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Paper Citation Record · LEDGER

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning

As of 9 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 2 inbound Pith citation observations for arXiv:2505.15687.

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

pith.paper-citation-record.v1
2505.15687 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:16:20.070236Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T19:32:46.604200Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T21:47:27.810427Z

Reference resolution

14 of 14 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1a312f3a-b72d-4c8c-871d-f1153062300b · outbound

This paper cites Qwen2.5-VL Technical Report.

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning Qwen2.5-VL Technical Report

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:19.581785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:19.581785Z digest=sha256:b1a2a7f767097c55ffab577923a4bd4eedc345126073fb8286b5f3843de67581

Observation 2b24a36c-6a6b-4d7d-a099-5bc9ee094e34 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning Adam: A Method for Stochastic Optimization

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:19.813439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:19.813439Z digest=sha256:f8caf81bb4604f53634c5282ef7368a4f6ab2a524b5592d5bb1c6a897be5db55

Observation 41977d72-e92d-4151-beac-93c7d84366b8 · outbound

This paper cites Table 7: Pathological Reasoning Templates.

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning Table 7: Pathological Reasoning Templates

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:16:20.479835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:16:20.064550Z digest=sha256:810c99d2ddb47e75207431d1d45e159451b881ab4b8ecab146a86b91d5cf4b03

Observation 66eeabb7-a71b-4f89-82a0-afebed8733c6 · outbound

This paper cites Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation.

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:20.032641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:20.032641Z digest=sha256:ba478dfe619b1d0e10c8316260b1ca4ffd92d5adfb094010c3c298ff59a9b564

Observation 1eac1a94-f573-4b77-8f66-3d7e8b0fdd3e · outbound

This paper cites Proximal Policy Optimization Algorithms.

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning Proximal Policy Optimization Algorithms

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:20.048658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:20.048658Z digest=sha256:2c9b96714a471b4c2900d4c0b083755964f4dca1ddf2eb2ed0626af51cbed0ad

Observation e36dbd80-8242-4f5d-b36d-18cfb67fbf4b · outbound

This paper cites CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology.

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:20.054485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:20.054485Z digest=sha256:34fc8ba7325bc62b0140d617a9ead4c2eb78f1a468a5c9ac2029ade827f6d414

Observation 65c77c8a-7e9d-43b6-b516-570f1fc5b551 · outbound

This paper cites A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model.

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:20.059202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:20.059202Z digest=sha256:1d31dc461e6e9975c6e89e7df0cad6e5a43df29ffa03f46e47e40a54e1e720d3

Observation a15b40fa-2d7a-4256-b78e-c62ce1313bbe · outbound

This paper cites These observations underscore the need for adaptive token allocation, where the model dynamically adjusts its computational budget based on input complexity.

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning These observations underscore the need for adaptive token allocation, where the model dynamically adjusts its computational budget based on input complexity

Reference 256

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:16:20.454310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:16:20.070236Z digest=sha256:a30cb3a444db48b162aab90f3cb21f5ae5e805d909106692ba815f3fea0f14e4

Observation 56510d17-a0f9-49b2-8460-1ef89a20a49f · outbound

This paper cites Med-r1: Reinforcement learning for generalizable medical reasoning in vision-language models.arXiv preprint arXiv:2503.13939,.

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning Med-r1: Reinforcement learning for generalizable medical reasoning in vision-language models.arXiv preprint arXiv:2503.13939,

Reference 2014

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:19.883374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:19.883374Z digest=sha256:94d2eae1542d6480af5150316ecea485a397eeaebd8e7ff0cf9b647b7ae67121

Observation f99f5b5a-cc23-4ecd-9221-92d73947217d · outbound

This paper cites OpenAI o1 System Card.

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning OpenAI o1 System Card

Reference 2018

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unresolved
no resolver link, observed 2026-08-07T15:16:19.750133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:19.750133Z digest=sha256:25ddd67d11943e5bc3aba782b15cbed4c20376c3920012da898b772de25eb548

Observation 26384ab9-86a3-496c-93d3-cec7c42d4ccd · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:19.673067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:19.673067Z digest=sha256:021c3fc8ab64aedd661977ad9f692be532614d2fbadae510a9935728a6e42c53

Observation d668d7bc-6c98-44d8-b7a8-0a4afe4ea8e8 · outbound

This paper cites Visual-RFT: Visual Reinforcement Fine-Tuning.

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning Visual-RFT: Visual Reinforcement Fine-Tuning

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:19.973477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:19.973477Z digest=sha256:17e4b0bc6d66adcf578104e3fc125a08c83e2633f9aeacc9630ec0843c079964

Observation bd3a22e8-c138-4c89-a138-f69b4dd5b2d1 · outbound

This paper cites Scaling self-supervised learning for histopathology with masked image modeling.medRxiv, pages 2023–07,.

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning Scaling self-supervised learning for histopathology with masked image modeling.medRxiv, pages 2023–07,

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:16:20.503952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:16:19.612449Z digest=sha256:57118f3300fe166219d8e0084e90f49ad2a36775d17621ff2efd9b3e549f733e

Observation 22594480-b835-421e-8756-746b1da011c3 · outbound

This paper cites PathVQA: 30000+ Questions for Medical Visual Question Answering.

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning PathVQA: 30000+ Questions for Medical Visual Question Answering

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:19.716034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:16:19.716034Z digest=sha256:b5a0b4dc522b7ff3a6122fb91037da78dca8231d31a10fc4f3e7be393eaba2d7

Pith citing papers

Observation a98639b0-4254-4aa2-b357-e09a7d157242 · inbound

TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots cites this paper.

TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-17T20:30:11.129835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-17T20:29:39.744103Z digest=sha256:e6b02ed0752bd0e69ca8dac8db0b6672329d3099430d086bfc540133a6ef986f

Observation eee22f86-2f03-4df0-b546-9099d30ce44e · inbound

A Multi-modal Agentic Co-pilot for Evidence Grounded Computational Pathology cites this paper.

A Multi-modal Agentic Co-pilot for Evidence Grounded Computational Pathology Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-07-02T21:47:27.811656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T19:32:46.604200Z digest=sha256:79695020143f5930a266438fcb8f0ab49fd4291d216e3386453a9302e94cf946