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Paper Citation Record · LEDGER

SigLIP-HD by Fine-to-Coarse Supervision

As of 12 August 2026, this Paper Citation Record lists 100 of 106 outbound references and 0 inbound Pith citation observations for arXiv:2607.09488.

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

pith.paper-citation-record.v1
2607.09488 v1

Coverage vector

measured 100 of 106 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-13T02:39:58.984385Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

100 of 106 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved100
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c2ff76d3-a618-471a-b010-f61af8b5a6a1 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:9878e4bbb76dff12106a57393550cc4ef8385445762036fddd237345f4c7d805

Observation e8350301-f309-438a-8631-f714575c47f1 · outbound

This paper cites NeurIPS , year=.

SigLIP-HD by Fine-to-Coarse Supervision NeurIPS , year=

Reference 2

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:738f65db1bb5df829a6915050b20f667b8aec110f1f4d1a575f300a943ab3667

Observation 298b8cf1-2e43-4f26-b750-0899c80498cb · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 3

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:8661d895d88f132e6a1047c981e3a6075d0d20c557321ad401376e6cb64d8ecf

Observation 30be5e39-2a5c-4fbf-9837-373c3a8f9e57 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 4

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:e4022e64c51b2a63e3b361537b060d8f66dcb12173131acd3945f826cab7c8d2

Observation c7dc6649-2310-428c-91e7-22f68d343a2d · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 5

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:16b7821a9e44fa68e975dc5e2aa5608a7e3790ce45b4e7c585e8cec1234f41b7

Observation 33c1f97d-d96e-4d9c-a877-81e49770670e · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 6

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:24cc091b82ef5af648dbdbbd35283fe8059f6e9b81dd7cb03ff47c2c496d23d0

Observation 587d93ae-4dec-4139-96a8-17069e69a200 · outbound

This paper cites ICML , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICML , year=

Reference 7

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no resolver link, observed 2026-07-13T02:39:58.984385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:cde836e6f5599e763685ce4ecb0bfe42f88c3b1d2f5706718a102e2dcc02ccd9

Observation b7b7a4bc-e11e-4741-9d33-f592ac5dd104 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 8

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:3e0e1896e9efb36a24f1e33a667b45082772a6ccc8833227c1f21461f0ee0078

Observation 324475ff-9d23-4a5b-8f62-e48d39592af4 · outbound

This paper cites ICML , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICML , year=

Reference 9

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:1bc612d0c053386e1e231f7965a636ed50a91f8efea42683acbcd4d93fe2f367

Observation 7ea4f37e-6e99-4916-9b82-2acbd9377049 · outbound

This paper cites ICML , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICML , year=

Reference 10

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:c2e5efff549a9ba5d1aa0c8cd413bc2fa09603c1f2bc98971783c5fa16bc080d

Observation cda22473-c076-4008-ad76-f8e785bf749d · outbound

This paper cites ICCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICCV , year=

Reference 11

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no resolver link, observed 2026-07-13T02:39:58.984385Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:a226fa62c97b29c669e826be696b3f6d97f330ff8fe439f1f781d9ede66276a9

Observation 432535c3-b763-4a27-886a-8835cf613cc6 · outbound

This paper cites ICLR , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICLR , year=

Reference 12

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:3a7bcec815a866e0720e2da2333434a884830466a7d4091e3ecd48505caf6f96

Observation 228e63aa-f2da-427c-abc8-09dbed272eb3 · outbound

This paper cites SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.

SigLIP-HD by Fine-to-Coarse Supervision SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Reference 13

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:237646d8848983d90fba410c4d4b4b6668cc264af152686190a431232551e61f

Observation 191081bb-c536-4969-a734-b3cb55b5deb7 · outbound

This paper cites ICCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICCV , year=

Reference 14

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no resolver link, observed 2026-07-13T02:39:58.984385Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:472e309c6f04879ed8278d9d5771086d9bce06a1bd792303f1a245e685193f04

Observation 6cbdbbbc-0906-47c3-bcbf-fb9b3064c0b7 · outbound

This paper cites NeurIPS , year=.

SigLIP-HD by Fine-to-Coarse Supervision NeurIPS , year=

Reference 15

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no resolver link, observed 2026-07-13T02:39:58.984385Z

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:af03c0f86779a49441263b5c9f13849fb4084cab6923978d5a8d7b65d6d7c6ee

Observation fb19beb0-d308-493d-82b8-3286cec8cbb6 · outbound

This paper cites TMLR , year=.

SigLIP-HD by Fine-to-Coarse Supervision TMLR , year=

Reference 16

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:56a95537015b3293860dae017f8cc202babb61738fb0ea613a9569f2e9fe3cfd

Observation fa93e949-ff2c-476a-935c-0136f5160d4a · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 17

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:343c2684a63223eae838ce6742933c075c38d285716e0c6a0eeb665ba81c3147

Observation 82aeb73a-db72-4307-b4af-dcb9bfba1857 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 18

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no resolver link, observed 2026-07-13T02:39:58.984385Z

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:43f8c69e8fd6db4f47815cc6535dccf2c276b1160053c7ed566477ccd14eb604

Observation ca74a847-7645-4e72-a918-66adb7f2cded · outbound

This paper cites ECCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ECCV , year=

Reference 19

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:9943cbc66729968aad4a6b43a5f0264f869c430d3a6799993e9558467a51c9fe

Observation d6565b8d-97f2-400a-9360-30993969c23d · outbound

This paper cites GPT-4 Technical Report.

SigLIP-HD by Fine-to-Coarse Supervision GPT-4 Technical Report

Reference 20

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:8d468b823997aa14b61aa44b8cdf75b4be5845f61fae630a9393808b2333ca47

Observation b3650fbe-b975-4571-8039-1a4f68e88c55 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

SigLIP-HD by Fine-to-Coarse Supervision LLaMA: Open and Efficient Foundation Language Models

Reference 21

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:583473a0390d54a04f138a8bf2d9d24895c0c2d4081635cfe80ae8b398829e41

Observation 6310f63e-f7cc-4ac0-a936-6f8abd804173 · outbound

This paper cites Qwen Technical Report.

SigLIP-HD by Fine-to-Coarse Supervision Qwen Technical Report

Reference 22

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no resolver link, observed 2026-07-13T02:39:58.984385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:80c1558ee832d227dbc412f432e593d913f42a088a0c2c1d44470bb0517f1bbd

Observation b5319af0-d987-4d13-81bb-447ef8cdf43f · outbound

This paper cites NeurIPS , year=.

SigLIP-HD by Fine-to-Coarse Supervision NeurIPS , year=

Reference 23

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no resolver link, observed 2026-07-13T02:39:58.984385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:648e10b01b75bdf8bf6f872ba8eee7770a0ef56d96a1464f9b1e384fa15ed492

Observation 43172df0-586e-4ce9-a205-216449973b0a · outbound

This paper cites ICLR , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICLR , year=

Reference 24

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no resolver link, observed 2026-07-13T02:39:58.984385Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:a90804408c6a8a8c312d5fb3254a1497ad20ae5fa153f36dddda66c6aff23169

Observation 2fc3b47c-dde6-49c7-9419-4cfab900b85a · outbound

This paper cites ECCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ECCV , year=

Reference 25

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no resolver link, observed 2026-07-13T02:39:58.984385Z

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:f3787bb06edb419b83cf268fd4b55154a94237135f0f14c7bbf4a5d9782b637e

Observation 2894fe9d-48c0-488e-a751-bb7a34586f06 · outbound

This paper cites ECCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ECCV , year=

Reference 26

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no resolver link, observed 2026-07-13T02:39:58.984385Z

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:5be0d931563e29bb0cec30d75f8a55d99e6b6f41bc51b02adbb3cfb0479f127d

Observation 097a42a8-c4f4-4abb-9e02-50146d69559b · outbound

This paper cites NeurIPS , year=.

SigLIP-HD by Fine-to-Coarse Supervision NeurIPS , year=

Reference 27

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no resolver link, observed 2026-07-13T02:39:58.984385Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:5181b735cb7419a2fff81b32c63ce1b4ad2b6be6e4735cca3b8d762d9eb87293

Observation b4b183c5-b769-47e6-90ea-8ea95cb93247 · outbound

This paper cites ICLR , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICLR , year=

Reference 28

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no resolver link, observed 2026-07-13T02:39:58.984385Z

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:99154063136ef2f0a2550109397238a858bfa03aec58807c1a2a182c5dbfbd03

Observation 6571220d-33ab-416a-b543-5570d6fde77f · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 29

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no resolver link, observed 2026-07-13T02:39:58.984385Z

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:868d354231500c3ab5477e15a754e1f185de9b34b69f774060e3ceb74a009ec0

Observation 3b4e134f-6caf-4711-95bd-abd99deab116 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 30

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no resolver link, observed 2026-07-13T02:39:58.984385Z

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:512342cb16a6eac0d033feaffc945ba39be6bf22c9fe99c2d9f66da1a02dfe8f

Observation 99882e5e-7cf4-4a99-81a7-816b5216d33e · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 31

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unresolved
no resolver link, observed 2026-07-13T02:39:58.984385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:befa0ca102319f1f6a3fae29b464eaa6e170b3f9bad795f9a911e5d7221b8aad

Observation 9e4dde1d-a427-494b-93bb-eeb1952d423e · outbound

This paper cites ICLR , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICLR , year=

Reference 32

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no resolver link, observed 2026-07-13T02:39:58.984385Z

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:0c99cc7c3c6c7d907c26736939fb3323a6e7ed31a271ce38f9a8764b280e57ab

Observation 70d6a3f6-3ad7-4717-bdb5-3abddc3e4ec1 · outbound

This paper cites Multimodal Autoregressive Pre-training of Large Vision Encoders.

SigLIP-HD by Fine-to-Coarse Supervision Multimodal Autoregressive Pre-training of Large Vision Encoders

Reference 33

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:cfffd09ff1e98581a661fedf07dace83e6cb72f17ddbc33f7b1a7900385f5179

Observation 6813781d-fc65-4bf4-88f0-7e0811b4c1a7 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 34

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no resolver link, observed 2026-07-13T02:39:58.984385Z

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:716ccd65e6749dc4194c3c16e32ef15d776bf31c642ed4cbd6fb6d83f2e3a51f

Observation ec7f7cdf-df4a-49c9-801e-0dfa5d771377 · outbound

This paper cites Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models.

SigLIP-HD by Fine-to-Coarse Supervision Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models

Reference 35

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:37b05655c04df066ecb24cb23b59938462ca99e2aaf0eb36664a46e6308429be

Observation 68020ef7-24b0-408e-9a4b-3c35bde992cd · outbound

This paper cites LLaVA-NeXT: Improved reasoning, OCR, and world knowledge , url=.

SigLIP-HD by Fine-to-Coarse Supervision LLaVA-NeXT: Improved reasoning, OCR, and world knowledge , url=

Reference 36

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no resolver link, observed 2026-07-13T02:39:58.984385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:8d4302da2ef1348e6e40505a2e5b94fd18b08b25aa93e939424715804856cc44

Observation 4611062d-9272-4141-8462-4d26bd961910 · outbound

This paper cites TMLR , year=.

SigLIP-HD by Fine-to-Coarse Supervision TMLR , year=

Reference 37

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no resolver link, observed 2026-07-13T02:39:58.984385Z

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:9ece45e036aa50eaf257d01002619c0d601b498cb27872c644135e5aa2f20aba

Observation ac4f6a76-a634-4087-97a1-b6e494d31442 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

SigLIP-HD by Fine-to-Coarse Supervision Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 38

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no resolver link, observed 2026-07-13T02:39:58.984385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:d5a18168a33c61070376e6da5d3f3a7df48e8fd59986061f9e916e30b8af185a

Observation 6e6e04a7-b705-4c6b-b63c-7e59d9f75354 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 39

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no resolver link, observed 2026-07-13T02:39:58.984385Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:a61fb42c7582a0c82847a7eb55b542632bf0108cf93f1f37c95b6ce1b3938a52

Observation 969c5e3d-4871-4709-a93b-d15ca3a182fd · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

SigLIP-HD by Fine-to-Coarse Supervision Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 40

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:9eb7c195890944af8e534f41df161b3cd16af6f7cfdd147dacf84f1856f4f394

Observation 7e45afed-75ea-4388-9a0a-2e8b450f1147 · outbound

This paper cites ICLR , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICLR , year=

Reference 41

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:51192fe0d3779055135eaf9670750cdabbc365a8f8fa614e35d8b8a55bfa6dcb

Observation f84888a4-c621-45c0-87de-9b2a383a19ff · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 42

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:830fc7b4cbcf7b4b4c607dc7e31f8b7ade9f59a73113518623f74dc6ee09867b

Observation a485ec10-5a2b-409f-88e0-8c47ef1f3bd5 · outbound

This paper cites Qwen2.5-VL Technical Report.

SigLIP-HD by Fine-to-Coarse Supervision Qwen2.5-VL Technical Report

Reference 43

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:1d7583ec48ee4039cd1b95796660b8d687271d9dc5814738648345eab5614094

Observation 1299711e-b75f-438c-a11c-ce45a40aaaac · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

SigLIP-HD by Fine-to-Coarse Supervision Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 44

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:6a244894fe6099b39b2ee036b16b01b7b6d6896cbda1b63339b50273970b434e

Observation b6b724cf-f273-4c40-a354-98f1404e1bd2 · outbound

This paper cites DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding.

SigLIP-HD by Fine-to-Coarse Supervision DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

Reference 45

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:111dd9822ccc44ad19510e3b04ca19e867cbbfde3e46d3f9a3426684638bdfbb

Observation e4056050-ae00-42bc-ae1d-48537768f17c · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 46

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:895e35dbb8eef7347d4e62bb74fe499a281868cfbe1e8083c93dda92c849fba4

Observation 36c9ae83-9396-4f04-bb01-5f825a8fe1af · outbound

This paper cites NeurIPS , year=.

SigLIP-HD by Fine-to-Coarse Supervision NeurIPS , year=

Reference 47

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:656ad5fca533db06ef1a49ef92a3a3866dbf8caab8c598a0d50a6e3f489e49fa

Observation d66c955c-5f7b-4888-98a8-a5ddcb60213c · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

SigLIP-HD by Fine-to-Coarse Supervision Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 48

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:448654a3b0918660f62a91ad03a7ea4575cd98cbaf6c4d2880144226ff7a0990

Observation c4606f99-f651-41eb-9cfa-319db0229a62 · outbound

This paper cites Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models.

SigLIP-HD by Fine-to-Coarse Supervision Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models

Reference 49

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:ae400d91eec434627cd50c042750b96330c524ff960b6d4e70fa565250ac2039

Observation 525f04b4-accf-49e1-a4b9-6b430ce13498 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 50

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:345cd6edf4c47c9befa7791126833227b59f534de9fc900b040656130594fd11

Observation 1db9abe0-cdfa-4ad5-a8ab-109f7ee06ca4 · outbound

This paper cites ICML , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICML , year=

Reference 51

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:c72037745da10ca27576552aa66038a493343e4777631d673cc6827a5b250716

Observation e445e493-b210-4075-b0a4-cea11163b33a · outbound

This paper cites ICML , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICML , year=

Reference 52

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:cb38245d08e7adb08b5f37a6f4ecee25ff5a1d09c7b31be72658c51a7379ce59

Observation 1e34d64f-dd3b-4482-b459-193a2d796bfd · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 53

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:920165e137388f865c0f4090100b7f516921bb4c9ca666fffdfcf4361e0319a3

Observation 6b2c01d7-0782-4112-a206-0cf3b1e36760 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 54

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:ff6f33e6afbe2630418ba0aeb94e250cdb33e4a9656b0fe59b3595417b1a0b23

Observation e70dcd31-3265-4980-9c82-a0c5fb16c913 · outbound

This paper cites WACV , year=.

SigLIP-HD by Fine-to-Coarse Supervision WACV , year=

Reference 55

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:711231d584d1f0ed7a9b65aaf4b2a9dd9088a4ea3d2272682f4b1d179992590b

Observation ad94d457-d238-4c93-ab98-972dd62f87e0 · outbound

This paper cites AAAI , year=.

SigLIP-HD by Fine-to-Coarse Supervision AAAI , year=

Reference 56

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:3a78ba0f0780a28c196536633eb9e19d878032d31d7c506815f1db7de416e535

Observation 91facadc-625d-4435-bfd9-c6a0cce735fb · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 57

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:57ccd34fde745e50db099956458c4fca24c323c0755a16671c6151e80f3a807e

Observation 9877d28f-d621-4b22-b874-d8174123f715 · outbound

This paper cites ECCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ECCV , year=

Reference 58

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:4f91a47519798f6289f690374eeaf51bec89f59d3d5234289df464c45e353313

Observation b0101cb2-caa2-4c75-a317-e187f7ab98f6 · outbound

This paper cites ICLR , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICLR , year=

Reference 59

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Source-reported events for the cited work

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:f2018b8ccc334fdc6ab39a79801f27d1c6de4175b6ad10498b2ba5391962f62b

Observation 1553deff-193a-4b4c-96e9-a434b337d3d0 · outbound

This paper cites ICCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICCV , year=

Reference 60

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:660fd453f8344b83b41cc2881e6469995ca9d9dfeaf3948e5adc26f0a9ed0ab6

Observation dedfcaea-21fb-4539-83a6-a12d76d13426 · outbound

This paper cites ECCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ECCV , year=

Reference 61

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:0d101016e6b7421b5721db9310af074d30e3b8418c577c1ed9b19b6cf23e610f

Observation 3ebf510e-9316-434a-aaa7-d2bbc633790a · outbound

This paper cites ICLR , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICLR , year=

Reference 62

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:3290b0bc3644760a95f88cfaed0ecbfe4d2f1d6a8e63f24d3752162027fa772c

Observation ff51fd54-0a23-4d99-b4b1-10d00fe0095c · outbound

This paper cites LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models.

SigLIP-HD by Fine-to-Coarse Supervision LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Reference 63

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:9b770906e163c130cebf7f2521d8b68f9f092e9b1df3518a1397ca2f79300964

Observation 0b7323ef-6a3c-410b-969e-1f87112e657a · outbound

This paper cites ECCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ECCV , year=

Reference 64

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:654e030bd838c4bca891449d291a51b73eea70dd9e2fbc61ec729c4bc4c7c665

Observation 7aaa4818-df27-49f6-9ab0-544e1583f8e2 · outbound

This paper cites IJCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision IJCV , year=

Reference 65

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:d58db523234007fe9a4ab6e85a4f1ef7fd1929394f02ebee478718b21fb231b0

Observation f4f0d1ef-7892-4ce5-90c1-7d78f912089b · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 66

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:c8c4f1c161f4802ba0736bc83c2c2acf45d7c1f95f5a28a4d9344353c63c4a8a

Observation ac6b32d6-f998-461b-897d-e697dff7256e · outbound

This paper cites ICLR , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICLR , year=

Reference 67

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:9eaf4d70b06a033531cefe2873af38f99535c9352db2d2363c1ca389d4aae22d

Observation 6cdbf597-5074-4e57-b80c-7a1ca1ba56b5 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 68

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:c5d241537014e3d8ed4812ad7ba698f8c97ed893077ef097aa2ef0e4c92ac492

Observation 353ed8bd-480f-4fda-8be5-351858f22446 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 69

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:bf9cfb7a3bb6df2f97154f220fc52e230f23a81e62da21e9bb532b9ec2a42666

Observation e7dd6082-9b21-401c-af2d-769e90e242a7 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 70

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:65ee489c37754caa0303dda50a2d28895112cd003d39f98de9afaaf6d403e6ae

Observation 80244eff-2fd1-4ffc-9300-0f581ed3b212 · outbound

This paper cites ICCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICCV , year=

Reference 71

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:5eecfb90029f1d4395dde956293a3dfd8f9732af2559525c70f1bfab6cdf54f0

Observation 4fe1e241-cb3b-40c4-850b-f8463ff2ebdf · outbound

This paper cites ECCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ECCV , year=

Reference 72

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:708d45b0ebfa42571c2e3a625877ba661c7435df04c14f6b098e776c70738e8b

Observation a0439de7-a469-4514-bfb8-e9e6ff11df4d · outbound

This paper cites ICLR , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICLR , year=

Reference 73

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:458f4c31b8c9f00120167018d0068df27949bfe737bf00ab8bf6cbc9e474d0e1

Observation 37081cc2-10f4-4f4e-97e4-8581d0c064e2 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 74

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:b92cb0f934d1a3d9e9c08f3a9a482369b3d6219cd17df9aaaf1e270a93b17e15

Observation 6a0d0454-28c1-4ba0-ad7e-d7b0c618b174 · outbound

This paper cites NeurIPS , year=.

SigLIP-HD by Fine-to-Coarse Supervision NeurIPS , year=

Reference 75

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:a074d9d3d64a113e74fecee9505a148e6ebb92c56ddcb4a6d4a16380c7179937

Observation 12c86b32-e047-4427-8c77-a66fc37f36ae · outbound

This paper cites ICCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICCV , year=

Reference 76

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Source-reported events for the cited work

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:91470ee1a820e97f69fd67b13697b832f44416005784d261cefac2892a8b2010

Observation 192bb7c2-8cd0-4f93-b354-1b795be14ab5 · outbound

This paper cites Introducing our Multimodal Models , url =.

SigLIP-HD by Fine-to-Coarse Supervision Introducing our Multimodal Models , url =

Reference 77

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:28671e820afb8987ffe538a2cf9a951a931fb1ea01fdda837152c3d7f170b55c

Observation 3202476b-3cb5-43a0-966f-20fcdcbd9167 · outbound

This paper cites ICCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICCV , year=

Reference 78

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Source-reported events for the cited work

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:1514f89bc0cc14458409bf2a2968cb1f938d3d48e5f761a5d343e290d51ba733

Observation 72e40580-15d8-47dc-a2d6-15d7dea1fa8f · outbound

This paper cites DeepSeek-VL: Towards Real-World Vision-Language Understanding.

SigLIP-HD by Fine-to-Coarse Supervision DeepSeek-VL: Towards Real-World Vision-Language Understanding

Reference 79

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:121d7566a46810ecc093e43aae332f6bf39a51c85f6108d42a81f759aa50f99c

Observation cfd90b4b-6bcd-4aa9-a3ee-0cacdc40ac45 · outbound

This paper cites arXiv:2505.00742 , year=.

SigLIP-HD by Fine-to-Coarse Supervision arXiv:2505.00742 , year=

Reference 80

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:9b527b5346d4f244ead09840245bde31056b59e82ede4a6b1e0c10404ed8878c

Observation 4af1c45a-c2fe-471a-a2d1-f842a2179d17 · outbound

This paper cites ICCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICCV , year=

Reference 81

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:9516947199369ab542efbc2f8f050b02f88425c2371e3f6486c498e252f88291

Observation 2ae07005-edfc-408e-a801-ab47bd314742 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 82

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Source-reported events for the cited work

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:fa8b5f5b96d5d7c0686e31b5f7f8c5e0f20702d18854702a7a8778ab0452f7d3

Observation 78f67654-effe-452d-b07a-f4aa226a639a · outbound

This paper cites Distilling the Knowledge in a Neural Network.

SigLIP-HD by Fine-to-Coarse Supervision Distilling the Knowledge in a Neural Network

Reference 83

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:a5c8fcefe91d0b6658e995b29d49b3330703a4d88717097f42a000347ee53e68

Observation cd34b5f0-aa2d-481a-a9d3-66474d0817d4 · outbound

This paper cites Distill Any Depth: Distillation Creates a Stronger Monocular Depth Estimator.

SigLIP-HD by Fine-to-Coarse Supervision Distill Any Depth: Distillation Creates a Stronger Monocular Depth Estimator

Reference 84

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:2e772a479f6530521f1369c27965557a8248fb28593756b2866a8b73c09ef364

Observation 2ac15913-02ec-42f6-80ea-22908968d909 · outbound

This paper cites ICLR , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICLR , year=

Reference 85

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:db0c16ad8058db40723b3e9d7b5bda6160bad51ada4c8a7678463fa49b9e177c

Observation 42c6e98c-7e0d-4107-857f-6053559d67c9 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 86

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:0b68db9ed030fac7d725c0a4b17be25c58fc6ff802cacc8ae051809e86956b75

Observation e49429be-b39e-4931-be4b-c7e92d74e4f7 · outbound

This paper cites ICLR , year=.

SigLIP-HD by Fine-to-Coarse Supervision ICLR , year=

Reference 87

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:429a21c21b23c5615e454d944f2d5dc235ada24b18701729b09ca72f397ed316

Observation a8a49123-7d54-4bf8-9f59-7e362f16b222 · outbound

This paper cites NeurIPS , year=.

SigLIP-HD by Fine-to-Coarse Supervision NeurIPS , year=

Reference 88

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:7f5641c6d0b955c2139f389898ac8d97a18db841f8a2237afda40fcbf93f9999

Observation c66f2e02-a833-41c6-9e49-420252c150df · outbound

This paper cites ACL , year=.

SigLIP-HD by Fine-to-Coarse Supervision ACL , year=

Reference 89

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:22ce4981ba4c167d1474f831a23a22ffc8964ef10d3eb18de2f67d4a74c0bdef

Observation 4a0849e6-ff58-4553-9e8d-e2e7d1deafc6 · outbound

This paper cites WACV , year=.

SigLIP-HD by Fine-to-Coarse Supervision WACV , year=

Reference 90

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:95df2ac12dced5b45755435f4277e5e848d52d0beaa989850d1ce67a428e5f00

Observation 8280abac-2550-4893-ac05-1fec00ab189f · outbound

This paper cites ECCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ECCV , year=

Reference 91

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:eae1a0364508263b9b343a3a41c7c798ba30ed8a26202c1a2554c0d3ccfc4022

Observation c5873ce0-891c-410e-a37b-bc72009c6ca5 · outbound

This paper cites Grok-1.5 Vision Preview , url=.

SigLIP-HD by Fine-to-Coarse Supervision Grok-1.5 Vision Preview , url=

Reference 92

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:40b6a5fae887e4548e7268f6debe6330d6db6980f5aad9b39f579b7af34c839c

Observation bb5b53fc-b56f-4373-aa0d-fb89989f7821 · outbound

This paper cites CVPR , year=.

SigLIP-HD by Fine-to-Coarse Supervision CVPR , year=

Reference 93

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:f06b64b624c596b8581d8b002e2ca6296582d73ed5139bd33e3ef83a8987d224

Observation e4141604-6a80-4f01-9c57-a5c84ef9c743 · outbound

This paper cites NeurIPS , year=.

SigLIP-HD by Fine-to-Coarse Supervision NeurIPS , year=

Reference 94

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:a83fea723d117b3e7480b8728009fa02065a1a475d1fc4471a42beb3a769b9c0

Observation d10863e2-2dbe-4c9f-a157-c5e1a9b89356 · outbound

This paper cites EMNLP , year=.

SigLIP-HD by Fine-to-Coarse Supervision EMNLP , year=

Reference 95

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:f2875933dbe1a298a1c2ad220e97358e09c26390ba357461cdc76d72732ae48d

Observation 2e5139f1-32eb-4063-ae2e-08625d0865a9 · outbound

This paper cites NeurIPS , year=.

SigLIP-HD by Fine-to-Coarse Supervision NeurIPS , year=

Reference 96

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:23a85531308d8ef79cbf8924f08cdf0b59a8e1c5c6d9ef62e16985fcd4852820

Observation 0d8ce87a-5914-45da-bff5-c0581c33dd61 · outbound

This paper cites ECCV , year=.

SigLIP-HD by Fine-to-Coarse Supervision ECCV , year=

Reference 97

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:1c997cc11b779fd5364c658c298f4d9573b7ddafcf4ff350f7d6056609154363

Observation 48d9b169-7fa3-4831-a998-f386f8b7e1b0 · outbound

This paper cites Qwen2.5 Technical Report.

SigLIP-HD by Fine-to-Coarse Supervision Qwen2.5 Technical Report

Reference 98

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:5d45f6ac8ecb6e0b474be407c48878cffaa5b3a599d598149025a0ba2c4799f2

Observation 931576eb-8a9e-4f88-abbf-9acea90c14e2 · outbound

This paper cites The Llama 3 Herd of Models.

SigLIP-HD by Fine-to-Coarse Supervision The Llama 3 Herd of Models

Reference 99

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:418d304e219246059a5800dec6e5e1790aaee2faab2024932deecf4836161613

Observation 449f9965-ec42-4110-aafb-f07552e43653 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

SigLIP-HD by Fine-to-Coarse Supervision Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 100

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source=arxiv_source observed=2026-07-13T02:39:58.984385Z digest=sha256:1e956eff0d122bf0a35c84ea5b7e5d20bde8e2cae533242e9c4d54c532b876e2

Pith citing papers

No inbound Pith citation observations are available.