Paper Citation Record · LEDGER

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement

As of 21 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2411.09894.

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

pith.paper-citation-record.v1
2411.09894 v1

Coverage vector

measured 42 of 42 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-12T20:17:30.154037Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

42 of 42 outbound references displayed

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External citation measurements

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Outbound references

Observation be7d5c09-4f25-4dda-8657-6b32d9a2606a · outbound

This paper cites Deep Variational Information Bottleneck.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Deep Variational Information Bottleneck

Reference 1

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Observation 8eadd42f-dcb6-4be0-9ed5-5ebd1496e1a4 · outbound

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

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Scaling vision transformers to gigapixel images via hierarchical self-supervised learning

Reference 2

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Observation 92423f02-02a7-4563-80d7-274bb0457bd1 · outbound

This paper cites Towards a general- purpose foundation model for computational pathology.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Towards a general- purpose foundation model for computational pathology

Reference 3

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Observation e367f829-7257-4943-b5b1-3f770f34e092 · outbound

This paper cites Robust whole slide image analysis for cervical cancer screening using deep learning.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Robust whole slide image analysis for cervical cancer screening using deep learning

Reference 4

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Observation b3403d66-046a-4f58-9cc3-024a3df10dfb · outbound

This paper cites Deep learning-based transformation of h&e stained tissues into special stains.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Deep learning-based transformation of h&e stained tissues into special stains

Reference 5

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Observation 27559774-312a-4b56-9f0c-77e33411c834 · outbound

This paper cites Learning Robust Representations via Multi-View Information Bottleneck.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Learning Robust Representations via Multi-View Information Bottleneck

Reference 6

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Observation d744092b-864f-4d50-99b3-57ec287adbf5 · outbound

This paper cites Scaling self-supervised learning for histopathology with masked image modeling.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Scaling self-supervised learning for histopathology with masked image modeling

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:30.465727Z

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Observation 9a89be02-0aef-484d-a551-2c8a6c7a9225 · outbound

This paper cites On information plane analyses of neural network classifiers—a review.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement On information plane analyses of neural network classifiers—a review

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:30.456949Z

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Observation 10f9448a-254f-4d3e-8914-10d5e01bcfcb · outbound

This paper cites Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Philip Bachman, Adam Trischler, and Yoshua Bengio.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Philip Bachman, Adam Trischler, and Yoshua Bengio

Reference 9

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Observation 74758a0d-6a79-425b-9a69-53009ab8a3fb · outbound

This paper cites Hˆ 2-mil: exploring hierarchical representation with heterogeneous multiple instance learning for whole slide image analysis.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Hˆ 2-mil: exploring hierarchical representation with heterogeneous multiple instance learning for whole slide image analysis

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:30.439558Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 75bac577-6bbc-4495-8fcb-f89dabb96477 · outbound

This paper cites The impact of site-specific digital histology signatures on deep learning model accuracy and bias.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement The impact of site-specific digital histology signatures on deep learning model accuracy and bias

Reference 11

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Observation 2da82295-4003-40cc-a755-9a516d488f39 · outbound

This paper cites Densely connected convolutional networks.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Densely connected convolutional networks

Reference 12

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Observation ddafc317-990c-46b0-b590-b69d5c9b5303 · outbound

This paper cites Conslide: Asynchronous hierarchical interaction transformer with breakup-reorganize rehearsal for contin- ual whole slide image analysis.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Conslide: Asynchronous hierarchical interaction transformer with breakup-reorganize rehearsal for contin- ual whole slide image analysis

Reference 13

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Observation 8d0c94d2-ae8e-4e8d-a2c1-a69a3833b3cc · outbound

This paper cites A visual–language foundation model for pathology image analysis using medical twitter.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement A visual–language foundation model for pathology image analysis using medical twitter

Reference 14

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Observation 12c8708a-b54f-4f2c-b05c-11064e76d9db · outbound

This paper cites Quilt-1m: One million image-text pairs for histopathology.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Quilt-1m: One million image-text pairs for histopathology

Reference 15

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Observation c3c9df68-bc6a-41ea-b951-04771105e3a9 · outbound

This paper cites Attention-based deep multiple instance learning.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Attention-based deep multiple instance learning

Reference 16

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Observation 743c0110-80bf-431a-a091-7f18912d21fe · outbound

This paper cites Additive mil: Intrinsically interpretable multiple instance learning for pathology.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Additive mil: Intrinsically interpretable multiple instance learning for pathology

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:30.392836Z

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Observation 0cefdf2b-6618-487d-b428-8b72dd4914c8 · outbound

This paper cites Auto-Encoding Variational Bayes.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Auto-Encoding Variational Bayes

Reference 18

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Observation b9090853-f9ab-4e57-8c41-a178d4cc4f27 · outbound

This paper cites Self-normalizing neural networks.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Self-normalizing neural networks

Reference 19

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Observation e3d60709-b535-44cb-bb91-a9e74a9ed91a · outbound

This paper cites Clipath: Fine-tune clip with visual feature fusion for pathology image analysis towards minimizing data collection efforts.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Clipath: Fine-tune clip with visual feature fusion for pathology image analysis towards minimizing data collection efforts

Reference 20

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Observation 4c5de793-5034-4899-bb86-4a92297f8afd · outbound

This paper cites Dual-stream multiple instance learning network for whole slide image classification with self-supervised contrastive learning.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Dual-stream multiple instance learning network for whole slide image classification with self-supervised contrastive learning

Reference 21

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Observation 6bedcf8b-9297-4c1e-8a0e-bc4f00af827b · outbound

This paper cites Generalizable whole slide image classification with fine-grained visual- semantic interaction.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Generalizable whole slide image classification with fine-grained visual- semantic interaction

Reference 22

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Observation f06f6a5d-67fc-4584-8cd4-24f8c393ad77 · outbound

This paper cites Artificial intelligence for multimodal data integration in oncology.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Artificial intelligence for multimodal data integration in oncology

Reference 23

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Observation 711fc8e9-b5c3-40b2-a2c2-fb55b219ecbb · outbound

This paper cites PathoTune: Adapting Visual Foundation Model to Pathological Specialists.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement PathoTune: Adapting Visual Foundation Model to Pathological Specialists

Reference 24

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Observation 03f130b4-823e-4a0e-bc7b-7ac40513aa91 · outbound

This paper cites A visual-language foundation model for computational pathology.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement A visual-language foundation model for computational pathology

Reference 25

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Observation c1e5328c-c652-4741-9b20-a36a6c43faa8 · outbound

This paper cites Data-efficient and weakly supervised computational pathology on whole-slide images.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Data-efficient and weakly supervised computational pathology on whole-slide images

Reference 26

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Observation 5f711a28-d0e7-4a1f-b1cd-9077ce692b13 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Representation Learning with Contrastive Predictive Coding

Reference 27

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Observation bb85c772-94c4-4d94-bd42-329d2fbac422 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement DINOv2: Learning Robust Visual Features without Supervision

Reference 28

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Observation 63a829c3-5bb7-4b32-bed0-083247edefdf · outbound

This paper cites The rise of ai language patholo- gists: Exploring two-level prompt learning for few-shot weakly-supervised whole slide image classification.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement The rise of ai language patholo- gists: Exploring two-level prompt learning for few-shot weakly-supervised whole slide image classification

Reference 29

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Observation c3cc15b5-82b7-4bc4-b573-4f8630e8f92e · outbound

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

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Learning transferable visual models from natural language supervision

Reference 30

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Observation 4c00cde0-43a8-4a25-b856-d2b58cfb0099 · outbound

This paper cites Fine-tuning and training of densenet for histopathology image representation using tcga diagnostic slides.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Fine-tuning and training of densenet for histopathology image representation using tcga diagnostic slides

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:30.323098Z

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Observation 42c95881-16ed-4e4e-8af6-f57ce49c8e83 · outbound

This paper cites Model-based domain generalization.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Model-based domain generalization

Reference 32

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Observation 74551883-ac86-4155-83c6-9cda4b4be0a6 · outbound

This paper cites Transmil: Transformer based correlated multiple instance learning for whole slide image classification.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Transmil: Transformer based correlated multiple instance learning for whole slide image classification

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:30.308521Z

Source-reported events for the cited work

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Observation cc7d62d4-d60f-4729-bb7c-6918c13366c7 · outbound

This paper cites Artificial intelligence in histopathology: enhancing cancer research and clinical oncology.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Artificial intelligence in histopathology: enhancing cancer research and clinical oncology

Reference 34

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Observation 023c4f12-339a-4ab1-88d5-d9b578c99c37 · outbound

This paper cites Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology

Reference 35

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This paper cites Virchow: A Million-Slide Digital Pathology Foundation Model.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Virchow: A Million-Slide Digital Pathology Foundation Model

Reference 36

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Observation 44388d36-3a5b-4ca2-9eba-91730f8bbd1b · outbound

This paper cites Transformer-based unsupervised contrastive learning for histopathological image classification.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Transformer-based unsupervised contrastive learning for histopathological image classification

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:30.290183Z

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Observation c45e63eb-0331-4b4d-b7e7-ebdf1730a477 · outbound

This paper cites Collaborative optimization and aggregation for decentralized do- main generalization and adaptation.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Collaborative optimization and aggregation for decentralized do- main generalization and adaptation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:30.281112Z

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Observation 62480319-0b23-454f-963b-cfb4cccfdb4c · outbound

This paper cites Bayes-mil: A new probabilistic perspective on attention-based multiple instance learning for whole slide images.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Bayes-mil: A new probabilistic perspective on attention-based multiple instance learning for whole slide images

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:30.270807Z

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Observation 32d98f6e-402f-4a2b-b515-de87736d9bb6 · outbound

This paper cites Dtfd-mil: Double-tier feature distillation multiple instance learning for 12 histopathology whole slide image classification.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Dtfd-mil: Double-tier feature distillation multiple instance learning for 12 histopathology whole slide image classification

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:30.261629Z

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Observation 2699370b-1a2e-424f-bc04-921c7cffe88e · outbound

This paper cites Text-guided foundation model adaptation for pathological image classification.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement Text-guided foundation model adaptation for pathological image classification

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:17:30.253408Z

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Observation abee8d33-51a6-4090-9274-0eb7b1bc31d1 · outbound

This paper cites iBOT: Image BERT Pre-Training with Online Tokenizer.

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement iBOT: Image BERT Pre-Training with Online Tokenizer

Reference 42

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Pith citing papers

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