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Paper Citation Record · LEDGER

Text-promptable Object Counting via Quantity Awareness Enhancement

As of 16 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2507.06679.

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

pith.paper-citation-record.v1
2507.06679 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:03:14.359160Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

51 of 51 outbound references displayed

  • verified exact0
  • verified fuzzy43
  • unresolved7
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1b43084b-4ce6-456f-a23f-5bf670a51709 · outbound

This paper cites Amini-Naieni, K.

Text-promptable Object Counting via Quantity Awareness Enhancement Amini-Naieni, K

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.890887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:11.756032Z digest=sha256:5a803eb16f88f60d245737009673ac7a17f55051dade90de785cc91066633795

Observation 6a879c51-57d3-431c-8f87-612785eddcbb · outbound

This paper cites Counting in the wild.

Text-promptable Object Counting via Quantity Awareness Enhancement Counting in the wild

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.882212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:11.855140Z digest=sha256:07fd37d6be3c703e44588dd0dc09a1accb93cc805fb38d0e76bb3bf7245809bd

Observation 500112ee-505e-45ae-a0dc-66daa2a5e3e5 · outbound

This paper cites Single domain generalization for few-shot counting via universal representation matching.

Text-promptable Object Counting via Quantity Awareness Enhancement Single domain generalization for few-shot counting via universal representation matching

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.873444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:12.008482Z digest=sha256:b3c71920e0e8c7ae0e24e4c32b1961eac22566500df4df9ddc6d5e71e4192b3b

Observation 5f00707e-27bb-4b5b-aa28-708f0aefad5c · outbound

This paper cites Reproducible scal- ing laws for contrastive language-image learning.

Text-promptable Object Counting via Quantity Awareness Enhancement Reproducible scal- ing laws for contrastive language-image learning

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.864603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:12.207656Z digest=sha256:658d89821163115964028e208541aaff74a622c05a9d472b3c36221c31708727

Observation 680db637-51f2-4d6b-aff1-3a02e6806c48 · outbound

This paper cites Referring ex- pression counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Referring ex- pression counting

Reference 5

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raw_fallback, observed 2026-08-06T19:03:14.855850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:12.362330Z digest=sha256:51a2cf7859d0c9d1acf4e1ced7805a2ae29fbfbf77ca04235f900dae72a80953

Observation f80e0924-0ebf-45eb-af89-c4f151ee05ac · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Text-promptable Object Counting via Quantity Awareness Enhancement BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T19:03:12.515848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:03:12.515848Z digest=sha256:96e5669b830b1479f2ce1ef401d7bf01eb9cf374463f2438dcfd2954323e63ca

Observation 8180d2db-6968-41a4-9b60-d70664b7d263 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Text-promptable Object Counting via Quantity Awareness Enhancement An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T19:03:12.663628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:03:12.663628Z digest=sha256:62a785e7ad63a17d861a99778f6b3379557b6d5b2539ca3d7e69817f8076a9b6

Observation 635dc7d4-38ab-4868-a28b-61b3fc094ff6 · outbound

This paper cites Semantic generative augmentations for few-shot counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Semantic generative augmentations for few-shot counting

Reference 8

Resolution
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raw_fallback, observed 2026-08-06T19:03:14.847132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:12.809890Z digest=sha256:cc55862fd9061195c8a8b4a9e25bade62b39149626b1368f3c493db21cbe6c2d

Observation be0f8fc6-d4ef-4604-bd20-cc6987db81ed · outbound

This paper cites Domain- general crowd counting in unseen scenarios.

Text-promptable Object Counting via Quantity Awareness Enhancement Domain- general crowd counting in unseen scenarios

Reference 9

Resolution
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raw_fallback, observed 2026-08-06T19:03:14.837875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:12.934299Z digest=sha256:c1f993a4a3c734e0dc75274d936cdc4c133a4746c209c9cb90492fc8df4de57f

Observation c93e8c55-8303-4e88-86b1-1d657ed87444 · outbound

This paper cites Regressor-segmenter mutual prompt learning for crowd counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Regressor-segmenter mutual prompt learning for crowd counting

Reference 10

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raw_fallback, observed 2026-08-06T19:03:14.828818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:13.043778Z digest=sha256:97b5bdb2f98eae2eeadc7220cf14aea4375ae7d3844c7e8afa98f6f5df6770ea

Observation 86609ac8-8681-41fe-930d-a5e880503009 · outbound

This paper cites Learning to count anything: Reference-less class-agnostic counting with weak supervision.

Text-promptable Object Counting via Quantity Awareness Enhancement Learning to count anything: Reference-less class-agnostic counting with weak supervision

Reference 11

Resolution
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raw_fallback, observed 2026-08-06T19:03:14.819489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:13.181810Z digest=sha256:b29161ff1676e6e210de66559cad6ea7988075b8d59b65eaf09164ff0fe285f0

Observation cc8285ee-cd98-4b62-b2f2-1ff53d286d25 · outbound

This paper cites Drone- based object counting by spatially regularized regional pro- posal network.

Text-promptable Object Counting via Quantity Awareness Enhancement Drone- based object counting by spatially regularized regional pro- posal network

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.808490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:13.336144Z digest=sha256:f09228c0b6384fceb81f7d647cd786cc7a3d2c883c35dca0fd6f37d3da7db947

Observation 4e59b03a-6458-417a-a7c6-fb4b3d094d87 · outbound

This paper cites Squeeze-and-excitation net- works.

Text-promptable Object Counting via Quantity Awareness Enhancement Squeeze-and-excitation net- works

Reference 13

Resolution
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raw_fallback, observed 2026-08-06T19:03:14.797655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:13.500887Z digest=sha256:e7546a7cbbe6c1aa527d6d1783012b57a77da5a3da4e7d45732ee783aa48ff69

Observation 6b49e444-b4cf-4313-b56b-c2301e876435 · outbound

This paper cites Class-agnostic object counting with text-to-image diffusion model.

Text-promptable Object Counting via Quantity Awareness Enhancement Class-agnostic object counting with text-to-image diffusion model

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.787162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:13.668208Z digest=sha256:9a0a6ab8ba05e19c0f1c94bbeecd545860d554a0119da1b4eb8a3d832c0619f7

Observation 2fb67742-57f0-472e-b09e-5bfe73087fb3 · outbound

This paper cites CLIP-Count: Towards Text-Guided Zero-Shot Object Counting.

Text-promptable Object Counting via Quantity Awareness Enhancement CLIP-Count: Towards Text-Guided Zero-Shot Object Counting

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T19:03:13.827855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:03:13.827855Z digest=sha256:87e35ba0ecdd58ad71169a98d1262bb0f41f9d31ab361968c8159063de5d71c1

Observation 933933cd-9e91-4384-80af-55eaf72b8014 · outbound

This paper cites Vlcounter: Text-aware visual representation for zero- shot object counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Vlcounter: Text-aware visual representation for zero- shot object counting

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.777528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:13.988148Z digest=sha256:614d06de6421837828968502586e5d9ba66c95d227deff938783b633d83e7a50

Observation 68977ed2-b2e4-4925-a79a-7952aa9db778 · outbound

This paper cites Calibrating uncertainty for semi-supervised crowd counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Calibrating uncertainty for semi-supervised crowd counting

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.768441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.113292Z digest=sha256:1416c1ca6852792c7e8954ad86177ff3c68ecd190475a3559efd11b46273e5fe

Observation 8be642c1-0e30-4155-ae93-6330ce20e5ab · outbound

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

Text-promptable Object Counting via Quantity Awareness Enhancement Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 18

Resolution
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raw_fallback, observed 2026-08-06T19:03:14.758786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.248427Z digest=sha256:5de3bfd77cd40795ae2649b4343ca82d8a439159e91e865f6c543243d28a72ed

Observation a11f7686-f1e3-49cd-b0dd-952017cf0310 · outbound

This paper cites Csrnet: Di- lated convolutional neural networks for understanding the highly congested scenes.

Text-promptable Object Counting via Quantity Awareness Enhancement Csrnet: Di- lated convolutional neural networks for understanding the highly congested scenes

Reference 19

Resolution
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raw_fallback, observed 2026-08-06T19:03:14.747454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.252308Z digest=sha256:a53c29ac5e44a2a2aff7ed90995f1fa2927e7a1ac43c821a8782e1353068273b

Observation e63d9729-f058-44f9-a751-190e48635d6e · outbound

This paper cites An end-to-end transformer model for crowd localization.

Text-promptable Object Counting via Quantity Awareness Enhancement An end-to-end transformer model for crowd localization

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.737791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.255496Z digest=sha256:42273bcbf719a1627c9ea38d647739896293cb2c1819cb6797abfcaa06e739d8

Observation 8cbf97ac-2163-4fa8-ae8f-12b5f4b6e1c6 · outbound

This paper cites Crowdclip: Unsupervised crowd counting via vision-language model.

Text-promptable Object Counting via Quantity Awareness Enhancement Crowdclip: Unsupervised crowd counting via vision-language model

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.728239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.258773Z digest=sha256:e8f3dd9a939de406e821bf9c1cdbc763c9dfb92587e94671f91af80b08cffa98

Observation e26a1a79-a668-437d-b34c-29ce96f66b11 · outbound

This paper cites A fixed-point approach to unified prompt-based counting.

Text-promptable Object Counting via Quantity Awareness Enhancement A fixed-point approach to unified prompt-based counting

Reference 22

Resolution
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raw_fallback, observed 2026-08-06T19:03:14.718661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.261778Z digest=sha256:f6f83822752c176876953bcdff6471b5fa80b8e92c5910efe6182d8b68a7a1fc

Observation b684f5be-b96a-4cbc-a6a9-4661f8513f43 · outbound

This paper cites CounTR: Transformer-based Generalised Visual Counting.

Text-promptable Object Counting via Quantity Awareness Enhancement CounTR: Transformer-based Generalised Visual Counting

Reference 23

Resolution
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no resolver link, observed 2026-08-06T19:03:14.264970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:03:14.264970Z digest=sha256:7f490b78b8c55f132b8637ec4b8b0c526c31d3320b295a206a841c92824db586

Observation 08d99d92-527d-4b08-8a86-e9f8065ae82a · outbound

This paper cites Point-query quadtree for crowd counting, localization, and more.

Text-promptable Object Counting via Quantity Awareness Enhancement Point-query quadtree for crowd counting, localization, and more

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.709217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.268563Z digest=sha256:3f38be62fbde20d92befd520943ed18b0c4917b2c825b2ddf27058d670d71d60

Observation a04d2699-2b1e-4e3d-9101-30a3e581fad7 · outbound

This paper cites Visual instruction tuning.

Text-promptable Object Counting via Quantity Awareness Enhancement Visual instruction tuning

Reference 25

Resolution
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no resolver link, observed 2026-08-06T19:03:14.272434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:03:14.272434Z digest=sha256:bcbaf31adb69738dcdf011324a42dfa628871b6597bf0a42832757d2bb107895

Observation 4b83e397-a3d5-4b96-8ab2-b86f49e8917e · outbound

This paper cites Point in, box out: Beyond counting persons in crowds.

Text-promptable Object Counting via Quantity Awareness Enhancement Point in, box out: Beyond counting persons in crowds

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.692793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.275889Z digest=sha256:10dfce2dec43b626fde7a8dd46d9658407f71c4145c8b737295ae7fc91a68b04

Observation 5856f389-3525-42f4-bb00-8149833bd6cc · outbound

This paper cites Discovering regression- detection bi-knowledge transfer for unsupervised cross- domain crowd counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Discovering regression- detection bi-knowledge transfer for unsupervised cross- domain crowd counting

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.683555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.279115Z digest=sha256:a4df158fc5c524a39ea049527c49c3532cb15c3e0fabea561f60b4fe6ed9dcfd

Observation 82c96d3d-53ae-4164-9e44-4592383a14f9 · outbound

This paper cites Decoupled Weight Decay Regularization.

Text-promptable Object Counting via Quantity Awareness Enhancement Decoupled Weight Decay Regularization

Reference 28

Resolution
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no resolver link, observed 2026-08-06T19:03:14.282618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:03:14.282618Z digest=sha256:2e39b757b6d65df0ca0aaba7eb3d05a9c8081cadf0c9c121f5f2588db3de78c5

Observation 73dffed5-95b3-4402-bc39-cff05a59673e · outbound

This paper cites Class-agnostic counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Class-agnostic counting

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.674254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.286277Z digest=sha256:c0bd5fd21b0516c48b212bf0a88905844750b139d424249db3505c34ba583885

Observation 4cd6cedc-74eb-4cb8-9aad-766edbb94a62 · outbound

This paper cites A large contextual dataset for classification, detection and counting of cars with deep learning.

Text-promptable Object Counting via Quantity Awareness Enhancement A large contextual dataset for classification, detection and counting of cars with deep learning

Reference 30

Resolution
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raw_fallback, observed 2026-08-06T19:03:14.655112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.292958Z digest=sha256:13a877aac0ee96d57574e250434ec1eeb78c663c9c3d4648d0f11d09d4563dde

Observation 1414730d-c8f4-453f-a839-8267914b28c9 · outbound

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

Text-promptable Object Counting via Quantity Awareness Enhancement DINOv2: Learning Robust Visual Features without Supervision

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T19:03:14.296199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:03:14.296199Z digest=sha256:ab33d7c24330ab5e233340878391d6fa6d70a1348f12ba532914f504db6f0372

Observation bdf143f4-23a1-417c-a970-e3a7b32ae3f0 · outbound

This paper cites Teaching clip to count to ten.

Text-promptable Object Counting via Quantity Awareness Enhancement Teaching clip to count to ten

Reference 32

Resolution
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raw_fallback, observed 2026-08-06T19:03:14.645611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.299893Z digest=sha256:1fbf66454517863fb2c87f18ad5f24e66dd3dee21ebe004e4369b1b7ddcb1a82

Observation 1a159c29-e07f-4069-9b8f-7ba2bb170997 · outbound

This paper cites Dave-a detect-and-verify paradigm for low-shot counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Dave-a detect-and-verify paradigm for low-shot counting

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.635120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.303151Z digest=sha256:aedeadbb5da02e8c9a63df74f86d3a1134b95cdea0505f0f84a06c75ed3cd5e8

Observation 14541c31-c6e2-4505-9d8b-50dfe9a3b7e1 · outbound

This paper cites Single domain general- ization for crowd counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Single domain general- ization for crowd counting

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.624862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.306244Z digest=sha256:be0396ffee4471e116d4405e615451fc3ee8bba516d678dfcfaa2598ee0aa489

Observation 68abffb7-6daf-4b1f-aa3f-69862a3c268e · outbound

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

Text-promptable Object Counting via Quantity Awareness Enhancement Learning transferable visual models from natural language supervi- sion

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.615809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.309659Z digest=sha256:37ee4cf4757aeac7adcbaffb2325ab434a1c8bc848d83430e6f1a6dda299b3bb

Observation 238ae5d4-eea2-433c-9f3e-442db6657d4a · outbound

This paper cites Crowd- diff: Multi-hypothesis crowd density estimation using dif- fusion models.

Text-promptable Object Counting via Quantity Awareness Enhancement Crowd- diff: Multi-hypothesis crowd density estimation using dif- fusion models

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.606770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.312912Z digest=sha256:2e79688163ac1cc84fab45ff592cf69b4eefc3ceeec5b8e31ccb8f46c095877c

Observation 8132fe31-cf19-41c6-bbd4-c2758220a6e9 · outbound

This paper cites Exemplar free class agnostic counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Exemplar free class agnostic counting

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.598077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.316720Z digest=sha256:56dd994e42cb1a5fa240fb68e9f314cc44747fe5c2bf37b2de9b59f4a4fc762d

Observation ed8ebee9-e039-4a93-93ad-bd858085d368 · outbound

This paper cites Learning to count everything.

Text-promptable Object Counting via Quantity Awareness Enhancement Learning to count everything

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.588993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.320330Z digest=sha256:5e7ecd4db0b2494170827d34f00ba37bc67e3eab58bb8d0c5dae8d422135b784

Observation 61595131-0c72-45d7-a097-d83dda69a760 · outbound

This paper cites Re- visiting perspective information for efficient crowd counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Re- visiting perspective information for efficient crowd counting

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.580574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.323890Z digest=sha256:ef03754cffbe70d247c8d9fc1d89690801de28105f007520f3f641533174a8a8

Observation 41d12455-4aa8-40f0-af7a-33be658ab79f · outbound

This paper cites Represent, compare, and learn: A similarity-aware framework for class-agnostic counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Represent, compare, and learn: A similarity-aware framework for class-agnostic counting

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.571612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.327129Z digest=sha256:28e3ca1badf3b1bbf1a4316826c0215fc9c3413efd18642117bb406b0016d182

Observation cba8e512-6910-4820-b35d-c9ad0ec957a1 · outbound

This paper cites A low-shot object counting network with iterative prototype adaptation.

Text-promptable Object Counting via Quantity Awareness Enhancement A low-shot object counting network with iterative prototype adaptation

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.562421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.330624Z digest=sha256:81a911f247780fe4d93d34d15f221a90c445eec4dd0c26267286e81af9ec7d94

Observation 4daf5d26-5653-492e-8dfc-25c2b3b7e2e3 · outbound

This paper cites Exploring contextual at- tribute density in referring expression counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Exploring contextual at- tribute density in referring expression counting

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.551971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.333749Z digest=sha256:39574f816b018b95d9ec733689facac24cd05cd0393c8414d8d7e7b25a1e0c27

Observation 66e7977d-fc36-4c2b-aae4-222b2c8224af · outbound

This paper cites Learning super-features for image re- trieval.

Text-promptable Object Counting via Quantity Awareness Enhancement Learning super-features for image re- trieval

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.541890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.337057Z digest=sha256:e3b16d1d39dc4b96f58ae21fd645809d397582d55c1c6c2be4f3697cfc5745e9

Observation 04a5182f-2e08-46c3-9a5d-3738b17520aa · outbound

This paper cites Boosting detection in crowd analysis via underutilized output features.

Text-promptable Object Counting via Quantity Awareness Enhancement Boosting detection in crowd analysis via underutilized output features

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.531135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.340400Z digest=sha256:ac08568426aeaaaad4910cb84589a40fd5aa70694c3fab01cce4b9c5beb2d488

Observation 0c5d6c1a-8e72-44fa-a2d3-21700f62f76a · outbound

This paper cites Mi- croscopy cell counting and detection with fully convolutional regression networks.

Text-promptable Object Counting via Quantity Awareness Enhancement Mi- croscopy cell counting and detection with fully convolutional regression networks

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.519363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.344297Z digest=sha256:ecacd8f70ea3660ec2779b58eaca162917671b0851fa23689279b7ac7fc0f058

Observation e122f068-60b0-4449-8d4d-23805985a82d · outbound

This paper cites Zero-shot object counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Zero-shot object counting

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.507244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.347506Z digest=sha256:4ba0d816acbe63d45a02eb0ea04ff5a0d215cf756a6a517c689c27f406f8f859

Observation a2bd59cf-c646-4118-933d-9571d387bcaa · outbound

This paper cites Pbe- count: Prompt-before-extract paradigm for class-agnostic counting.

Text-promptable Object Counting via Quantity Awareness Enhancement Pbe- count: Prompt-before-extract paradigm for class-agnostic counting

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.495914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.350170Z digest=sha256:808b677972a0fd098577a428cde459c4779d3cae7c07c55d3356af4b163b859f

Observation a3f8dec9-8a88-4e03-8526-ac7578b92a9b · outbound

This paper cites Zero-shot object counting with vision-language prior guid- ance network.

Text-promptable Object Counting via Quantity Awareness Enhancement Zero-shot object counting with vision-language prior guid- ance network

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.484629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.353235Z digest=sha256:836cda9c6406cc92d650e2c12055c9de5df08b49ba8838c29ff6ef933ebb0f1c

Observation 8fcfa3dc-27fa-4651-97d0-72bbeb6aa9f1 · outbound

This paper cites Single-image crowd counting via multi-column convolutional neural network.

Text-promptable Object Counting via Quantity Awareness Enhancement Single-image crowd counting via multi-column convolutional neural network

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.473369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.356291Z digest=sha256:4fddc2d3e7713292140d03183e0da0b1645fde27861616bd148d0ab8cd82b92b

Observation 8e5d9146-184f-4464-a116-2c4ecb6df9d2 · outbound

This paper cites Zero-shot object counting with good exemplars.

Text-promptable Object Counting via Quantity Awareness Enhancement Zero-shot object counting with good exemplars

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:03:14.461903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.359160Z digest=sha256:070b3a7a1fb496e75c200163fc7d9871d8978a12b994beaa9a9e489f0e6b831d

Observation 19773813-f6df-438a-9924-8cd2823bbbdb · outbound

This paper cites an unresolved cited work.

Text-promptable Object Counting via Quantity Awareness Enhancement Unresolved cited work

Reference 684

Resolution
parse uncertain
raw_fallback, observed 2026-08-06T19:03:14.664976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:03:14.289717Z digest=sha256:027ceef7e27739961d2c2780c5378ead9188ba6580ee09d7d1b00c813f7f34fd

Pith citing papers

No inbound Pith citation observations are available.