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Paper Citation Record · LEDGER

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation

As of 5 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 0 inbound Pith citation observations for arXiv:2606.00987.

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

pith.paper-citation-record.v1
2606.00987 v1

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T17:40:16.265708Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+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

70 of 70 outbound references displayed

  • verified exact22
  • verified fuzzy0
  • unresolved44
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a88b726d-ff30-4912-ba73-140fb83f7d80 · outbound

This paper cites GPT-4 Technical Report.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation GPT-4 Technical Report

Reference 1

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local_arxiv, observed 2026-07-01T20:46:14.164447Z

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Observation a6198e52-cdc5-447d-ae4c-9857bcd0e90a · outbound

This paper cites Qwen3 Technical Report.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Qwen3 Technical Report

Reference 2

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local_arxiv, observed 2026-07-01T20:46:14.213949Z

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Observation e0e549da-0763-4e7c-88b5-adefa676b1a5 · outbound

This paper cites Qwen Technical Report.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Qwen Technical Report

Reference 3

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Observation 386e7487-fbca-4357-9a91-1f5c7d6fdabd · outbound

This paper cites F- lmm: Grounding frozen large multimodal models,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation F- lmm: Grounding frozen large multimodal models,

Reference 4

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Observation faacc1f0-c7ba-4061-bbc9-27be9e0ca036 · outbound

This paper cites arXiv preprint arXiv:2510.18262 (2025) SOUBench 19.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation arXiv preprint arXiv:2510.18262 (2025) SOUBench 19

Reference 5

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arxiv_id, observed 2026-07-01T20:46:14.216373Z

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Observation 99f573e4-a6f1-4736-b71b-5bfa43119794 · outbound

This paper cites Lisa: Reasoning segmentation via large language model,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Lisa: Reasoning segmentation via large language model,

Reference 6

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Observation 3d28aca3-9ec8-46d3-bdd9-71b9796fd0f0 · outbound

This paper cites Remotesam: Towards segment anything for earth observation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Remotesam: Towards segment anything for earth observation,

Reference 7

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Observation 756d752b-a23e-4021-b726-bdd33912de47 · outbound

This paper cites Videoglamm: A large multimodal model for pixel-level visual grounding in videos,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Videoglamm: A large multimodal model for pixel-level visual grounding in videos,

Reference 8

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Observation 5a416c7d-2231-4f5a-9b7c-d584ae41fc0a · outbound

This paper cites Glamm: Pixel grounding large multimodal model,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Glamm: Pixel grounding large multimodal model,

Reference 9

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Observation 7243a222-074b-4b85-896e-2e09d155ba10 · outbound

This paper cites Ai flow: Perspectives, scenarios, and approaches,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Ai flow: Perspectives, scenarios, and approaches,

Reference 10

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Observation a5333b60-ef10-4b2a-83c6-54081fa536f4 · outbound

This paper cites Stare-vla: Progressive stage-aware reinforcement for fine- tuning vision-language-action models.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Stare-vla: Progressive stage-aware reinforcement for fine- tuning vision-language-action models

Reference 11

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Observation 2af199be-5159-4e5c-bdc1-8309168697e9 · outbound

This paper cites Fine-grained preference optimiza- tion improves spatial reasoning in vlms.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Fine-grained preference optimiza- tion improves spatial reasoning in vlms

Reference 12

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arxiv_id, observed 2026-07-01T20:46:14.190814Z

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Observation ee6344e3-c40b-4c3e-80bd-00d037102112 · outbound

This paper cites Toward cognitive supersensing in multimodal large language model.arXiv preprint arXiv:2602.01541.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Toward cognitive supersensing in multimodal large language model.arXiv preprint arXiv:2602.01541

Reference 13

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Observation db18d797-4cfe-481c-a9c4-41f324f48041 · outbound

This paper cites Egoforge: Goal-directed egocen- tric world simulator.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Egoforge: Goal-directed egocen- tric world simulator

Reference 14

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Observation 87d26cf6-af90-4253-b73c-3139d9a37f39 · outbound

This paper cites Sarkar, M.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Sarkar, M

Reference 15

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Observation 733fa65d-e51f-4006-abce-e1b0b86615e9 · outbound

This paper cites Towards Transparent AI: A Survey on Explainable Large Language Models.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Towards Transparent AI: A Survey on Explainable Large Language Models

Reference 16

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Observation 3b36b617-7fb5-4586-9d14-a35eea7e5c46 · outbound

This paper cites Yielding unblemished aesthetics through a unified network for visual imperfections removal in generated images,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Yielding unblemished aesthetics through a unified network for visual imperfections removal in generated images,

Reference 17

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Observation 4f686098-1e85-41e2-ac72-ccae06458cce · outbound

This paper cites Cotextor: Training- free modular multilingual text editing via layered disentanglement and depth-aware fusion,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Cotextor: Training- free modular multilingual text editing via layered disentanglement and depth-aware fusion,

Reference 18

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Observation 27f99180-5f71-4e60-a204-f8c62b53e71c · outbound

This paper cites Forgetme: Benchmarking the selective forgetting capabilities of generative models,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Forgetme: Benchmarking the selective forgetting capabilities of generative models,

Reference 19

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Observation 2f410424-bc24-46c9-8a69-d5cac1812941 · outbound

This paper cites Tri- subspaces disentanglement for multimodal sentiment analysis,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Tri- subspaces disentanglement for multimodal sentiment analysis,

Reference 20

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Observation ff76da4f-f106-456e-a4d9-fbfd514d06e0 · outbound

This paper cites Generative video compression: towards 0.01% compression rate for video transmission,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Generative video compression: towards 0.01% compression rate for video transmission,

Reference 21

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Observation 9e859310-7427-42a8-aead-a46f796b3f4c · outbound

This paper cites Geobench-vlm: Benchmarking vision-language models for geospatial tasks,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Geobench-vlm: Benchmarking vision-language models for geospatial tasks,

Reference 22

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Observation 12034758-bd3b-4643-9cfc-4f15709b750e · outbound

This paper cites Geomag: A vision-language model for pixel-level fine-grained remote sensing image parsing,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Geomag: A vision-language model for pixel-level fine-grained remote sensing image parsing,

Reference 23

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Observation d0c7bef5-3ad5-44d7-882b-941a180e2791 · outbound

This paper cites GeoPixel: Pixel Grounding Large Multimodal Model in Remote Sensing.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation GeoPixel: Pixel Grounding Large Multimodal Model in Remote Sensing

Reference 24

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arxiv_id, observed 2026-07-01T20:46:14.192236Z

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Observation 44c2dc00-cb64-4c8e-afd7-9aa40009251c · outbound

This paper cites Dinov3-powered multi- task foundation model for quantitative remote sensing estimation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Dinov3-powered multi- task foundation model for quantitative remote sensing estimation,

Reference 25

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Observation c980e607-7c2d-43a0-ad46-e386644e0d33 · outbound

This paper cites Visualizing our changing earth: A creative ai framework for democratizing environmental storytelling through satellite imagery,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Visualizing our changing earth: A creative ai framework for democratizing environmental storytelling through satellite imagery,

Reference 26

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Observation d68a5817-e438-40a4-9c49-4b75c11f5653 · outbound

This paper cites Spatiotemporal alignment for remote sensing image recovery via terrain-aware diffusion,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Spatiotemporal alignment for remote sensing image recovery via terrain-aware diffusion,

Reference 27

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Observation 31fd2b20-15aa-4204-ac7d-8909cd1e52bf · outbound

This paper cites Maris: Marine open-vocabulary in- stance segmentation with geometric enhancement and se- mantic alignment.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Maris: Marine open-vocabulary in- stance segmentation with geometric enhancement and se- mantic alignment

Reference 28

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Observation 157da8f6-092d-4ba4-ac1a-e0fd77cc935e · outbound

This paper cites Convolutions die hard: Open-vocabulary segmentation with single frozen convolutional clip,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Convolutions die hard: Open-vocabulary segmentation with single frozen convolutional clip,

Reference 29

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Observation e4b94894-d8e1-4b26-aa62-514cc51a1646 · outbound

This paper cites Diffusion models for open-vocabulary segmentation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Diffusion models for open-vocabulary segmentation,

Reference 30

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Observation 4d4a4dae-74b4-4978-be14-178c0f84f9f8 · outbound

This paper cites Cat- seg: Cost aggregation for open-vocabulary semantic segmentation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Cat- seg: Cost aggregation for open-vocabulary semantic segmentation,

Reference 31

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Observation 4a2349cc-104a-435e-96d8-f2f76257c0ca · outbound

This paper cites Exploring the underwater world segmentation without extra training.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Exploring the underwater world segmentation without extra training

Reference 32

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arxiv_id, observed 2026-07-01T20:46:14.189718Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation f5aecb79-6bb3-4d65-88f4-4050e988a015 · outbound

This paper cites Exploring efficient open-vocabulary segmentation in the remote sensing.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Exploring efficient open-vocabulary segmentation in the remote sensing

Reference 33

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arxiv_id, observed 2026-07-01T20:46:14.203116Z

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Observation eb032346-130f-4d10-a3b3-52fa6bb19821 · outbound

This paper cites A simple framework for open-vocabulary segmentation and detection,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation A simple framework for open-vocabulary segmentation and detection,

Reference 34

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Observation e37f32d6-6377-4bc8-885d-19ed37c1634d · outbound

This paper cites Open-Vocabulary Universal Image Segmentation with MaskCLIP.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Open-Vocabulary Universal Image Segmentation with MaskCLIP

Reference 35

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arxiv_id, observed 2026-07-01T20:46:14.181598Z

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Observation 8bd25363-6166-44e0-9148-42d1f80acebf · outbound

This paper cites Polyformer: Referring image segmentation as sequential polygon generation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Polyformer: Referring image segmentation as sequential polygon generation,

Reference 36

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Observation b7e684e8-876c-42c3-bba0-1d740faa619a · outbound

This paper cites Toward robust referring image segmentation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Toward robust referring image segmentation,

Reference 37

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:97c10927981093941040c2e8a9e4ed9fb828bd88e24db605faaf885a03b1a12e

Observation 93f4eb1b-1afd-496d-87af-8e0460bc41aa · outbound

This paper cites Rotated multi-scale interaction network for referring remote sensing image seg- mentation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Rotated multi-scale interaction network for referring remote sensing image seg- mentation,

Reference 38

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:ff3361fe7950acc1ec5b34f5547e05b175f2d94c8ca83bdb6ff6ff3d0c657979

Observation 107e43cd-717f-435f-a019-79aa9b790423 · outbound

This paper cites Lqmformer: Language-aware query mask transformer for referring image segmentation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Lqmformer: Language-aware query mask transformer for referring image segmentation,

Reference 39

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:1cc2c9e58856dddb4880ef15e12711b3ff96539e654efaee91fc84825a981847

Observation 726183f7-5b03-4209-adab-5bfa650b28e0 · outbound

This paper cites A survey of language-guided video object segmentation: from referring to reasoning,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation A survey of language-guided video object segmentation: from referring to reasoning,

Reference 40

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:ba4b16f5366c4968d9b71f89233ca8054a290ad03323276e75f81b913f7d2048

Observation 3fd8ddec-fc60-4b95-850c-fd982ffd5b2f · outbound

This paper cites Adaptive selection based referring image segmentation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Adaptive selection based referring image segmentation,

Reference 41

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:a31014be7c6c5b21711a009eb8b599800372526025c3fb6fa66f43a98f6756bd

Observation 8c9ba2e8-83c3-48c3-956f-db1c22483370 · outbound

This paper cites Rsrefseg: Refer- ring remote sensing image segmentation with foundation models,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Rsrefseg: Refer- ring remote sensing image segmentation with foundation models,

Reference 42

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:25d413b6a7cbe21b21e757978ed9f680a33b82ced3633ce555f934f91191954f

Observation 0b8480fb-a4df-4ba9-8a30-95ebb747e862 · outbound

This paper cites Referring Remote Sensing Image Segmentation with Cross-view Semantics Interaction Network.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Referring Remote Sensing Image Segmentation with Cross-view Semantics Interaction Network

Reference 43

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arxiv_id, observed 2026-07-01T20:46:14.208362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:d760ee48886fae54695e18e100c8e2086dd141890bcaadba172c255b0531af15

Observation b30691bb-55c7-4280-aaeb-08f06d8cbdba · outbound

This paper cites Deris: Decoupling perception and cognition for enhanced referring image segmentation through loopback synergy,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Deris: Decoupling perception and cognition for enhanced referring image segmentation through loopback synergy,

Reference 44

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:2282d0d58e90657b2bb43dae34a7a3096b68e2ff9bd3de7db889fb07c19bb2fe

Observation 7af768d3-d5e3-47e5-a58f-47ec0412fa35 · outbound

This paper cites Lavt: Language-aware vision transformer for referring image segmentation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Lavt: Language-aware vision transformer for referring image segmentation,

Reference 45

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:6ef0eacf973187dd1c4d7a767640c3bca8d3b37ba04ce412380dcf71af0469ba

Observation 041aaf67-9059-433b-80b4-35e9c57ea6fd · outbound

This paper cites Gres: Generalized referring expression segmentation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Gres: Generalized referring expression segmentation,

Reference 46

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:d2bc199de6947272e45c98366c4f8d6e162f47feea0c2baf0295fcfbdc8f6e17

Observation b8e467a4-0021-4335-85bb-9504af4634de · outbound

This paper cites Mask grounding for referring image segmentation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Mask grounding for referring image segmentation,

Reference 47

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:b6d7f62c845fc43127822bb906f703e53d4eadb82dad3b1d1ae22cbb861377ee

Observation 75a8a89c-a09f-45b6-9850-41ad423f7087 · outbound

This paper cites SegLLM: Multi-round Reasoning Segmentation.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation SegLLM: Multi-round Reasoning Segmentation

Reference 48

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arxiv_id, observed 2026-07-01T20:46:14.182343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:0cc974add2f607f571b4dea1dbafb5ee3a9983dfd3861421cc7743f4d71f7bd7

Observation 99dbdaa5-f54f-43cb-989b-8cf35a603dd1 · outbound

This paper cites Reasoning Segmentation for Images and Videos: A Survey.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Reasoning Segmentation for Images and Videos: A Survey

Reference 49

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arxiv_id, observed 2026-07-01T20:46:14.156308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:d0e82634358637c51041fd3cc9bdab2beff4b249c53d0e9298da29449707abf3

Observation 6262dea8-79f3-4bf1-ad9e-5b2c0a861604 · outbound

This paper cites Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement

Reference 50

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local_arxiv, observed 2026-07-01T20:46:14.161959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:ae9041a8cb8402bed0865d24ad186aa63149e21a6783b7e534a69f2b2f4e3458

Observation 24910f6d-07cf-422e-b5f3-ece4397050b8 · outbound

This paper cites LISA++: An Improved Baseline for Reasoning Segmentation with Large Language Model.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation LISA++: An Improved Baseline for Reasoning Segmentation with Large Language Model

Reference 51

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arxiv_id, observed 2026-07-01T20:46:14.171607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:cd21ae51b03b1a4ff7d6ffb26e3569a37ab490312e78b54e187b93873131ac93

Observation fc042287-b249-459e-b042-f1df4dbba405 · outbound

This paper cites Dataset on underwater change detection,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Dataset on underwater change detection,

Reference 52

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:3d4e91458b535b0ff0171b633da461bb0e07dd86740804965cc853fcc18a3ccd

Observation 269e7fc8-94f7-460f-9f88-e2302d504874 · outbound

This paper cites Mds- net: An image-text enhanced multimodal dual-branch siamese network for remote sensing change detection,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Mds- net: An image-text enhanced multimodal dual-branch siamese network for remote sensing change detection,

Reference 53

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:4235e7f60e3c6e1df9f2b45e10354e2f73ca267d270e26c62e80c977168639df

Observation 68c8aed3-ad50-451d-98a3-0465981abfa8 · outbound

This paper cites Qrs-trs: Style transfer-based image-to-image translation for carbon stock estimation in quantitative remote sensing,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Qrs-trs: Style transfer-based image-to-image translation for carbon stock estimation in quantitative remote sensing,

Reference 54

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:612bc0ccc73394e16ae7d70db3cd3b95f153a02fd9bd2f4ca2ba6cd16a353066

Observation 34876e45-82f6-410b-b6d1-0bcf5f017603 · outbound

This paper cites DynamicEarth: How Far are We from Open-Vocabulary Change Detection?.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation DynamicEarth: How Far are We from Open-Vocabulary Change Detection?

Reference 55

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arxiv_id, observed 2026-07-01T20:46:14.178562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:778b288ea10d40ac5a1599b6a887e6edec524bdc1446d59b150224219dd6c3fa

Observation d68b17bd-4409-4c9c-9ad9-f32b7acc8bca · outbound

This paper cites Semantic-cd: Remote sensing image semantic change detection towards open-vocabulary setting,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Semantic-cd: Remote sensing image semantic change detection towards open-vocabulary setting,

Reference 56

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:7bc7f77946b62901bfc9310eb5ae88210ef2be7e61b03cd769e322a911ec2b8b

Observation 39a0002f-7a89-4372-912d-8ca6077f836a · outbound

This paper cites Unichange: Unifying change detection with multimodal large language model.arXiv preprint arXiv:2511.02607.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Unichange: Unifying change detection with multimodal large language model.arXiv preprint arXiv:2511.02607

Reference 57

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:2b31989c57e60019dc1e75137a929db44610f420403c6010e361516b24a7eef9

Observation f5c814ed-b30b-4a55-a3c4-3b38419a37c1 · outbound

This paper cites Referring change detection in remote sensing imagery,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Referring change detection in remote sensing imagery,

Reference 58

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:2396c5fd968a2796c04186a9dffdbae45889c521519807d2cb2c57d9515cd395

Observation b3ad838a-468b-4437-92f2-caaf20dca015 · outbound

This paper cites Changechat: An interactive model for remote sensing change analysis via multimodal instruction tuning,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Changechat: An interactive model for remote sensing change analysis via multimodal instruction tuning,

Reference 59

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:7c0a04ec1a01a02c57d7f7784f837d8ca6c401453ead2f14df17f6ffcd29817b

Observation 897820a2-7a06-4b6f-8922-8448c0d59f36 · outbound

This paper cites SegChange-R1: LLM-Augmented Remote Sensing Change Detection.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation SegChange-R1: LLM-Augmented Remote Sensing Change Detection

Reference 60

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arxiv_id, observed 2026-07-01T20:46:14.197919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:36c64753ae71fbc5779abf366d82d101ae68e4d18ff6b17cf94967caffc70d7e

Observation a69347af-56bc-455a-8495-89411de767a3 · outbound

This paper cites Viewpoint Integration and Registration with Vision Language Foundation Model for Image Change Understanding.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Viewpoint Integration and Registration with Vision Language Foundation Model for Image Change Understanding

Reference 61

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arxiv_id, observed 2026-07-01T20:46:14.211728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:baa705fd53889c700b8bcb7977010bc34373f29ec75982fd1882932421596e43

Observation 1d90989a-9fc2-4e25-b726-7d0f8bf3b2d3 · outbound

This paper cites Modeling context in referring expressions,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Modeling context in referring expressions,

Reference 62

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:419171f319c1045dc20955408f81d56f21db24cb8d24aa1fc9135d2a8a131d0f

Observation 7bd51686-e612-4e48-ae59-82ea51cad6a4 · outbound

This paper cites Rrsis: Referring remote sensing image segmentation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Rrsis: Referring remote sensing image segmentation,

Reference 63

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:d6f1684659aaffc800a3e4ae1c0756cc13d2b2d943e05d431eeef3c4e5ec55f3

Observation 4711ecdb-aac1-480f-a009-c5ca83a235e9 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 64

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:2239a4e393c7102eb505ea045d6b0f1a36fdd4eecd1872dfd2b42b9671f8b68a

Observation 5e3cb0ed-e35f-4d7e-9830-7cff9c11df97 · outbound

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

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Learning transferable visual models from natural language supervision,

Reference 65

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:bef3b65dfc6f469d3485919ac3d5db5a53b44abbf92ceca8e4850ce74d118ed6

Observation a160db88-cbfd-452e-a1da-8329ba0f9338 · outbound

This paper cites Cris: Clip- driven referring image segmentation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Cris: Clip- driven referring image segmentation,

Reference 66

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source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:9a7f880dde864596f8d2eaf6afc30867119d259b6c73ae6cf191d99f82746e07

Observation 18864c7c-39c8-4b6e-b83f-de7d2d8f9786 · outbound

This paper cites Exploring fine-grained image-text alignment for referring remote sensing image segmentation,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Exploring fine-grained image-text alignment for referring remote sensing image segmentation,

Reference 67

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:1bedd67ef780eac9c2c554cc40cf9f5593234d83d322d4428d5bb6d5113c5d2d

Observation f7425539-de8e-411e-a3a7-b720087cdaf2 · outbound

This paper cites Gsva: Generalized segmentation via multimodal large language models,.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation Gsva: Generalized segmentation via multimodal large language models,

Reference 68

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:90948df1876e4ad8f009f7c73633a1b5086199db9daf1dfe0a45199bad28d98f

Observation 00e97dd3-bf1d-42ef-bc06-20a269f2d50b · outbound

This paper cites UniGeoSeg: Towards Unified Open-World Segmentation for Geospatial Scenes.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation UniGeoSeg: Towards Unified Open-World Segmentation for Geospatial Scenes

Reference 69

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verified exact
local_arxiv, observed 2026-07-01T20:46:14.210868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:7b957ca458e51e10f116ec3bd456f42d2b5db5e02bf50a2676275a13e7062ac6

Observation a9297750-c2d6-4705-ab34-a7e7eaea5a07 · outbound

This paper cites SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model.

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model

Reference 70

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verified exact
arxiv_id, observed 2026-07-01T20:46:14.218945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-28T17:40:16.265708Z digest=sha256:053e0db5aa7b5a270f0a36c202672e62e92256e397153d2b7fea2c94b412b4cc

Pith citing papers

No inbound Pith citation observations are available.