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Paper Citation Record · LEDGER

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways

As of 17 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2508.07308.

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

pith.paper-citation-record.v1
2508.07308 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:15:09.898848Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T16:14:18.164403Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T01:57:32.123183Z

Reference resolution

52 of 52 outbound references displayed

  • verified exact2
  • verified fuzzy18
  • unresolved31
  • parse uncertain1
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 52a55cba-67d0-4366-8538-594f783b9ac9 · outbound

This paper cites GPT-4 Technical Report.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways GPT-4 Technical Report

Reference 1

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source=pdf_text observed=2026-08-05T22:15:09.700858Z digest=sha256:d88bdfd0b1ba53a5bb308bc974656bd8493371960570ea7ff22713321fa3346c

Observation b0f28552-57db-4a2b-89f6-e612755ef227 · outbound

This paper cites A Comprehensive Overview of Large Language Models.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways A Comprehensive Overview of Large Language Models

Reference 2

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source=pdf_text observed=2026-08-05T22:15:09.705004Z digest=sha256:c9f7fde6b0a3ef80d3673d14dfb77876416f9d86e7fda6e77eb63bafd120dadf

Observation 48cf0928-8943-4f45-9767-37cb06d4547e · outbound

This paper cites Unifying Large Language Models and Knowledge Graphs: A Roadmap.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Unifying Large Language Models and Knowledge Graphs: A Roadmap

Reference 3

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source=pdf_text observed=2026-08-05T22:15:09.709334Z digest=sha256:92b36ce3fcd67a81e61cc0a7cfced1f03d82e00fff9ce0a6c48b46e21b3dcd35

Observation 5f902965-1f77-467a-b735-b40b793ebd0c · outbound

This paper cites Role of chat gpt in public health.Annals of biomedical engineering, 51(5):868–869, 2023.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Role of chat gpt in public health.Annals of biomedical engineering, 51(5):868–869, 2023

Reference 4

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raw_fallback, observed 2026-08-05T22:15:10.447020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.713285Z digest=sha256:e525b6563fcbe82a6ee15511b61b08c223d41bea9443e4b0029fc31cb6ab4b42

Observation e3f87fdd-46fc-48a0-98fb-6c75b068c491 · outbound

This paper cites Benchmarking Retrieval-Augmented Generation for Medicine.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Benchmarking Retrieval-Augmented Generation for Medicine

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.717218Z digest=sha256:dff36d4845758947fcbf5d0895e1e738cc8ec42685d933c3c42ee37ae25a23c6

Observation 35cde59d-842f-4914-aa34-6d39486c5bec · outbound

This paper cites A survey on rag with llms.Procedia Computer Science, 246:3781–3790, 2024.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways A survey on rag with llms.Procedia Computer Science, 246:3781–3790, 2024

Reference 6

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raw_fallback, observed 2026-08-05T22:15:10.435730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.721402Z digest=sha256:fafbc47126a7c358df193847bec45a4b98b55d3661f761ae9dddc6a5fac2a4a7

Observation 7c3333ae-4a14-43b7-808e-7ee5e2c5baec · outbound

This paper cites Medical Dialogue: A Survey of Categories, Methods, Evaluation and Challenges.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Medical Dialogue: A Survey of Categories, Methods, Evaluation and Challenges

Reference 7

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verified exact
local_arxiv, observed 2026-08-05T22:15:10.155055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.725532Z digest=sha256:23224d71f1a03878e8070fab39552c66a4f0b93c991a3283ecaa5357942feda9

Observation a05bf3a0-e8ab-4031-941b-f2b70c36ffd3 · outbound

This paper cites Extract- ing training data from large language models.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Extract- ing training data from large language models

Reference 8

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raw_fallback, observed 2026-08-05T22:15:10.424558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.730009Z digest=sha256:9fee24f49941d6a12f234a8dcdf35195d4e8cbfb19e3920611afa5ce70f2f438

Observation 4b548cd2-bf4e-4cf5-8a8f-09030a3e1df1 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Direct preference optimization: Your language model is secretly a reward model

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.733993Z digest=sha256:94487bfce5ffedcd52d81217a0e0e99c871433bc25f8749e987d45a18f7f1817

Observation f1ce7d53-94de-4f0c-8599-07a826ef19b2 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.Advances in Neural Information Processing Systems, 33:9459–9474, 2020.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Retrieval-augmented generation for knowledge-intensive nlp tasks.Advances in Neural Information Processing Systems, 33:9459–9474, 2020

Reference 10

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source=pdf_text observed=2026-08-05T22:15:09.737403Z digest=sha256:01146307b681b85584e97fb2a0c99bfffea6486fef32a3331db7c8e83cfd9f64

Observation c6b1946a-d7de-4bf5-a86b-0d3813b4426a · outbound

This paper cites Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing.ACM Computing Surveys, 55(9):1–35, 2023.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing.ACM Computing Surveys, 55(9):1–35, 2023

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.400111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.740686Z digest=sha256:13b8548692f79950679e29f8cf2bff5ded5eb0d7acc2b808382202ebae9980b6

Observation e8c253ae-a0f4-4172-803a-0ed99140fe1c · outbound

This paper cites Retrieval augmented language model pre-training.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Retrieval augmented language model pre-training

Reference 12

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T22:15:09.744215Z digest=sha256:c360dd848197a37843bee40ed532884c6a1e8807ecea7c940497d90824884ce0

Observation f58a69a5-2c1f-48bd-9514-d45d7168163e · outbound

This paper cites Atlas: Few-shot learning with retrieval augmented language models.Journal of Machine Learning Research, 24(251):1–43, 2023.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Atlas: Few-shot learning with retrieval augmented language models.Journal of Machine Learning Research, 24(251):1–43, 2023

Reference 13

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raw_fallback, observed 2026-08-05T22:15:10.382576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.748222Z digest=sha256:522c142699392eb31f7cf18f081f47c06ce3a2ef9510b0d8b971c27f2c419220

Observation 5ed4a2df-d488-45b0-8f3f-edd0337cce11 · outbound

This paper cites Retrieving Supporting Evidence for LLMs Generated Answers.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Retrieving Supporting Evidence for LLMs Generated Answers

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.752027Z digest=sha256:6bd0e5af01e5667654351d63d48c918aab7bc487664e601559f6cc868c002307

Observation 3bef35ef-1e42-4b3a-be61-830d1c9dfb68 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.755768Z digest=sha256:7228af8ca8ef55f956fda31e2fb9a71b3647e9ff73a396b67b3e2e8ff834d168

Observation a61af990-ee50-4efc-a8dc-3021f7dbfcd3 · outbound

This paper cites Health-LLM: Personalized Retrieval-Augmented Disease Prediction System.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Health-LLM: Personalized Retrieval-Augmented Disease Prediction System

Reference 16

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source=pdf_text observed=2026-08-05T22:15:09.760293Z digest=sha256:af801f84f9c377e3ee73b94d78673df4826b14ab24d192ea889fbe43f0e57657

Observation f4fa7d9d-b205-444e-b6e1-ec2955b01414 · outbound

This paper cites HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversations.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversations

Reference 17

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source=pdf_text observed=2026-08-05T22:15:09.763907Z digest=sha256:2e6de395dd840865936875c5291dec9f77347ed47dbaf79bcb9669bd25fa0113

Observation 46cdd1c6-3098-4c1c-94a3-8237d206aa50 · outbound

This paper cites Enhancing Large Language Models with Domain-specific Retrieval Augment Generation: A Case Study on Long-form Consumer Health Question Answering in Ophthalmology.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Enhancing Large Language Models with Domain-specific Retrieval Augment Generation: A Case Study on Long-form Consumer Health Question Answering in Ophthalmology

Reference 18

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local_arxiv, observed 2026-08-05T22:15:10.100836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.767547Z digest=sha256:49f7a84aede879b8f5728c12504175bf1f0a8253f8b14e798793ac4992f73d68

Observation d336674c-dcd5-4b24-a79b-e28b9cbd8923 · outbound

This paper cites Graph retrieval-augmented generation for large language models: A survey.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Graph retrieval-augmented generation for large language models: A survey

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.371409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.771480Z digest=sha256:a43c08c6b0aff98bc78bbf782a7ec2ab7d9d7126200d74b88c6d2fc8599efdcc

Observation 000a6337-85ba-4db3-915c-847e61b3448a · outbound

This paper cites medIKAL: Integrating Knowledge Graphs as Assistants of LLMs for Enhanced Clinical Diagnosis on EMRs.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways medIKAL: Integrating Knowledge Graphs as Assistants of LLMs for Enhanced Clinical Diagnosis on EMRs

Reference 20

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source=pdf_text observed=2026-08-05T22:15:09.774911Z digest=sha256:dd0a3f22ecc0718fd8aefe51f8715dd0d2b6edff854384794750fdad436e511f

Observation ed7fe314-f1d8-4bd1-8b81-f54a1a5136c0 · outbound

This paper cites Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation

Reference 21

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source=pdf_text observed=2026-08-05T22:15:09.778474Z digest=sha256:d423a3b49690f8582b710ff98f36be6604d2fd78953338e4ee89c0fad0543a09

Observation f93b319c-adbe-439a-bbad-8eb8a1602f6f · outbound

This paper cites Leveraging retrieval-augmented generation for reliable medical question answering using large language models.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Leveraging retrieval-augmented generation for reliable medical question answering using large language models

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.359574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.782088Z digest=sha256:46b359b36abf99268df99cff5b05367af03b9606ce110800ae293ef491ae9626

Observation 3a3d6e19-488a-40f7-b754-b4d05b56428a · outbound

This paper cites HEAD-QA: A Healthcare Dataset for Complex Reasoning.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways HEAD-QA: A Healthcare Dataset for Complex Reasoning

Reference 23

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T22:15:09.785590Z digest=sha256:5bbdbf67fcb20a878add5b699a9c453632cf80510204f9613fb72a13e318affb

Observation e8dd7352-0cf5-4239-8fff-d5ad575f5307 · outbound

This paper cites MeDiaQA: A Question Answering Dataset on Medical Dialogues.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways MeDiaQA: A Question Answering Dataset on Medical Dialogues

Reference 24

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source=pdf_text observed=2026-08-05T22:15:09.789267Z digest=sha256:cc01c5c86bd9bfdab118ec02fadb9c61d4cd70730bc90b4823485f222e35534c

Observation ab22f3d4-f4a1-41af-bf3b-9a6fa15e8065 · outbound

This paper cites What disease does this patient have? a large-scale open domain question answering dataset from medical exams.Applied Sciences, 11(14):6421, 2021.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways What disease does this patient have? a large-scale open domain question answering dataset from medical exams.Applied Sciences, 11(14):6421, 2021

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.793387Z digest=sha256:4ac4bdf455e8cbfa266b65345bdf3395656aa5f587c6ba419a767dd6478c6a91

Observation ff1ed2d5-8daa-4bb9-a8fc-81dbf35ed8bd · outbound

This paper cites Pub- medqa: A dataset for biomedical research question answering.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Pub- medqa: A dataset for biomedical research question answering

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.341584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.796669Z digest=sha256:cea1dd1633e153cc6f6310ee8ebce137371efbc4fa8e2cea866cc88a0b9a1648

Observation 59b8af93-c29a-488b-8b3d-56849203a6b8 · outbound

This paper cites Medcalc-bench: Evaluating large language models for medical calculations.Advances in Neural Information Processing Systems, 37:84730–84745, 2024.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Medcalc-bench: Evaluating large language models for medical calculations.Advances in Neural Information Processing Systems, 37:84730–84745, 2024

Reference 27

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raw_fallback, observed 2026-08-05T22:15:10.330807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.800015Z digest=sha256:79a18f378180d83ba1be33f6f196e1eda6a411eaab36d4a6ae161eb708ae46f7

Observation dd5a822a-8d12-47b1-91a2-6922c53db6fa · outbound

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

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways PathVQA: 30000+ Questions for Medical Visual Question Answering

Reference 28

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T22:15:09.804058Z digest=sha256:6b60e6659ecfb636ef24b817bd7b6b255ea65fee27f421cb86a16793a9455409

Observation 79c74b63-3575-4107-a71c-1c6a7baa8a60 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Measuring Massive Multitask Language Understanding

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.808044Z digest=sha256:7f65045164a1216ce756e029bdfbfa45ecbcc20dae9fca019ee135c8515a93e5

Observation 095c61c5-541d-402c-bfe5-81fd8a7f004f · outbound

This paper cites MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding

Reference 30

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no resolver link, observed 2026-08-05T22:15:09.811969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.811969Z digest=sha256:8609a6e588746efa5c42b44a8884f1f535124d9f1be895da5c8baa1101fafc4b

Observation 7866e88d-2c80-478e-bfd1-6336e1c3debe · outbound

This paper cites Knowledge graph-based question answering with electronic health records.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Knowledge graph-based question answering with electronic health records

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.318056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.815778Z digest=sha256:74bfcdb0ebde421f1cc2649d95ba682beab51082744fc6e4ead69bf76c0bc779

Observation 503e2e58-3d08-4498-b4e2-90ffb1302189 · outbound

This paper cites Ultramedical: Building specialized generalistsinbiomedicine.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Ultramedical: Building specialized generalistsinbiomedicine

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.306110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.820612Z digest=sha256:b143c458c8fdc80eee2e17b4fcf464be470a88437442966ba5fa4ac8ed91727b

Observation 25f7555e-1606-48bb-bd07-5e3106850c4d · outbound

This paper cites Sm3-text-to-query: Synthetic multi-model medical text-to-query benchmark.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Sm3-text-to-query: Synthetic multi-model medical text-to-query benchmark

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.295299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.824835Z digest=sha256:7609e73193f7a4ef1f7e956b817b43531ed766d7b4766e863528fd97e23c67aa

Observation 77d03735-fb39-4154-9b88-12af56d59b4e · outbound

This paper cites Elsevier Health Sciences, 2009.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Elsevier Health Sciences, 2009

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.284644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.828137Z digest=sha256:9adff571a1b6a2b23c3c3d31656a18d6d53cf63e4898db914102ab01284b3351

Observation 004d8eb8-31dc-4980-80f7-586b6d45b9f7 · outbound

This paper cites Algorithms for emergency medicine.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Algorithms for emergency medicine

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.273749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.831531Z digest=sha256:782a22aec38cc997cd347e6dfb53dbd6ddd066412969478e639143daf7fb038a

Observation a19e8a24-b35f-4890-9a0d-2676fb522f6a · outbound

This paper cites Elsevier Health Sciences, 2021.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Elsevier Health Sciences, 2021

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.263117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.835133Z digest=sha256:eeea3d9d63080ed225ba0a7cb7c466e96df273f88b44e8324b367d8c2b1597e4

Observation be648ffa-66e1-4d6c-a16a-141a8c6a0ab6 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Gemini: A Family of Highly Capable Multimodal Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.838549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.838549Z digest=sha256:70e448f0e696831a5eb47bdcfd8e5b5a0474e6e34483f0c18f4559b82aee7120

Observation a3b03bf9-d650-4901-8ba4-57d03487093d · outbound

This paper cites Identifying and mitigating vulnerabilities in llm-integrated applications.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Identifying and mitigating vulnerabilities in llm-integrated applications

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.846820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.846820Z digest=sha256:a89e846b94f940cb62fab98d74429367333c51e5258ae56a8b25657b804b4eed

Observation a65f439e-3560-4b63-b5c8-d6969a811296 · outbound

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

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.850141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.850141Z digest=sha256:f36e6da4ae752e71decb80608e3fa56dc460a2346eb72cb3a0f4315825cdd251

Observation 64196f21-aa6a-4a2e-a73c-e87040672d17 · outbound

This paper cites The Llama 3 Herd of Models.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways The Llama 3 Herd of Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.853828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.853828Z digest=sha256:3d078b95cb72b43751004bba94d853c55bd5ce26e0008dc0f622a869d1398e02

Observation 8be1e80f-7373-4fec-b4eb-67e49033dc46 · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Gemma: Open Models Based on Gemini Research and Technology

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.858219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.858219Z digest=sha256:c1ec4fad9d4311fbe48b7368129d643969c7bb696fb0552424342c2126328408

Observation 1e62783e-54b3-4bf0-b112-c0e4a6dbc514 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Gemma 2: Improving Open Language Models at a Practical Size

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.861888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.861888Z digest=sha256:e869679dd5d9f087a0260947c4adf2963c08aa20f6294db20d282a0431107788

Observation 6bb9ea16-76ed-40b5-a0a5-5cdd4076c964 · outbound

This paper cites Gemma 3 Technical Report.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Gemma 3 Technical Report

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.865915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.865915Z digest=sha256:d0fc3a0aa36a2bf3df776b82fb8a7895b19a294663a660588eca21aca8a84b34

Observation 81fe91f4-02b5-4213-949a-93b3d895775d · outbound

This paper cites Qwen2.5 Technical Report.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Qwen2.5 Technical Report

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.869604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.869604Z digest=sha256:bec8ad60a49ee8ad94d3031250cebf646c0ec5cc0bc818d7fea9803fe88a72ef

Observation 8e8e6163-725e-4b11-93f5-c7f8bc6eb09d · outbound

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

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.873050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.873050Z digest=sha256:e079a63d310e60db069928fc97162254d446a54d7ccc103f6678a332502e9279

Observation 8f30269d-5663-4552-88c0-8bf442d3f33c · outbound

This paper cites Phi-4 Technical Report.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Phi-4 Technical Report

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.876647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.876647Z digest=sha256:7dc6b765f71a0b52d773dec8d0ebc7de5838bdfbbb9d681dd286ce30ca6760b6

Observation f597ec7f-287d-422d-b6b2-391fadb5b925 · outbound

This paper cites an unresolved cited work.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Unresolved cited work

Reference 49

Resolution
parse uncertain
raw_fallback, observed 2026-08-05T22:15:10.245758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.881078Z digest=sha256:d6c8596a3f07957d54de1b79f2973b41babf48251cd43ddb3c6b71eab66ff857

Observation caa57769-604f-4579-99b7-3d7793733887 · outbound

This paper cites G-eval: NLG evaluation using gpt-4 with better human alignment.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways G-eval: NLG evaluation using gpt-4 with better human alignment

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.884534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.884534Z digest=sha256:95595ed89ce31d7e4bf59c9eebfc0f1de3766254b5a3db21bd4f0fb94ded8bad

Observation 2db0d703-8dc4-4b5f-abbb-92ba651707cc · outbound

This paper cites M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.888039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.888039Z digest=sha256:69650311a0c07dd54352a120610f3cb6e9a3ca13cea4eea7b946b0aa0fc77ce8

Observation acd0bdbd-b715-4d50-8e51-512b92c7e85a · outbound

This paper cites Lessons learned from the chameleon testbed.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Lessons learned from the chameleon testbed

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.226504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.891666Z digest=sha256:a4ea00f215adf5e8d3c27aac7ef0da26435f2ef3729a7bb1096483f0585b1de9

Observation 1201b530-d759-4a5f-b012-dade49b5e464 · outbound

This paper cites It has to be structured as a decision tree.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways It has to be structured as a decision tree

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.214740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.895173Z digest=sha256:98658bc8d79efbfe6fe64e99d1bf83da5a82c63b7bf978f641e5dac17e721d3c

Observation 82fff41f-ad02-40b5-bb54-4ed8ee4a4fc6 · outbound

This paper cites Make sure that you don’t get ’Invalid control character at line’ errors.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Make sure that you don’t get ’Invalid control character at line’ errors

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.204175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T22:15:09.898848Z digest=sha256:e6abcb58180f2df9a60688958b2aa11e047e2fdfd6da413b275c1cbab9631013

Pith citing papers

Observation d22fee2d-262a-4138-a9fb-54042ea76fdf · inbound

LLM-Orchestrated Conformance Checking in Stroke Care Without Computer-Interpretable Guidelines cites this paper.

LLM-Orchestrated Conformance Checking in Stroke Care Without Computer-Interpretable Guidelines HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-07-03T01:57:32.124810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-27T16:14:18.164403Z digest=sha256:86ef9ccef64dbfebb748da2ebc127a13a8732d33610556b33d782c98bba9de5a