Pith. sign in

Paper Citation Record · LEDGER

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation

As of 8 August 2026, this Paper Citation Record lists 88 of 88 outbound references and 1 inbound Pith citation observation for arXiv:2506.21233.

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

pith.paper-citation-record.v1
2506.21233 v2

Coverage vector

measured 88 of 88 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:36:50.080336Z

measured 89 of 89 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T02:20:34.568987Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T02:21:16.444115Z

Reference resolution

88 of 88 outbound references displayed

  • verified exact3
  • verified fuzzy55
  • unresolved29
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cf7ffdbe-619a-4043-8f38-01740027583d · outbound

This paper cites GPT-4 Technical Report.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation GPT-4 Technical Report

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:41.066792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:41.066792Z digest=sha256:67ac6a38fd942da5729cad4929ae597497dd1c040c25df40efb5aa45a4d107bc

Observation cd914686-f234-451d-9949-7d09c783182c · outbound

This paper cites Flamingo: a visual language model for few-shot learning.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Flamingo: a visual language model for few-shot learning

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:41.205604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:41.205604Z digest=sha256:916b5563aec2d7a5bf0394d9fc3b03b44f97e4ffe551f6376c6a4c2db8856e93

Observation 74c5eecd-f12d-4c99-98b5-ff0aba3e3442 · outbound

This paper cites OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:41.378991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:41.378991Z digest=sha256:676ff181e0634cc45d269f99732bea38b5e408d8625f43f6e3ca0c2356820ef5

Observation 0baa2d50-c5a6-41f9-952a-5795148417ec · outbound

This paper cites Qwen2.5-VL Technical Report.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Qwen2.5-VL Technical Report

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:41.542927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:41.542927Z digest=sha256:a24e617b503d70dc896a40ff8f73f048e9ad65b818f3acc25b950ce94fcee58c

Observation 46710b7c-4fe9-49d9-82b9-dba06738be3b · outbound

This paper cites Fossil: Free open-vocabulary semantic seg- mentation through synthetic references retrieval.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Fossil: Free open-vocabulary semantic seg- mentation through synthetic references retrieval

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:41.772590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:41.772590Z digest=sha256:eff656e9b4e77ccee236e68bf3f632af13ac00717a6eb739ae216908a9b66054

Observation 333a0029-aa3a-4a3a-88b9-80e6799c5484 · outbound

This paper cites Training-free open- vocabulary segmentation with offline diffusion-augmented prototype generation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Training-free open- vocabulary segmentation with offline diffusion-augmented prototype generation

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:41.884696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:41.884696Z digest=sha256:18e42c6ffeca6f691e3189c8bf89b886081947ed9a69db7d28bdcf88a7002ef3

Observation d76d690d-d53b-4205-a2e2-7e76aedd0ed8 · outbound

This paper cites Grounding everything: Emerging localiza- tion properties in vision-language transformers.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Grounding everything: Emerging localiza- tion properties in vision-language transformers

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:42.039022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:42.039022Z digest=sha256:d1315b2aa09bed7e94dd13ff9ae68e29af1df3826c70f485e68d5e1e42ade538

Observation 9a8c96ff-c8a7-4241-b597-68eba597dd03 · outbound

This paper cites Coco- stuff: Thing and stuff classes in context.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Coco- stuff: Thing and stuff classes in context

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:42.213969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:42.213969Z digest=sha256:b43475bc96c3dd1ec2286eb39513394b885c7e7dfd32d3ac0cc780cdae207d90

Observation 94387481-f722-4ff7-b6d5-4a4d5bacff81 · outbound

This paper cites Less is More: Removing Text-regions Improves CLIP Training Efficiency and Robustness.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Less is More: Removing Text-regions Improves CLIP Training Efficiency and Robustness

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:36:50.840513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:42.353046Z digest=sha256:c43b32c757c46978ce3205730e4105f9e9d0850649f86879e76d8b62eb86a8ee

Observation ca4bd275-f430-4cc3-976a-6f1df19623e8 · outbound

This paper cites Emerg- ing properties in self-supervised vision transformers.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Emerg- ing properties in self-supervised vision transformers

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:42.467394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:42.467394Z digest=sha256:89322226801ed8069e1c659309318b32a3de7183e9521947b42143943fa45e23

Observation 11b8a85c-faab-4680-9636-0f94aa33aa3f · outbound

This paper cites Learn- ing to generate text-grounded mask for open-world semantic segmentation from only image-text pairs.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Learn- ing to generate text-grounded mask for open-world semantic segmentation from only image-text pairs

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:42.530193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:42.530193Z digest=sha256:c0c12f428f11d7502a25844cddee752774e1e6a003a98258bd09a954bcee0ea2

Observation 67565dd0-a3ce-4640-8fa7-5b9562b3ecc1 · outbound

This paper cites Exploring open-vocabulary semantic segmentation from clip vision encoder distillation only.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Exploring open-vocabulary semantic segmentation from clip vision encoder distillation only

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:42.592388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:42.592388Z digest=sha256:2b43314f5aed74c5ad5f1263eeb99f86e395c720833b68f85677b5df1c4fda23

Observation adb1df3d-4eeb-44cc-af5b-64b414e4d944 · outbound

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

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Cat- seg: Cost aggregation for open-vocabulary semantic seg- mentation

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:37:01.189272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:42.654833Z digest=sha256:a09b638812fdf5a6a7d3a34b3f5a66bc08ddff44c244c27c50e6654b84ff39d8

Observation f7b5927d-492a-4cb0-93ea-2e1a17daf067 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation The cityscapes dataset for semantic urban scene understanding

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:42.720357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:42.720357Z digest=sha256:f7e74f7f4ed91d0c40cb55bce6db1a434249530f63e7082e7a4713f71b3632e4

Observation 36ef914b-a060-49d1-a8ec-59918348b329 · outbound

This paper cites A Reliable Framework for Human-in-the-Loop Anomaly Detection in Time Series.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation A Reliable Framework for Human-in-the-Loop Anomaly Detection in Time Series

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:36:50.628452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:42.807218Z digest=sha256:7ea58002d8d728620f1aa7ddf3de7e74bd2535378ea0416562851fd88d447f68

Observation 2cd16033-0233-4c96-a8bf-3ba19040934a · outbound

This paper cites De- coupling zero-shot semantic segmentation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation De- coupling zero-shot semantic segmentation

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:37:01.060369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:42.894928Z digest=sha256:8d4c0fe887e0b067da561a1a37d4a5ed91cd1f95edbda241ab955bb55acc5531

Observation 6c908253-b44e-4cbb-ab13-92d2447b06f6 · outbound

This paper cites The pascal visual object classes (voc) challenge.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation The pascal visual object classes (voc) challenge

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:42.984185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:42.984185Z digest=sha256:569bb3037a72e3c093a4f8fee692b19d9a3dc0997c1cace221ab7c252ce3b45b

Observation 3892d368-a669-48c5-8cf8-0a505b637656 · outbound

This paper cites Scaling laws of synthetic images for model training.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Scaling laws of synthetic images for model training

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:37:00.928416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:43.072377Z digest=sha256:6ca06dd183dbbf0466dfead01e8349f00bd40f2382c7ffe28f58cf928b2cc276

Observation 311b996a-43aa-43ef-a8a4-b2df7c035b97 · outbound

This paper cites Data filtering networks.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Data filtering networks

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:43.164983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:43.164983Z digest=sha256:d181d2b34906f3566920b25ea75e4441407f2fd8cae29af1e45ae143c93fd016

Observation 954082e9-66ad-49e9-b105-1853337e8dfb · outbound

This paper cites Efficient graph-based image segmentation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Efficient graph-based image segmentation

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:37:00.809896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:43.252714Z digest=sha256:2a06524e7d235408ac18dfeef98cfc26b680f41c3fc9aaf85ea06608dcd20205

Observation d803ab9f-f081-4f38-9ce5-14389720d6f7 · outbound

This paper cites Dat- acomp: In search of the next generation of multimodal datasets.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Dat- acomp: In search of the next generation of multimodal datasets

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:37:00.656979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:43.328155Z digest=sha256:a322288c1646a0b5ee01bac6029cd28ecf45e7bf467aa11bf32e8b5908066da2

Observation 4ed156c9-1ccd-4c66-85a5-d6259b2ed1a4 · outbound

This paper cites Scal- ing open-vocabulary image segmentation with image-level labels.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Scal- ing open-vocabulary image segmentation with image-level labels

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:37:00.515245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:43.405581Z digest=sha256:dc944e03946588732ae3f02ff66a72cd96a85586471741e2d0b4053e8ca4d96b

Observation b4d3db01-e840-4138-8b42-31e5b166fbfd · outbound

This paper cites kNN-CLIP: Retrieval enables training-free segmentation on continually expanding large vocabularies.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation kNN-CLIP: Retrieval enables training-free segmentation on continually expanding large vocabularies

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:37:00.375826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:43.488587Z digest=sha256:55fe32d57dd58276dbab914a1c3a5f684009bd0f43e9591192a7d90d4f80de49

Observation 52935343-e4da-4be0-84d9-3be0fb9dea9c · outbound

This paper cites Robustifying token attention for vision transformers.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Robustifying token attention for vision transformers

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:37:00.241465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:43.577378Z digest=sha256:504745f3e5fe124399a10d961c285532accc91d476e2201f37f1020e0ca6c253

Observation eb7229ce-55a5-423c-acd2-5a7a34c4a8ca · outbound

This paper cites Pay Attention to Your Neighbours: Training-Free Open-Vocabulary Semantic Segmentation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Pay Attention to Your Neighbours: Training-Free Open-Vocabulary Semantic Segmentation

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:43.675722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:43.675722Z digest=sha256:8a538b75497cda3202dcde1b04fd15967dc0777bd99eae501798644a96b0f169

Observation 9a0960c0-ee4f-45ec-9e1f-9e051843e8e3 · outbound

This paper cites Scaling up visual and vision-language representa- tion learning with noisy text supervision.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Scaling up visual and vision-language representa- tion learning with noisy text supervision

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:43.732948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:43.732948Z digest=sha256:b6bc7d9df65ca64b0b47ca6c8ada14edb7287f262e75af1c8527f24fb8b5be46

Observation 8a30cfe1-fe1a-4f29-a0aa-658120423536 · outbound

This paper cites Diffusion models for open-vocabulary segmen- tation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Diffusion models for open-vocabulary segmen- tation

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:37:00.075626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:43.846052Z digest=sha256:7285b9db527142554a18f6223da2e02c9e8b70eacb8639602563c2870baafcfb

Observation f8a112ce-fa41-4054-8fa9-ca0fdae66fbe · outbound

This paper cites Segment any- thing.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Segment any- thing

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:59.927219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:43.914741Z digest=sha256:9c39daa9b5cf00a0f6965dc288a3f63cda53169bb9d0bd18de1b5baf5d097666

Observation 3b4bf006-a2cb-4476-9dc6-33e3c00841fa · outbound

This paper cites Efficient inference in fully connected crfs with gaussian edge potentials.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Efficient inference in fully connected crfs with gaussian edge potentials

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:59.783055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:44.018955Z digest=sha256:9e20c848ff69d1bccc3878228131e191c5f77223b605f1a29daa3ceb40f14ce7

Observation 81b4d717-c583-40c0-92f1-222e9f679150 · outbound

This paper cites LISA: Reasoning segmentation via large language model.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation LISA: Reasoning segmentation via large language model

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:59.634942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:44.138088Z digest=sha256:40baacf05a6ba9100785cbe531e038e5562a18ff89eba5ee149c18905120649c

Observation dfe96d18-2965-425a-adf8-a6fc94efafe6 · outbound

This paper cites Veclip: Improving clip training via visual-enriched captions.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Veclip: Improving clip training via visual-enriched captions

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:59.488442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:44.250058Z digest=sha256:2975d62a825739c199c289ea6349b7275c3a402c6d0b4b84bdf50c5e7a0fbb10

Observation 4c8af45d-efa0-401f-93b7-9205e54e89c1 · outbound

This paper cites Proxyclip: Proxy at- tention improves clip for open-vocabulary segmentation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Proxyclip: Proxy at- tention improves clip for open-vocabulary segmentation

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:59.303421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:44.346562Z digest=sha256:015bf0b7c261634113f459a3a85881301abd44bd8609b9ec41695923b087e54f

Observation 331b762f-f057-49cd-a03f-10158e0fe608 · outbound

This paper cites TagCLIP: Improving Discrimination Ability of Open-Vocabulary Semantic Segmentation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation TagCLIP: Improving Discrimination Ability of Open-Vocabulary Semantic Segmentation

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:36:50.395037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:44.403622Z digest=sha256:0a45047488c3793097799d4ccb2533326404eb7a05e26392bf0009654b790971

Observation 180ecf60-04bc-4158-8db5-28f171710624 · outbound

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

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:59.128591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:44.480509Z digest=sha256:b422cfa93bda5fb4547743ebd69e3e43dcfaf17c43ac8115cbb4715ed25f9d47

Observation 8beec294-3051-4213-8b55-992b160f942d · outbound

This paper cites A Closer Look at the Explainability of Contrastive Language-Image Pre-training.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation A Closer Look at the Explainability of Contrastive Language-Image Pre-training

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:44.502984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:44.502984Z digest=sha256:76bca924b389f43112329064783148bf8e9bab86f0738132f7d375a9124c2e61

Observation 16dbde27-7b52-4aa6-9434-a11135ffa506 · outbound

This paper cites Open-vocabulary semantic segmentation with mask-adapted clip.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Open-vocabulary semantic segmentation with mask-adapted clip

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:58.953216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:44.507435Z digest=sha256:493debbd81671013288ff26464f5cb9a1c73f77b059c0d2c8cd00f8c56fe334a

Observation 3a351e8b-0260-4233-8d10-03e5542bf1ab · outbound

This paper cites Microsoft coco: Common objects in context.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Microsoft coco: Common objects in context

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:58.792576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:44.585617Z digest=sha256:8a03015fcace63ae9cd279d9b39ee4524ec59911ac7aa62dff7652f6df79299c

Observation fba273c8-4571-4c9f-ba49-e2c19b85bc7f · outbound

This paper cites Visual instruction tuning.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Visual instruction tuning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:58.656534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:44.721539Z digest=sha256:575e0212175d5c05f319d4997cd520718493aa980ec6a5a8097610218a88cb8a

Observation 5125b102-0d7b-419c-8686-4989c1d9110f · outbound

This paper cites Segclip: Patch aggregation with learnable centers for open-vocabulary semantic segmentation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Segclip: Patch aggregation with learnable centers for open-vocabulary semantic segmentation

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:58.521702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:44.901957Z digest=sha256:d565845dca8107211f18dd67ee00f265cc0d671fd324b0799bd90c5ad378c69a

Observation 3b06323d-273a-437f-9e1a-03618052a566 · outbound

This paper cites Emergent open-vocabulary semantic segmenta- tion from off-the-shelf vision-language models.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Emergent open-vocabulary semantic segmenta- tion from off-the-shelf vision-language models

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:58.342445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:45.083381Z digest=sha256:c5ad68edb59b5aeee8b8411b447e9eaa4deaabbd1ab7b694d6efe0cd6102e2f4

Observation 6002662a-966c-4168-9b96-2978718d2b6e · outbound

This paper cites Sieve: Multimodal dataset pruning using image captioning models.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Sieve: Multimodal dataset pruning using image captioning models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:45.286587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:45.286587Z digest=sha256:e2011db17186e414a93127a7fc9d103cca9cae465c068f0bb6123669770e6f7b

Observation c9af95e9-08f0-48e3-9e2e-054a974cf749 · outbound

This paper cites Towards interactive 3d surgical scene reconstruction: An incremental training and monitoring framework.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Towards interactive 3d surgical scene reconstruction: An incremental training and monitoring framework

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:58.156005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:45.463478Z digest=sha256:16ae9a010a77ae580f054919887caebecbc6e871b3f760106f20c04791b3b364

Observation 8a6d29d4-e7ac-489b-9ecb-07effd638e79 · outbound

This paper cites The role of context for object detection and semantic segmentation in the wild.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation The role of context for object detection and semantic segmentation in the wild

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:57.944191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:45.669187Z digest=sha256:495a9256e29f4750f1a888ec30f406c653b33901ef3eeaad6ec5b02308e3878c

Observation 7bd015a8-43b4-4111-8c61-7c5e69ec2db0 · outbound

This paper cites Open vocabulary semantic segmentation with patch aligned con- trastive learning.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Open vocabulary semantic segmentation with patch aligned con- trastive learning

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:45.814609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:45.814609Z digest=sha256:938bc9790b7f222fc8ab820575d781ad09f8f25f6a59e5433af5190891e77966

Observation 1244d5a0-8689-405c-8415-f8912b86acd7 · outbound

This paper cites Dataset diffusion: Diffusion-based synthetic data generation for pixel-level semantic segmentation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Dataset diffusion: Diffusion-based synthetic data generation for pixel-level semantic segmentation

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:57.735661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:45.894499Z digest=sha256:4922aa25415a923b3b0cc73110aac8e61ae010ecec947d9b29944fab449d9186

Observation 66d335a9-8cfd-46e8-94e4-e5ba3e893868 · outbound

This paper cites Improving multimodal datasets with image captioning.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Improving multimodal datasets with image captioning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:57.525846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:45.934377Z digest=sha256:c74447b5f8290678d5ef99dd1b1648324bcdb939f40471fe479af68a1299cd96

Observation 9e61ecd3-404d-4af5-83fe-7fb003037fd8 · outbound

This paper cites an unresolved cited work.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Unresolved cited work

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:45.975908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:45.975908Z digest=sha256:7e3680eea1001f77099425801fc7a40ca204b3c64562ade997da897408074504

Observation 93041323-ebb8-40c9-bbec-e1bfeb8885e8 · outbound

This paper cites Kosmos-2: Grounding Multimodal Large Language Models to the World.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:46.053309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:46.053309Z digest=sha256:5541a807664567c4bab3f3dafa5737ac704db33889cf64cafd3cadabc4708964

Observation abd72d5f-9ef4-41b9-a29a-cad84a9053a0 · outbound

This paper cites and et al.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation and et al

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:57.281898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:46.167118Z digest=sha256:66dbe2156367944a3c99334942ba1b021d73c1db92833b71aa4d1c85ebc92d29

Observation 603d34ca-b464-4b79-affb-fcec8c418b06 · outbound

This paper cites Filtering, distil- lation, and hard negatives for vision-language pre-training.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Filtering, distil- lation, and hard negatives for vision-language pre-training

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:57.070655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:46.264276Z digest=sha256:a991e14d79b9a331850643958de06788d92fc14785607a98f190614c12909b91

Observation c5de6fb1-fd74-4917-a404-c71029f69adb · outbound

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

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Learning transferable visual models from natural language supervi- sion

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:46.359825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:46.359825Z digest=sha256:2a1727cb808bb74f5390f3e93ac272cd0981ee8a1386320ec8621bfef4379dd8

Observation 54d4afd6-97ee-4556-b348-9bb92f1b3abe · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation SAM 2: Segment Anything in Images and Videos

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:46.497678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:46.497678Z digest=sha256:f58e9b8f14e617592434f095e047e565e7895e84695cc7bba6d35b41f66425f9

Observation bcdc1e21-0cc8-4230-8e0d-5325b9b5e63a · outbound

This paper cites Zero- guidance segmentation using zero segment labels.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Zero- guidance segmentation using zero segment labels

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:56.869198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:46.587155Z digest=sha256:9c9a0cae508d6fe3b43f92be3221cabdf6aba28cdd913724311564d676c2e715

Observation 37ebec69-623b-43d2-8dd3-50d2be1383ee · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation High-resolution image synthesis with latent diffusion models

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:46.686677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:46.686677Z digest=sha256:6d4eb8b5c65cf0f0fc953103b561f4b86e5a0be65dbb78d2b770a7b57ae8ec97

Observation e32bfd97-c36c-496f-ad7a-5c05f34c0968 · outbound

This paper cites LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:46.806895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:46.806895Z digest=sha256:17a066608421cbc803c081e2a013d2f006db4ea6a68f07b4a7aa453f76d19c90

Observation 700574c9-37fb-49ba-8225-ed76d2ca434e · outbound

This paper cites LAION-5b: An open large-scale dataset for train- ing next generation image-text models.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation LAION-5b: An open large-scale dataset for train- ing next generation image-text models

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:56.707483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:46.923658Z digest=sha256:513dfc9325ba238ba692d90d9afd2caa493a5126f72872a8a9d8b4b5014aa47d

Observation 1d84a963-fb5e-4ca1-9e78-8e53df002a54 · outbound

This paper cites Explore the Potential of CLIP for Training-Free Open Vocabulary Semantic Segmentation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Explore the Potential of CLIP for Training-Free Open Vocabulary Semantic Segmentation

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:47.017637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:47.017637Z digest=sha256:590d8b09f41a2560dbb7c6eb1bfc5c86ca00014b341535014f821e71ee90bad9

Observation c4f2a0fe-8c59-4474-ba13-cc2f43d14b0d · outbound

This paper cites Reco: Re- trieve and co-segment for zero-shot transfer.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Reco: Re- trieve and co-segment for zero-shot transfer

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:56.491432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:47.128137Z digest=sha256:6f087b4c1e278910fbe07fcc646e1e3743084358128cc5bdcd47298141c10f94

Observation e0a010d1-d229-44bd-8efa-cee0425f0b95 · outbound

This paper cites Is synthetic data all we need? benchmarking the robustness of models trained with synthetic images.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Is synthetic data all we need? benchmarking the robustness of models trained with synthetic images

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:56.304317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:47.268929Z digest=sha256:c5ef00524917a22926460f1f5a85f589b7dce0b925c8569a862493bbaef74cfa

Observation 83d77fd3-a0b2-479b-8ae2-36eb0da908ac · outbound

This paper cites Clip as rnn: Segment countless visual concepts without training endeavor.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Clip as rnn: Segment countless visual concepts without training endeavor

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:56.055550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:47.348154Z digest=sha256:6401006b793cb5f4555fba51ea1555454764b3d247eac0899a738abf266c425a

Observation 02be3e0b-e9bd-4d43-8b88-6728f84301b6 · outbound

This paper cites Attention is all you need.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Attention is all you need

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:47.455196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:47.455196Z digest=sha256:11c87ce85bfa64e6cfc2e168959f41ca8be71bae0613257747e3e9b048ce9aeb

Observation 5f87a123-372f-44e3-9c41-ef8a0c82ad77 · outbound

This paper cites Sclip: Rethink- ing self-attention for dense vision-language inference.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Sclip: Rethink- ing self-attention for dense vision-language inference

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:55.766792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:47.584694Z digest=sha256:2f22565ddb0a3585c1ab36e6746bdd2b3c127752ce85c7ec34dba9808517b70e

Observation 41427905-8526-4e77-8d91-442d53537a6f · outbound

This paper cites Sam-clip: Merging vision foundation models to- wards semantic and spatial understanding.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Sam-clip: Merging vision foundation models to- wards semantic and spatial understanding

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:55.549572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:47.680065Z digest=sha256:69abfaed38dbfa62ec609b62230deeef3d04a70b24c72cc0cb6172a0f5f36b7f

Observation 309c8087-76f6-409b-b9a7-1eeabbd38cb1 · outbound

This paper cites Diffusion Model is Secretly a Training-free Open Vocabulary Semantic Segmenter.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Diffusion Model is Secretly a Training-free Open Vocabulary Semantic Segmenter

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:47.810899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:47.810899Z digest=sha256:689808c0a8a2008c6257b3d84dd92969de7e3434d16998d61bf7454e992fa7ce

Observation f5ff4a74-34cd-4f60-822d-7ff79976c443 · outbound

This paper cites Use: Universal segment embeddings for open-vocabulary image segmentation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Use: Universal segment embeddings for open-vocabulary image segmentation

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:55.340583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:47.971184Z digest=sha256:b58bdd4f44260aef9b0a32f2c41072e8176b5d6e3e6584bf8ebcb8d671253aac

Observation a4876ccb-0095-4a07-9b26-ce67a5934714 · outbound

This paper cites Image-to-image matching via foundation models: A new perspective for open-vocabulary semantic segmentation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Image-to-image matching via foundation models: A new perspective for open-vocabulary semantic segmentation

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:55.129780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:48.097496Z digest=sha256:5d715224bc2743745202330f43d5a3613c99b8c262d1a3204c660397d4fc92de

Observation 7c51c9f8-092b-4b3f-8468-bb066e5cb98f · outbound

This paper cites Probabilistic pixel-adaptive refinement networks.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Probabilistic pixel-adaptive refinement networks

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:54.927224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:48.256102Z digest=sha256:ac6321cfb0a4461e040794872dbfde16d9770af5b67e880c3f1155eba2336c19

Observation 8eed80cd-4bf3-467a-b25c-edc5a6ed56c9 · outbound

This paper cites Image-text co- decomposition for text-supervised semantic segmentation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Image-text co- decomposition for text-supervised semantic segmentation

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:54.827136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:48.365938Z digest=sha256:fa7b9f8ee0da820153fb87f5df7873a9cfc854192899e0020eb6c884beebb70c

Observation a08aac2d-72b3-4835-91a3-5794fd848797 · outbound

This paper cites Clip-diy: Clip dense infer- ence yields open-vocabulary semantic segmentation for-free.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Clip-diy: Clip dense infer- ence yields open-vocabulary semantic segmentation for-free

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:54.664824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:48.434137Z digest=sha256:0210609a55e1eefdeffa39959b48ceaa4da6adfd4736befa8d7c39d7c30fd6af

Observation b55d44bf-32a9-4afd-8a9c-0882d73331d5 · outbound

This paper cites Florence-2: Advancing a unified representation for a variety of vision tasks.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Florence-2: Advancing a unified representation for a variety of vision tasks

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:54.458882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:48.528678Z digest=sha256:d8fe670ea1abad33836e5e86640ff235c483db44e1395d39194cc20b04b8dc99

Observation ab6c9639-e480-4eba-acce-1449f601e5fc · outbound

This paper cites Rewrite caption semantics: Bridging seman- tic gaps for language-supervised semantic segmentation.Ad- vances in Neural Information Processing Systems, 36, 2024.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Rewrite caption semantics: Bridging seman- tic gaps for language-supervised semantic segmentation.Ad- vances in Neural Information Processing Systems, 36, 2024

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:54.145551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:48.616081Z digest=sha256:330738f19704a0b5bfd390b8bcce9410f2535d29f744c79ee0f9cacf9861feb8

Observation 4c496ad9-1609-4cde-9375-aa13bb9887fc · outbound

This paper cites Groupvit: Semantic segmentation emerges from text supervision.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Groupvit: Semantic segmentation emerges from text supervision

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:53.906607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:48.705840Z digest=sha256:639187d9ef078e4f869825839c3813be86bbb35b179179a1b4bd49af27a7b791

Observation 66b577f4-10ea-46e7-b8aa-7ebf025f3ec4 · outbound

This paper cites Learning open-vocabulary semantic segmentation models from natural language supervision.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Learning open-vocabulary semantic segmentation models from natural language supervision

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:53.753127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:48.798359Z digest=sha256:8ee0037e22937878f193fb0e909e8a0828681449833f102053ebda07eb2d6255

Observation fc8ff5d2-783f-4225-87bb-08d2cd59cd79 · outbound

This paper cites A simple baseline for open- vocabulary semantic segmentation with pre-trained vision- language model.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation A simple baseline for open- vocabulary semantic segmentation with pre-trained vision- language model

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:53.573724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:48.888577Z digest=sha256:475426194af905cdc334d3921315cf2403800f78344f2f2ab1e133db088e50a2

Observation be625883-898b-4e83-af6d-619f375df21b · outbound

This paper cites Side adapter network for open-vocabulary semantic segmentation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Side adapter network for open-vocabulary semantic segmentation

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:53.373398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:48.982197Z digest=sha256:55a5280f1116bb2b82ac37564cd0675f430df9ad9431454191ab193e207e6638

Observation ea1d4c6b-1f80-4025-be9e-86883b3755c0 · outbound

This paper cites V AC-CNN: A visual analytics system for compar- ative studies of deep convolutional neural networks.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation V AC-CNN: A visual analytics system for compar- ative studies of deep convolutional neural networks

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:53.213445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:49.041654Z digest=sha256:905b93095e53fa8513e80794151de1355342218862c5dce041b1e0e0a24d8fea

Observation 1ec1d09f-238b-4f3f-a1b0-cbdf222634b8 · outbound

This paper cites Suny: A visual interpretation framework for convolutional neural networks from a necessary and suf- ficient perspective.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Suny: A visual interpretation framework for convolutional neural networks from a necessary and suf- ficient perspective

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:53.030841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:49.112634Z digest=sha256:980b2b44072b56d52a27411982dc866cf0f271cf6de5bd7002454976b37ec12d

Observation 181d2d2a-36bf-4b86-81b6-42412eec4de8 · outbound

This paper cites SLIM: Spuriousness mitigation with minimal human annotations.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation SLIM: Spuriousness mitigation with minimal human annotations

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:52.810813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:49.188623Z digest=sha256:d956304e50244b7d3d4142dff75592324e0d887c14183063f59b47f157751269

Observation 83e490e4-ce6c-4795-8c24-9696f3cb06e4 · outbound

This paper cites AttributionScanner: A visual analytics system for model validation with metadata-free slice finding.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation AttributionScanner: A visual analytics system for model validation with metadata-free slice finding

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:52.601357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:49.284813Z digest=sha256:0765b8259b43943bcddbd01903679d2fd6bbc32958ed91485e1fd569924801f6

Observation 9e3cefe5-8395-4cb9-ae90-f0df2e3b1b36 · outbound

This paper cites VISTA: A visual analytics framework to enhance foundation model-generated data labels.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation VISTA: A visual analytics framework to enhance foundation model-generated data labels

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:52.339810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:49.373969Z digest=sha256:f2c86829a25fc8580c2cb7479ce0569d368881eff198c0095647c9395b742d6a

Observation 3c3e2c41-bf7c-44ba-beb5-881c22edc89f · outbound

This paper cites Vislix: An xai framework for val- idating vision models with slice discovery and analysis.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Vislix: An xai framework for val- idating vision models with slice discovery and analysis

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:52.130422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:49.475679Z digest=sha256:9d648693b56dd7f4d9913a7ec4dfa18ec60c1d2cb23b1ad700627ac12fa09ede

Observation d5d65c32-dd3d-42a1-86a3-778889d3e525 · outbound

This paper cites A simple framework for text- supervised semantic segmentation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation A simple framework for text- supervised semantic segmentation

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:51.956664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:49.564221Z digest=sha256:eb8b8fc2ee76c9526758eb0015d2fafd5911032b676b90eae20e56761f4dfbe8

Observation 5cba2281-be1c-4c55-9237-96172f817b4a · outbound

This paper cites CorrCLIP: Reconstructing Patch Correlations in CLIP for Open-Vocabulary Semantic Segmentation.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation CorrCLIP: Reconstructing Patch Correlations in CLIP for Open-Vocabulary Semantic Segmentation

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-06T22:36:49.685565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:49.685565Z digest=sha256:e9c95e98f4502b487b6e1d08a431c74d0f0a4a8d2d188274a28a5249dee0fb41

Observation 4fab9d7d-1604-42b9-98f8-480652ec23e8 · outbound

This paper cites Tip- adapter: Training-free adaption of clip for few-shot classi- fication.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Tip- adapter: Training-free adaption of clip for few-shot classi- fication

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:51.720728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:49.753856Z digest=sha256:7abdf3dcda0981bec78a32df253f7d8e0d26b497007c83c95ca433c91daa1494

Observation 6500ca74-6770-42a8-b284-04cce307a393 · outbound

This paper cites Labelvizier: Interactive validation and relabeling for technical text annotations.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Labelvizier: Interactive validation and relabeling for technical text annotations

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:51.537913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:49.837476Z digest=sha256:e203964e0c9fef87cfdc0efe1ec48167aa29608eae1927d6279be00102e5125d

Observation cb7908d7-b580-4ca3-8f1a-43ecba8a208a · outbound

This paper cites Semantic under- standing of scenes through the ade20k dataset.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Semantic under- standing of scenes through the ade20k dataset

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:51.293736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:49.933174Z digest=sha256:3a189ba797d53a7eb6fd00cc6953087ffcaacc32c38ea1e515be21ff9ae76d2c

Observation 3d7417e8-12e5-42aa-8179-965fb5ba9ca4 · outbound

This paper cites Extract free dense labels from clip.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation Extract free dense labels from clip

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:36:51.084290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T22:36:49.990789Z digest=sha256:0511947756db488a286651808356245cf106aef8daef11dd25fcb457e466b8ae

Observation 5afc66ba-1db5-4322-8cac-109c8ec26260 · outbound

This paper cites ChatGPT Asks, BLIP-2 Answers: Automatic Questioning Towards Enriched Visual Descriptions.

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation ChatGPT Asks, BLIP-2 Answers: Automatic Questioning Towards Enriched Visual Descriptions

Reference 88

Resolution
malformed identifier
no resolver link, observed 2026-08-06T22:36:50.080336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:36:50.080336Z digest=sha256:bf026cc18a1da0fe3bdcf959d9d26aa6b8e4e4929bacf4f7a8b9fb075b5fe753

Pith citing papers

Observation 3514aca8-2c36-42e1-b4ba-e32671ab8a27 · inbound

Investigating Anisotropy in Visual Grounding under Controlled Counterfactual Perturbations cites this paper.

Investigating Anisotropy in Visual Grounding under Controlled Counterfactual Perturbations ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-12T02:21:16.446524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T02:20:34.568987Z digest=sha256:f4cf25e0ae0450ee05b841ab5772be0dcb5c3a73bf6ef37922f1c61ec025bc45