Paper Citation Record · LEDGER

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking

As of 13 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 2 inbound Pith citation observations for arXiv:2411.15600.

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

pith.paper-citation-record.v1
2411.15600 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:09:18.356984Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:09:21.137235Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:47:30.785940Z

Reference resolution

51 of 51 outbound references displayed

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External citation measurements

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Outbound references

Observation c691b2e0-3aa4-4517-b7a8-de1014d9f763 · outbound

This paper cites Human mem- ory: A proposed system and its control processes.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Human mem- ory: A proposed system and its control processes

Reference 1

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This paper cites Hiptrack: Visual tracking with historical prompts.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Hiptrack: Visual tracking with historical prompts

Reference 2

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Observation 8a57c619-3fd1-4110-a336-57db4580f668 · outbound

This paper cites Lasot: A high-quality benchmark for large-scale single ob- ject tracking.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Lasot: A high-quality benchmark for large-scale single ob- ject tracking

Reference 3

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This paper cites Lasot: A high-quality large-scale single object tracking benchmark.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Lasot: A high-quality large-scale single object tracking benchmark

Reference 4

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Observation f2e1bfc6-d475-4fee-8d92-ffb21e0fc335 · outbound

This paper cites The ther- mal infrared visual object tracking vot-tir2015 challenge re- sults.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking The ther- mal infrared visual object tracking vot-tir2015 challenge re- sults

Reference 5

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Observation 3c47da88-d533-4e27-904e-94fd2c4cdf3f · outbound

This paper cites Siamese Natural Language Tracker: Tracking by Natural Language Descriptions with Siamese Trackers.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Siamese Natural Language Tracker: Tracking by Natural Language Descriptions with Siamese Trackers

Reference 6

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Observation 7ee7f2b0-718e-4e4a-9776-e6151e02ab5b · outbound

This paper cites Real-time visual object tracking with natural lan- guage description.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Real-time visual object tracking with natural lan- guage description

Reference 7

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Observation 44c9f2af-045c-42fa-8a7a-70f844a7e963 · outbound

This paper cites Siamese natural language tracker: Tracking by natural lan- guage descriptions with siamese trackers.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Siamese natural language tracker: Tracking by natural lan- guage descriptions with siamese trackers

Reference 8

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Observation b761f02c-1fd9-4117-bd35-8f0467b15c93 · outbound

This paper cites MemVLT: Vision-language tracking with adaptive memory- based prompts.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking MemVLT: Vision-language tracking with adaptive memory- based prompts

Reference 9

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Observation a56339be-e9c9-4f14-b7fe-fbf118c2f054 · outbound

This paper cites Consistencies are all you need for semi-supervised vision-language tracking.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Consistencies are all you need for semi-supervised vision-language tracking

Reference 10

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Observation 782e3fdb-7f13-423c-98a4-8e531c289e26 · outbound

This paper cites Divert more attention to vision-language tracking.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Divert more attention to vision-language tracking

Reference 11

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Observation a18ba0f9-cb3e-4228-ab3f-d09fe06e99c9 · outbound

This paper cites Divert more attention to vision-language object tracking.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Divert more attention to vision-language object tracking

Reference 12

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This paper cites Global instance tracking: Locating target more like humans.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Global instance tracking: Locating target more like humans

Reference 13

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Observation 2d5bd364-cf7e-4c6d-b4c7-e54bbbe5e165 · outbound

This paper cites A multi-modal global instance tracking benchmark (mgit): Better locating target in complex spatio-temporal and causal relationship.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking A multi-modal global instance tracking benchmark (mgit): Better locating target in complex spatio-temporal and causal relationship

Reference 14

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Observation e0ff01a6-a8e9-44e1-b151-b84c0f8c54c9 · outbound

This paper cites Sotverse: A user- defined task space of single object tracking.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Sotverse: A user- defined task space of single object tracking

Reference 15

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Observation c4eaebec-61c2-4c42-8e2e-a301cc81fb6e · outbound

This paper cites Rtracker: Recoverable track- ing via pn tree structured memory.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Rtracker: Recoverable track- ing via pn tree structured memory

Reference 16

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This paper cites The sixth visual object tracking vot2018 challenge results.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking The sixth visual object tracking vot2018 challenge results

Reference 17

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This paper cites The seventh visual object tracking vot2019 chal- lenge results.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking The seventh visual object tracking vot2019 chal- lenge results

Reference 18

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How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking The eighth visual object tracking vot2020 chal- lenge results

Reference 19

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Observation 3a1abc17-5ecc-43e2-aa9f-75e330ec33e5 · outbound

This paper cites The ninth visual object tracking vot2021 challenge results.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking The ninth visual object tracking vot2021 challenge results

Reference 20

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This paper cites The tenth visual object tracking vot2022 challenge re- sults.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking The tenth visual object tracking vot2022 challenge re- sults

Reference 21

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This paper cites Dtllm-vlt: Diverse text generation for visual language tracking based on llm.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Dtllm-vlt: Diverse text generation for visual language tracking based on llm

Reference 22

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This paper cites DTVLT: A Multi-modal Diverse Text Benchmark for Visual Language Tracking Based on LLM.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking DTVLT: A Multi-modal Diverse Text Benchmark for Visual Language Tracking Based on LLM

Reference 23

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This paper cites Visual Language Tracking with Multi-modal Interaction: A Robust Benchmark.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Visual Language Tracking with Multi-modal Interaction: A Robust Benchmark

Reference 24

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This paper cites Cross- modal target retrieval for tracking by natural language.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Cross- modal target retrieval for tracking by natural language

Reference 25

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Observation ede48084-bcb6-4c20-8c4b-64a06640b73b · outbound

This paper cites Tracking by natural language specification.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Tracking by natural language specification

Reference 26

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Observation 78a3cc78-8dba-4446-b3ca-29f268e31bd9 · outbound

This paper cites Unifying visual and vision-language tracking via contrastive learning.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Unifying visual and vision-language tracking via contrastive learning

Reference 27

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This paper cites Human memory.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Human memory

Reference 28

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This paper cites The visual object track- ing vot2016 challenge results.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking The visual object track- ing vot2016 challenge results

Reference 29

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This paper cites Context-aware integration of lan- guage and visual references for natural language tracking.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Context-aware integration of lan- guage and visual references for natural language tracking

Reference 30

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This paper cites Explicit visual prompts for visual object tracking.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Explicit visual prompts for visual object tracking

Reference 31

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This paper cites Auditory sensory (”echoic”) memory dysfunction in schizophrenia.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Auditory sensory (”echoic”) memory dysfunction in schizophrenia

Reference 32

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This paper cites ChatTracker: Enhancing Visual Tracking Performance via Chatting with Multimodal Large Language Model.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking ChatTracker: Enhancing Visual Tracking Performance via Chatting with Multimodal Large Language Model

Reference 33

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This paper cites Elysium: Exploring object-level perception in videos via mllm.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Elysium: Exploring object-level perception in videos via mllm

Reference 34

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This paper cites Semtrack: A large-scale dataset for semantic tracking in the wild.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Semtrack: A large-scale dataset for semantic tracking in the wild

Reference 35

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This paper cites Unified transformer with isomorphic branches for natural language tracking.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Unified transformer with isomorphic branches for natural language tracking

Reference 36

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This paper cites Describe and Attend to Track: Learning Natural Language guided Structural Representation and Visual Attention for Object Tracking.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Describe and Attend to Track: Learning Natural Language guided Structural Representation and Visual Attention for Object Tracking

Reference 37

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This paper cites Towards more flexible and accurate object tracking with natural language: Algo- rithms and benchmark.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Towards more flexible and accurate object tracking with natural language: Algo- rithms and benchmark

Reference 38

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This paper cites Online object tracking: A benchmark.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Online object tracking: A benchmark

Reference 39

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This paper cites Object track- ing benchmark.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Object track- ing benchmark

Reference 40

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This paper cites Autore- gressive queries for adaptive tracking with spatio-temporal transformers.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Autore- gressive queries for adaptive tracking with spatio-temporal transformers

Reference 41

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This paper cites Grounding-tracking-integration.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Grounding-tracking-integration

Reference 42

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This paper cites Webuav- 3m: A benchmark for unveiling the power of million-scale deep uav tracking.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Webuav- 3m: A benchmark for unveiling the power of million-scale deep uav tracking

Reference 43

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This paper cites Underwater Camouflaged Object Tracking Meets Vision-Language SAM2.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Underwater Camouflaged Object Tracking Meets Vision-Language SAM2

Reference 44

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This paper cites WebUOT-1M: Advancing Deep Underwater Object Tracking with A Million-Scale Benchmark.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking WebUOT-1M: Advancing Deep Underwater Object Tracking with A Million-Scale Benchmark

Reference 45

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This paper cites One-stream stepwise decreas- ing for vision-language tracking.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking One-stream stepwise decreas- ing for vision-language tracking

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:09:18.592456Z

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This paper cites One-stream vision-language memory network for object tracking.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking One-stream vision-language memory network for object tracking

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:09:18.575460Z

Source-reported events for the cited work

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Observation 0b10906b-48cd-4c07-9e97-30d1c1fd858d · outbound

This paper cites Transformer vision-language tracking via proxy token guided cross-modal fusion.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Transformer vision-language tracking via proxy token guided cross-modal fusion

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:09:18.558743Z

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Observation 7a4a8d23-6730-4448-af42-86aa5cfd59a4 · outbound

This paper cites Towards unified token learn- ing for vision-language tracking.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Towards unified token learn- ing for vision-language tracking

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:09:18.542702Z

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Observation f05b2deb-bb77-45d7-b166-5feaa4c7c507 · outbound

This paper cites Odtrack: Online dense temporal token learning for visual tracking.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Odtrack: Online dense temporal token learning for visual tracking

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:09:18.526689Z

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Observation 047e5346-a73f-4ae6-b1fe-3a345f869610 · outbound

This paper cites Joint vi- sual grounding and tracking with natural language specifica- tion.

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking Joint vi- sual grounding and tracking with natural language specifica- tion

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:09:18.511244Z

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Pith citing papers

Observation f9b351c5-372e-4071-9993-8bc2101de048 · inbound

Enhancing Vision-Language Tracking by Effectively Converting Textual Cues into Visual Cues cites this paper.

Enhancing Vision-Language Tracking by Effectively Converting Textual Cues into Visual Cues How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking

Reference 8

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Unavailable: canonical work link unavailable.

Observation 411cef07-8af4-4362-95f6-05eddc97d6ed · inbound

Vision-Language Guided Hyperspectral Object Tracking via Semantics Fusion and Contextual Template Updating cites this paper.

Vision-Language Guided Hyperspectral Object Tracking via Semantics Fusion and Contextual Template Updating How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:47:30.788092Z

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