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Paper Citation Record · LEDGER

PathSelect: Sequential Token Selection for Whole Slide Pathology

As of 10 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 1 inbound Pith citation observation for arXiv:2607.23631.

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

pith.paper-citation-record.v1
2607.23631 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-30T17:15:35.029890Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T17:18:16.474432Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

54 of 54 outbound references displayed

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Outbound references

Observation 37f944c3-2d8b-4b31-9cdc-39043201b558 · outbound

This paper cites Scalar: Spatial- concept alignment for robust vision in harsh open world.Pattern Recognition, page 113203, 2026.

PathSelect: Sequential Token Selection for Whole Slide Pathology Scalar: Spatial- concept alignment for robust vision in harsh open world.Pattern Recognition, page 113203, 2026

Reference 1

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Observation cd0f065b-7822-4ce7-a009-459d530a8451 · outbound

This paper cites A unified multi-task framework enables interpretable chest radiograph analysis.Med, 2026.

PathSelect: Sequential Token Selection for Whole Slide Pathology A unified multi-task framework enables interpretable chest radiograph analysis.Med, 2026

Reference 2

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Observation 1d477477-ff97-483b-990d-b28c42e1e526 · outbound

This paper cites A foundation model for generalizable disease diagnosis in chest X-ray images.

PathSelect: Sequential Token Selection for Whole Slide Pathology A foundation model for generalizable disease diagnosis in chest X-ray images

Reference 3

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Observation 4c35d70b-73a9-4b61-8f92-48ca1f63994a · outbound

This paper cites XrayClaw: Cooperative-Competitive Multi-Agent Alignment for Trustworthy Chest X-ray Diagnosis.

PathSelect: Sequential Token Selection for Whole Slide Pathology XrayClaw: Cooperative-Competitive Multi-Agent Alignment for Trustworthy Chest X-ray Diagnosis

Reference 4

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Observation beddba0a-40e4-471f-ba6b-0090638eb304 · outbound

This paper cites Clinical-grade computational pathology using weakly supervised deep learning on whole slide images.Nature medicine, 25(8):1301–1309, 2019.

PathSelect: Sequential Token Selection for Whole Slide Pathology Clinical-grade computational pathology using weakly supervised deep learning on whole slide images.Nature medicine, 25(8):1301–1309, 2019

Reference 5

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Observation e792948d-29ef-44ee-9e69-3802b88f0931 · outbound

This paper cites A graph-transformer for whole slide image classification.

PathSelect: Sequential Token Selection for Whole Slide Pathology A graph-transformer for whole slide image classification

Reference 6

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Observation 808c7f7b-a765-43a4-9d5a-221e1b132d0a · outbound

This paper cites Streaming convolutional neural networks for end-to- end learning with multi-megapixel images.IEEE transactions on pattern analysis and machine intelligence, 44(3):1581–1590, 2020.

PathSelect: Sequential Token Selection for Whole Slide Pathology Streaming convolutional neural networks for end-to- end learning with multi-megapixel images.IEEE transactions on pattern analysis and machine intelligence, 44(3):1581–1590, 2020

Reference 7

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Observation ee02baa1-7ccf-4663-b609-3eead23ab043 · outbound

This paper cites Tc-ssa: Token compression via semantic slot aggregation for gigapixel pathology reasoning.MICCAI, 2026.

PathSelect: Sequential Token Selection for Whole Slide Pathology Tc-ssa: Token compression via semantic slot aggregation for gigapixel pathology reasoning.MICCAI, 2026

Reference 8

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Observation 5762b530-9c63-49c9-9beb-8544da2c8c6c · outbound

This paper cites Scaling vision transformers to gigapixel images via hierar- chical self-supervised learning.

PathSelect: Sequential Token Selection for Whole Slide Pathology Scaling vision transformers to gigapixel images via hierar- chical self-supervised learning

Reference 9

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Observation 1ef94d37-889f-4a55-be78-fa30c2b634f4 · outbound

This paper cites Dynamicvit: Efficient vision transformers with dynamic token sparsification.

PathSelect: Sequential Token Selection for Whole Slide Pathology Dynamicvit: Efficient vision transformers with dynamic token sparsification

Reference 10

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Observation 775111e9-5c66-45ba-a0bd-038cd0c77cbd · outbound

This paper cites Token merging: Your ViT but faster.

PathSelect: Sequential Token Selection for Whole Slide Pathology Token merging: Your ViT but faster

Reference 11

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Observation be5f0f3d-3207-485d-95e0-62318cfe8873 · outbound

This paper cites Beyond Surrogate Gradients: Fully Differentiable Token Pruning for Vision-Language Models.

PathSelect: Sequential Token Selection for Whole Slide Pathology Beyond Surrogate Gradients: Fully Differentiable Token Pruning for Vision-Language Models

Reference 12

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Observation b9700206-cd5e-4216-92d1-f50f7a4936b5 · outbound

This paper cites The model knows which tokens matter:automatic token selection via noise gating.arXiv preprint arXiv:2603.07135, 2026.

PathSelect: Sequential Token Selection for Whole Slide Pathology The model knows which tokens matter:automatic token selection via noise gating.arXiv preprint arXiv:2603.07135, 2026

Reference 13

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Observation 80569dfd-0c58-4cab-99b1-9ec9bf1b5859 · outbound

This paper cites Stepwise token selection for efficient multimodal large language models.

PathSelect: Sequential Token Selection for Whole Slide Pathology Stepwise token selection for efficient multimodal large language models

Reference 14

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Observation 4752fe06-6890-4ce7-a867-c307d2f6667d · outbound

This paper cites Learnable Token Sparsification for Efficient Gigapixel Whole Slide Image Reasoning.

PathSelect: Sequential Token Selection for Whole Slide Pathology Learnable Token Sparsification for Efficient Gigapixel Whole Slide Image Reasoning

Reference 15

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Observation c0d4c6e3-6704-46a1-9307-380b494ac9d9 · outbound

This paper cites Stochastic beams and where to find them: The gumbel-top- k trick for sampling sequences without replacement.

PathSelect: Sequential Token Selection for Whole Slide Pathology Stochastic beams and where to find them: The gumbel-top- k trick for sampling sequences without replacement

Reference 16

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Observation 07b2d4ae-a4e6-4797-8226-7fc2f6a80f51 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

PathSelect: Sequential Token Selection for Whole Slide Pathology Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 17

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Observation a85287ae-ca97-4de2-b044-2b472c7dd019 · outbound

This paper cites LearnPruner: Rethinking Attention-based Token Pruning in Vision Language Models.

PathSelect: Sequential Token Selection for Whole Slide Pathology LearnPruner: Rethinking Attention-based Token Pruning in Vision Language Models

Reference 18

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Observation 705c54dc-c369-4f30-9af0-c043ea22b1d1 · outbound

This paper cites Slidechat: A large vision-language assistant for whole-slide pathol- ogy image understanding.

PathSelect: Sequential Token Selection for Whole Slide Pathology Slidechat: A large vision-language assistant for whole-slide pathol- ogy image understanding

Reference 19

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Observation bb2f9732-e967-44f1-8717-f738bd46e17b · outbound

This paper cites One leaf reveals the season: Occlusion-based contrastive learning with semantic-aware views for efficient visual representation.

PathSelect: Sequential Token Selection for Whole Slide Pathology One leaf reveals the season: Occlusion-based contrastive learning with semantic-aware views for efficient visual representation

Reference 20

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Observation 59177f7c-5626-4cf3-aeaf-0034eb63146f · outbound

This paper cites Fewer tokens, greater scaling: Self-adaptive visual bases for efficient and expansive representation learning.arXiv preprint arXiv:2511.19515, 2026.

PathSelect: Sequential Token Selection for Whole Slide Pathology Fewer tokens, greater scaling: Self-adaptive visual bases for efficient and expansive representation learning.arXiv preprint arXiv:2511.19515, 2026

Reference 21

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Observation 82c76b2d-80bb-411a-8ff9-2252a79d1a50 · outbound

This paper cites Attention-based deep multiple instance learning.

PathSelect: Sequential Token Selection for Whole Slide Pathology Attention-based deep multiple instance learning

Reference 22

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Observation 5d3b36ea-3a78-4ad8-ac29-3fc48b4b4ed4 · outbound

This paper cites Data-efficient and weakly supervised computational pathology on whole-slide images.Nature biomedical engineering, 5(6):555–570, 2021.

PathSelect: Sequential Token Selection for Whole Slide Pathology Data-efficient and weakly supervised computational pathology on whole-slide images.Nature biomedical engineering, 5(6):555–570, 2021

Reference 23

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Observation 8cd9c1d3-456c-40e9-8fe9-6e19f65c5451 · outbound

This paper cites Transmil: Transformer based correlated multiple instance learning for whole slide image classification.Advances in neural information processing systems, 34:2136–2147, 2021.

PathSelect: Sequential Token Selection for Whole Slide Pathology Transmil: Transformer based correlated multiple instance learning for whole slide image classification.Advances in neural information processing systems, 34:2136–2147, 2021

Reference 24

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Observation 748798ee-6243-4c73-a36e-192c07c52b65 · outbound

This paper cites an unresolved cited work.

PathSelect: Sequential Token Selection for Whole Slide Pathology Unresolved cited work

Reference 25

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Observation fdf081da-70e7-4b3d-8319-f3a0f99f211b · outbound

This paper cites Learning heterogeneous tissues with mixture of experts for gigapixel whole slide images.

PathSelect: Sequential Token Selection for Whole Slide Pathology Learning heterogeneous tissues with mixture of experts for gigapixel whole slide images

Reference 26

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Observation 3449b44b-22e3-4d51-8bce-58031100c450 · outbound

This paper cites Multi-modal gated mixture of local-to-global experts for dynamic image fusion.

PathSelect: Sequential Token Selection for Whole Slide Pathology Multi-modal gated mixture of local-to-global experts for dynamic image fusion

Reference 27

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Observation 48a37495-aec1-4070-a986-9f9c08a6167b · outbound

This paper cites Feature re-embedding: Towards foundation model-level performance in computational pathology.

PathSelect: Sequential Token Selection for Whole Slide Pathology Feature re-embedding: Towards foundation model-level performance in computational pathology

Reference 28

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Observation 0673f8d5-f108-4117-b7ba-fede84709146 · outbound

This paper cites Revisiting end-to-end learning with slide-level supervision in computational pathology.Advances in Neural Information Processing Systems, 38:160279–160312, 2026.

PathSelect: Sequential Token Selection for Whole Slide Pathology Revisiting end-to-end learning with slide-level supervision in computational pathology.Advances in Neural Information Processing Systems, 38:160279–160312, 2026

Reference 29

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Observation 5062f046-4cdd-4079-8f8c-9fe2bc556c5c · outbound

This paper cites Towards a general-purpose foundation model for computational pathology.Nature medicine, 30(3):850–862, 2024.

PathSelect: Sequential Token Selection for Whole Slide Pathology Towards a general-purpose foundation model for computational pathology.Nature medicine, 30(3):850–862, 2024

Reference 30

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Observation c979e19c-e6a2-46d8-a9ae-cd87710dac64 · outbound

This paper cites A whole-slide foundation model for digital pathology from real-world data.Nature, 630(8015):181–188, 2024.

PathSelect: Sequential Token Selection for Whole Slide Pathology A whole-slide foundation model for digital pathology from real-world data.Nature, 630(8015):181–188, 2024

Reference 31

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Observation 4d383d96-19c3-4ecf-9473-d60d5b85fca7 · outbound

This paper cites Multimodal model for computational pathology: Representation learning and image compression.arXiv preprint arXiv:2603.18660, 2026.

PathSelect: Sequential Token Selection for Whole Slide Pathology Multimodal model for computational pathology: Representation learning and image compression.arXiv preprint arXiv:2603.18660, 2026

Reference 32

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Observation 66c42414-cee6-4ad4-b5b2-795048e0f53e · outbound

This paper cites MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation.

PathSelect: Sequential Token Selection for Whole Slide Pathology MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation

Reference 33

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Observation f7f8bff8-4763-4af1-a463-06deceeaa43d · outbound

This paper cites A visual–language foun- dation model for pathology image analysis using medical twitter.Nature medicine, 29(9):2307–2316, 2023.

PathSelect: Sequential Token Selection for Whole Slide Pathology A visual–language foun- dation model for pathology image analysis using medical twitter.Nature medicine, 29(9):2307–2316, 2023

Reference 34

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Observation ef09edb5-4adc-4d92-a05a-8ddd29f82c7d · outbound

This paper cites A visual-language foundation model for computational pathology.Nature medicine, 30(3):863–874, 2024.

PathSelect: Sequential Token Selection for Whole Slide Pathology A visual-language foundation model for computational pathology.Nature medicine, 30(3):863–874, 2024

Reference 35

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Observation 890723f1-3a52-4f86-9e55-0709b71b92d2 · outbound

This paper cites Cpath-omni: A unified multimodal foundation model for patch and whole slide image analysis in computational pathology.

PathSelect: Sequential Token Selection for Whole Slide Pathology Cpath-omni: A unified multimodal foundation model for patch and whole slide image analysis in computational pathology

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source=pdf_text observed=2026-07-30T17:15:34.958548Z digest=sha256:b9f812f137d14fc69f9a6a7e7814fd924e686341df1174faa075a19e5654aff2

Observation 76437f9d-c954-44b3-8a66-bd8d9210fa8e · outbound

This paper cites Segmentation and vascular vectorization for coronary artery by geometry-based cascaded neural network.IEEE Transactions on Medical Imaging, 44(1):259–269, 2024.

PathSelect: Sequential Token Selection for Whole Slide Pathology Segmentation and vascular vectorization for coronary artery by geometry-based cascaded neural network.IEEE Transactions on Medical Imaging, 44(1):259–269, 2024

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source=pdf_text observed=2026-07-30T17:15:34.963488Z digest=sha256:880f95d33974ac563d2064bc3ef4d1e998a97746b02fadd1c2a8a9155ffd3e3a

Observation b891a22c-8b9e-4bcb-a7df-06ca697ebddf · outbound

This paper cites Geometry-based end- to-end segmentation of coronary artery in computed tomography angiography.

PathSelect: Sequential Token Selection for Whole Slide Pathology Geometry-based end- to-end segmentation of coronary artery in computed tomography angiography

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source=pdf_text observed=2026-07-30T17:15:34.967331Z digest=sha256:7af2b62e785c6760675b12b807bf16f9d78ab3bb5b8bae3a6026e5e3cfaf601e

Observation 8f83c328-8222-4b5a-a616-debdb9b0c9a9 · outbound

This paper cites Efficient chest x-ray representation learning via semantic- partitioned contrastive learning.arXiv preprint arXiv:2603.07113, 2026.

PathSelect: Sequential Token Selection for Whole Slide Pathology Efficient chest x-ray representation learning via semantic- partitioned contrastive learning.arXiv preprint arXiv:2603.07113, 2026

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source=pdf_text observed=2026-07-30T17:15:34.970932Z digest=sha256:bfd253b5f06ba24f0944b907ba145d3bce310d99af82fb79436e9967b0d887c2

Observation 616ed26f-a1a6-405e-ae3f-080df971676b · outbound

This paper cites When tokens talk too much: A survey of multimodal long-context token compression across images, videos, and audios.arXiv preprint arXiv:2507.20198, 2025.

PathSelect: Sequential Token Selection for Whole Slide Pathology When tokens talk too much: A survey of multimodal long-context token compression across images, videos, and audios.arXiv preprint arXiv:2507.20198, 2025

Reference 40

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source=pdf_text observed=2026-07-30T17:15:34.974578Z digest=sha256:ab9b0db467a49fa7c528e797a3acafd6685ee05a3bdaacf43e4b1dc716de5799

Observation 0b617662-6b96-4d9f-a558-779cb4a86209 · outbound

This paper cites Mmtok: Multimodal coverage maximization for efficient inference of vlms.International Conference on Learning Representations, 2026.

PathSelect: Sequential Token Selection for Whole Slide Pathology Mmtok: Multimodal coverage maximization for efficient inference of vlms.International Conference on Learning Representations, 2026

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source=pdf_text observed=2026-07-30T17:15:34.978093Z digest=sha256:26b1bbd875d70e16677bb612713e8e6ad9a9621046e1733b1b5b079b605dc50f

Observation 14b27d67-d230-43a2-a126-7686e3456498 · outbound

This paper cites Beyond attention or similarity: Maximizing conditional diversity for token pruning in mllms.Advances in Neural Information Processing Systems, 38:25438–25468, 2026.

PathSelect: Sequential Token Selection for Whole Slide Pathology Beyond attention or similarity: Maximizing conditional diversity for token pruning in mllms.Advances in Neural Information Processing Systems, 38:25438–25468, 2026

Reference 42

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source=pdf_text observed=2026-07-30T17:15:34.981704Z digest=sha256:8086ffd8c57155f4631eaa60f8244d38aaec337f3d3c5dffad43142af182c969

Observation 7ca0456d-682b-417e-9254-31ee16082514 · outbound

This paper cites Dynamic-llava: Efficient multimodal large language models via dynamic vision-language context sparsifi- cation.

PathSelect: Sequential Token Selection for Whole Slide Pathology Dynamic-llava: Efficient multimodal large language models via dynamic vision-language context sparsifi- cation

Reference 43

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source=pdf_text observed=2026-07-30T17:15:34.985518Z digest=sha256:6305897564e87bd2ea5b0105538c4ddd4fea30a9ddecd98b38f0622c375f5eb0

Observation f48d75ad-bc87-4939-bab3-af3c1723f750 · outbound

This paper cites Hidrop: Hierarchical vision token reduction in mllms via late injection, concave pyramid pruning, and early exit.International Conference on Learning Representations, 2026.

PathSelect: Sequential Token Selection for Whole Slide Pathology Hidrop: Hierarchical vision token reduction in mllms via late injection, concave pyramid pruning, and early exit.International Conference on Learning Representations, 2026

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source=pdf_text observed=2026-07-30T17:15:34.989435Z digest=sha256:8911d737d5a79dddd5c2ad6038a9b0401b937efceacbac43a47be198989aa2ad

Observation e3bd1bb0-e612-4e7a-a913-0b5927b1daab · outbound

This paper cites Visionzip: Longer is better but not necessary in vision language models.

PathSelect: Sequential Token Selection for Whole Slide Pathology Visionzip: Longer is better but not necessary in vision language models

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source=pdf_text observed=2026-07-30T17:15:34.993629Z digest=sha256:ada2e336512891edc098cb3b69ce6e06837deae20fc0d874e83e5b14d7339c69

Observation a4f5c122-f8de-42e9-8f01-f03c05e79e9c · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

PathSelect: Sequential Token Selection for Whole Slide Pathology Categorical Reparameterization with Gumbel-Softmax

Reference 46

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source=pdf_text observed=2026-07-30T17:15:34.997280Z digest=sha256:6366cc35c7d08a832cae9f844260b9a19467662c6e26bea0fe215111b9eaeeac

Observation 0365e8b6-17ef-46ee-b311-2efba3a20474 · outbound

This paper cites Loc-path: Learning to compress for pathology multimodal large language models.arXiv preprint arXiv:2512.05391, 2025.

PathSelect: Sequential Token Selection for Whole Slide Pathology Loc-path: Learning to compress for pathology multimodal large language models.arXiv preprint arXiv:2512.05391, 2025

Reference 47

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source=pdf_text observed=2026-07-30T17:15:35.001832Z digest=sha256:bf283281e9d39ad042a57de07cac5f0f052d2eb53ebcd0b4a912ecd796fcab26

Observation d1aa1123-8326-4a18-97ba-1b9cb74b1230 · outbound

This paper cites Wsisum: Wsi summarization via dual-level semantic reconstruc- tion.Medical Image Analysis, page 103970, 2026.

PathSelect: Sequential Token Selection for Whole Slide Pathology Wsisum: Wsi summarization via dual-level semantic reconstruc- tion.Medical Image Analysis, page 103970, 2026

Reference 48

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source=pdf_text observed=2026-07-30T17:15:35.005766Z digest=sha256:2d7bd473e93fca9e92bf192132c879674c0d7311d9503fa049a1274bc12b634e

Observation 580ff95d-62bc-4ad0-8bbe-66b97609dcb1 · outbound

This paper cites Focus: Knowledge-enhanced adaptive visual compression for few-shot whole slide image classification.

PathSelect: Sequential Token Selection for Whole Slide Pathology Focus: Knowledge-enhanced adaptive visual compression for few-shot whole slide image classification

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source=pdf_text observed=2026-07-30T17:15:35.009459Z digest=sha256:51bd65d82e086417195a731cc39515e27e1b1a9a57666d7a17acf57527a27729

Observation 2d2670b3-c3d4-4300-a33d-c8020e92eb63 · outbound

This paper cites Wsi-vqa: Interpreting whole slide images by generative visual question answering.

PathSelect: Sequential Token Selection for Whole Slide Pathology Wsi-vqa: Interpreting whole slide images by generative visual question answering

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source=pdf_text observed=2026-07-30T17:15:35.013536Z digest=sha256:67bd7aa6b2c76128c49b721a7c2347fe915752fee7dc86d84161bfc5f66bacd0

Observation 08847522-c34b-4e59-82e9-e35a39c32fff · outbound

This paper cites Llava-med: Training a large language-and-vision assistant for biomedicine in one day.Advances in Neural Information Processing Systems, 36:28541–28564, 2023.

PathSelect: Sequential Token Selection for Whole Slide Pathology Llava-med: Training a large language-and-vision assistant for biomedicine in one day.Advances in Neural Information Processing Systems, 36:28541–28564, 2023

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source=pdf_text observed=2026-07-30T17:15:35.017469Z digest=sha256:ce75e2d4755f44ea7e01a3bbbd599b28fecd5f454d7a54a4081d1ece999d2f33

Observation 8143a059-8863-4c64-b865-2aa3866c490b · outbound

This paper cites Quilt-llava: Visual instruction tuning by extracting localized narratives from open-source histopathology videos.

PathSelect: Sequential Token Selection for Whole Slide Pathology Quilt-llava: Visual instruction tuning by extracting localized narratives from open-source histopathology videos

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source=pdf_text observed=2026-07-30T17:15:35.021240Z digest=sha256:9440af203d6b0603069daba20588dc790024a5034d0acf44375199cc6f4390e3

Observation cbaa40b7-f1fe-4f7f-85c2-4d7f38beff23 · outbound

This paper cites GSCo: Towards Generalizable AI in Medicine via Generalist-Specialist Collaboration.

PathSelect: Sequential Token Selection for Whole Slide Pathology GSCo: Towards Generalizable AI in Medicine via Generalist-Specialist Collaboration

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source=pdf_text observed=2026-07-30T17:15:35.025610Z digest=sha256:ee6c8e604b4bcf70551125c337424336baba5596a38f92d35dadbaad2ef7adb1

Observation 3b943081-3dca-4ef8-9978-77b3b63b1063 · outbound

This paper cites GPT-4o System Card.

PathSelect: Sequential Token Selection for Whole Slide Pathology GPT-4o System Card

Reference 54

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source=pdf_text observed=2026-07-30T17:15:35.029890Z digest=sha256:05e7ab44e643efb6c2850406b463f37d5c56e011d494832e3fecb11186bc5f31

Pith citing papers

Observation 00836b36-0e4f-4756-8dee-4246054c7f18 · inbound

DiffPrune: differentiable information throttling for token pruning in vision-language models cites this paper.

DiffPrune: differentiable information throttling for token pruning in vision-language models PathSelect: Sequential Token Selection for Whole Slide Pathology

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source=pdf_text observed=2026-08-04T17:18:16.474432Z digest=sha256:d5a0b01a060edc150f09c19911b96810f92bce64a729fbdff7938827dd37bbfb