44e5-9021-aa1810378f1c · outbound

This paper cites Dense learning based semi-supervised object detection,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Dense learning based semi-supervised object detection,

Reference 35

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raw_fallback, observed 2026-08-05T20:09:04.619909Z

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.

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Observation 86aecf4e-5a82-4e71-b42e-dcdbc565ae4b · outbound

This paper cites Dense teacher: Dense pseudo-labels for semi-supervised object detection,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Dense teacher: Dense pseudo-labels for semi-supervised object detection,

Reference 36

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raw_fallback, observed 2026-08-05T20:09:04.334812Z

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.

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Observation d84a45b6-c18f-474b-aeb0-8c3603a7631b · outbound

This paper cites Efficient non-maximum suppression,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Efficient non-maximum suppression,

Reference 37

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raw_fallback, observed 2026-08-05T20:09:04.031016Z

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.

source=pdf_text observed=2026-08-05T20:08:52.430393Z digest=sha256:5a0cc1dcadf7fc6fe6270d7985455a2daf327c0be3c4d94eaf64f01711522811

Observation 9a55b7d3-29f5-41f1-88f0-4847402dabcd · outbound

This paper cites End-to-end semi-supervised object detection with soft teacher,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering End-to-end semi-supervised object detection with soft teacher,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:09:03.623609Z

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.

source=pdf_text observed=2026-08-05T20:08:52.520095Z digest=sha256:c859d5523a665966b02c40db7fb10693f2b9babd95f2e52bdff03f623a93f00d

Observation 7492cb33-9926-4500-bada-e1838a3f8bc3 · outbound

This paper cites Dual teacher: Improv- ing the reliability of pseudo labels for semi-supervised oriented object detection,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Dual teacher: Improv- ing the reliability of pseudo labels for semi-supervised oriented object detection,

Reference 39

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raw_fallback, observed 2026-08-05T20:09:03.134897Z

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.

source=pdf_text observed=2026-08-05T20:08:52.609937Z digest=sha256:f5e945901f659b582532a929e3e4110da7dad466dfa166377d9324e18a6cf4a3

Observation 67536cf9-d15a-4586-8a1d-cdbed0270c30 · outbound

This paper cites Minimizing sample redundancy for label-efficient object detection in aerial images,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Minimizing sample redundancy for label-efficient object detection in aerial images,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:09:02.778693Z

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.

source=pdf_text observed=2026-08-05T20:08:52.739539Z digest=sha256:d1e2f5e8214b65d7b1020e48348084af1a7eab58e7ddc36c3dcadc8273704db3

Observation 4c87497e-2df9-43fd-99b3-9c447ba96bbc · outbound

This paper cites Omni-detr: Omni-supervised object detection with transformers,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Omni-detr: Omni-supervised object detection with transformers,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:09:02.468411Z

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.

source=pdf_text observed=2026-08-05T20:08:52.821082Z digest=sha256:10ed02927d67deaca12967c51893a485490dec5d571ac16cb943010e9e4fe996

Observation e5afbb5c-7237-4f5c-b5d6-759bc579720f · outbound

This paper cites Semi-detr: Semi-supervised object detection with detection transformers,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Semi-detr: Semi-supervised object detection with detection transformers,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:09:02.141298Z

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.

source=pdf_text observed=2026-08-05T20:08:52.889181Z digest=sha256:f5cde629d63a2c2ec5e3a724d1feee0f173b1f26acfe2dbf064254994e6e084c

Observation 5617345c-6c18-455c-97a1-72ee3350f8db · outbound

This paper cites Sparse semi-detr: sparse learnable queries for semi-supervised object detection,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Sparse semi-detr: sparse learnable queries for semi-supervised object detection,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:09:01.880667Z

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.

source=pdf_text observed=2026-08-05T20:08:52.973325Z digest=sha256:6feaf4a34ef15c8640c2bdd118819e10f55f87f3b37c4632cfe23b79ed9bd97c

Observation e400d1d0-fb08-492c-a14e-4785ff73600e · outbound

This paper cites Detect Everything with Few Examples.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Detect Everything with Few Examples

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-05T20:08:53.051705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:08:53.051705Z digest=sha256:d89f0078711ce6043e29e9bd5b090fcfadaf4e87bbf58d335266b5291f3f395c

Observation f2ce63a9-6d03-4146-8927-7e7fd11f81ee · outbound

This paper cites Cross-domain few-shot object detection via enhanced open-set object detector,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Cross-domain few-shot object detection via enhanced open-set object detector,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:09:01.586682Z

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.

source=pdf_text observed=2026-08-05T20:08:53.108399Z digest=sha256:9910d8a666f1b4b0296cdb0815b9fb892e348c6682a9fb9bcf8066f8f4b03e76

Observation 0b08ac77-2cf3-48b1-b9e0-d4afa4dd5101 · outbound

This paper cites Large self-supervised models bridge the gap in domain adaptive object detection,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Large self-supervised models bridge the gap in domain adaptive object detection,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:09:01.170851Z

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.

source=pdf_text observed=2026-08-05T20:08:53.200211Z digest=sha256:494cfca0c79f3814a4ba83494f299013b89ff94c6547bc99c3cbc3758ea3d98f

Observation 6d37af25-4fa4-4b02-bef1-9f48380f6a2a · outbound

This paper cites Frozen-DETR: Enhancing DETR with Image Understanding from Frozen Foundation Models.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Frozen-DETR: Enhancing DETR with Image Understanding from Frozen Foundation Models

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-08-05T20:08:56.483742Z

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.

source=pdf_text observed=2026-08-05T20:08:53.282856Z digest=sha256:e47004f84619dfef2153083c177735024331c719e678e28749b616a725ee9e35

Observation 68b90415-a97c-441d-a650-408c64a1a45a · outbound

This paper cites Good: Towards domain generalized oriented object detection,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Good: Towards domain generalized oriented object detection,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:09:00.963282Z

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.

source=pdf_text observed=2026-08-05T20:08:53.390220Z digest=sha256:13b875d182547198891cfe1c72b16774cf54ab5e68dd9ce37059e33a670d8d5e

Observation 04d14aaf-4e96-494a-adb7-02c094ef47bd · outbound

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

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Learning transferable visual models from natural language supervision,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:09:00.775574Z

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.

source=pdf_text observed=2026-08-05T20:08:53.468892Z digest=sha256:87c53bb107d212a60373704c62cd00597badba42b0b386a50668997dd41f2312

Observation 72f9efc5-5cba-472e-9549-42ba582306ad · outbound

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

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Dino: Detr with improved denoising anchor boxes for end-to- end object detection,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:09:00.531453Z

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.

source=pdf_text observed=2026-08-05T20:08:53.537820Z digest=sha256:6a201d8d7beec6fa9cb19a95df9eba781198281b1e9a31255e72dc8f3004e6ec

Observation c9cc54a7-6e8e-458b-a944-ccc5c66f1337 · outbound

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

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:09:00.272266Z

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.

source=pdf_text observed=2026-08-05T20:08:53.694175Z digest=sha256:58e734a71cf95bc8bc500f7aebe2bc5811cfa6e94f8a9de55a9a32d182788921

Observation beaf7ded-edca-4695-88ac-135aafba3513 · outbound

This paper cites Exploring robust features for few-shot object detection in satellite 15 imagery,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Exploring robust features for few-shot object detection in satellite 15 imagery,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:59.970440Z

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.

source=pdf_text observed=2026-08-05T20:08:53.820272Z digest=sha256:1a16fdb9d356e71b2499f54b610299aed7f366fb8549e8f5f3ac017764e662f1

Observation a68969ca-a610-4647-b52e-915fbd5b2f7a · outbound

This paper cites Segment any change,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Segment any change,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:59.689882Z

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.

source=pdf_text observed=2026-08-05T20:08:53.971238Z digest=sha256:abb03ba19b10c3656cc1f0695f9734bba09446e1b0c7c846be30a9349b409285

Observation ddc0fbd4-cec4-4c71-bf46-9e5ee33ebebb · outbound

This paper cites Evaluating General Purpose Vision Foundation Models for Medical Image Analysis: An Experimental Study of DINOv2 on Radiology Benchmarks.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Evaluating General Purpose Vision Foundation Models for Medical Image Analysis: An Experimental Study of DINOv2 on Radiology Benchmarks

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-05T20:08:54.089610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:08:54.089610Z digest=sha256:b61d95c419ed7225bd0c074e9fd8b62bf2ca52c3d308b5a0d7a8630e6bc87c91

Observation 07f1f4fe-bcd7-40cf-a1ec-702578effc50 · outbound

This paper cites Dino-reg: General purpose image encoder for training-free multi-modal deformable medical image registration,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Dino-reg: General purpose image encoder for training-free multi-modal deformable medical image registration,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:59.462094Z

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.

source=pdf_text observed=2026-08-05T20:08:54.212292Z digest=sha256:2218fc740363a81946f9d971b3d1c4e8e7fb2aa3c9c6a0b5a02c648d51ecb232

Observation fb5d9f0b-987f-4566-8110-613c60a30614 · outbound

This paper cites Mask r-cnn,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Mask r-cnn,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:59.165838Z

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.

source=pdf_text observed=2026-08-05T20:08:54.328610Z digest=sha256:edec0b42bf900cd9d77699d3cdb96c960f9d2c16943b9832d1858797f8a059a8

Observation c3026f7a-4b07-46a5-be0b-c1a3e94032ef · outbound

This paper cites Datr: Unsupervised domain adaptive detection transformer with dataset-level adaptation and prototypical alignment,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Datr: Unsupervised domain adaptive detection transformer with dataset-level adaptation and prototypical alignment,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:58.842173Z

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.

source=pdf_text observed=2026-08-05T20:08:54.447224Z digest=sha256:05f7edf9dab0c1b6da283568323d49c0997f76ca74555df433f652224b2df3be

Observation d4b738cb-16f7-4dbf-b80c-20b108414cba · outbound

This paper cites Every pixel matters: Center-aware feature alignment for domain adaptive object detector,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Every pixel matters: Center-aware feature alignment for domain adaptive object detector,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:58.652533Z

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.

source=pdf_text observed=2026-08-05T20:08:54.616273Z digest=sha256:87657fcc52084347be202dde4596c597ee740be183d5ed61071ebb2254e95e1f

Observation 2ba04edb-7462-416c-83bd-1e8620e83219 · outbound

This paper cites Instance relation graph guided source- free domain adaptive object detection,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Instance relation graph guided source- free domain adaptive object detection,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:58.326623Z

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.

source=pdf_text observed=2026-08-05T20:08:54.733832Z digest=sha256:c925ce09994af5501a19967719df4ff33b87e3b049fbfc6532d753addca6e782

Observation 0d0c8350-acbf-495e-b486-0aee02830c63 · outbound

This paper cites Enhanc- ing source-free domain adaptive object detection with low-confidence pseudo label distillation,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Enhanc- ing source-free domain adaptive object detection with low-confidence pseudo label distillation,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:58.110840Z

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.

source=pdf_text observed=2026-08-05T20:08:54.894840Z digest=sha256:2e357cca0ae68097e555cedf931cb449270e9f1a7156c632e1c6658056f14369

Observation d4cb0fac-2c7d-4571-84ea-e0d29dc21701 · outbound

This paper cites Unbiased teacher v2: Semi-supervised object detection for anchor-free and anchor-based detectors,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Unbiased teacher v2: Semi-supervised object detection for anchor-free and anchor-based detectors,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:57.924504Z

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.

source=pdf_text observed=2026-08-05T20:08:55.011939Z digest=sha256:6216bdc3f89d69c0469e412d56831dfb81acb8746e5d5725c213436036086305

Observation 9cf4977b-bc5f-4311-9eb5-4191e0661810 · outbound

This paper cites Multi-clue consistency learning to bridge gaps between general and oriented object in semi-supervised detection,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Multi-clue consistency learning to bridge gaps between general and oriented object in semi-supervised detection,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:57.647553Z

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.

source=pdf_text observed=2026-08-05T20:08:55.124372Z digest=sha256:34021b6a134b3306fe9a5ade1233a5dcfc35e96a5db77c44e598548bbff80008

Observation 79408df6-7501-428b-b9eb-da3f9f8b6274 · outbound

This paper cites Rareplanes: Synthetic data takes flight,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Rareplanes: Synthetic data takes flight,

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-05T20:08:55.240769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:08:55.240769Z digest=sha256:41e6c29b08710f5f93b2d75150ea2c736b77d215cb4d13d42eae6d98eac5fe90

Observation e7e87c9a-4204-43cb-a88d-d2ca0a287fa9 · outbound

This paper cites Unsupervised domain adaptation for remote- sensing vehicle detection using domain-specific channel recalibration,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Unsupervised domain adaptation for remote- sensing vehicle detection using domain-specific channel recalibration,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:57.430431Z

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.

source=pdf_text observed=2026-08-05T20:08:55.337003Z digest=sha256:d654d5e4e9bc1f576066948ea671405851530ae2d95d81ff1d2782e9cce26953

Observation 89219eac-06f4-46df-9832-23a8690fa143 · outbound

This paper cites Hierarchical similarity alignment for domain adaptive ship detection in sar images,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Hierarchical similarity alignment for domain adaptive ship detection in sar images,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:57.183475Z

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.

source=pdf_text observed=2026-08-05T20:08:55.463559Z digest=sha256:269429ce5a36e2d37c8a72f00adff2f33846ee80ca06b03f5c858e58a9b194fc

Observation 00e4ea2e-d8fc-4d94-a061-e294a2e3dee0 · outbound

This paper cites Fsda-detr: Few- shot domain-adaptive object detection transformer in remote sensing im- agery,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Fsda-detr: Few- shot domain-adaptive object detection transformer in remote sensing im- agery,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:08:57.013648Z

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.

source=pdf_text observed=2026-08-05T20:08:55.588907Z digest=sha256:ce2e8f18ff842d8a0f8ced55346dbc50bce9621b76a7bd5820b8af1332bad77b

Observation b5c4eac9-388f-4dfb-a6e4-32f10406619c · outbound

This paper cites Ima- genet: A large-scale hierarchical image database,.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Ima- genet: A large-scale hierarchical image database,

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-05T20:08:55.707635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:08:55.707635Z digest=sha256:805b0566782e43cdac5c00982df3d6ad2c57a9682e3e6bef75dd256a8ef7c4c8

Observation 33ad6b50-3203-4ae3-b8e5-fffb1b6cb9b3 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering Adam: A Method for Stochastic Optimization

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-05T20:08:55.823633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:08:55.823633Z digest=sha256:1183561b340b17ffa2098f1f170c03b26f2f1df6900d93b458dc5326747063c3

Observation 0b8aa0d4-6938-44dc-a674-241ebe62c9cd · outbound

This paper cites DINOv3.

MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering DINOv3

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-05T20:08:56.016306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:08:56.016306Z digest=sha256:d52f740c5a3b65ff2c7ac923cdf5b78b82d7af3a7b3a1fc09e94b59d3f32ace6

Pith citing papers

No inbound Pith citation observations are available.