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Paper Citation Record · LEDGER

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching

As of 9 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2507.04099.

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

pith.paper-citation-record.v1
2507.04099 v2

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:01:45.923680Z

measured 17 of 17 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 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

17 of 17 outbound references displayed

  • verified exact2
  • verified fuzzy5
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e67e7342-26c5-4827-bb62-2a5ace367e72 · outbound

This paper cites Towards Democratization of Subspeciality Medical Expertise.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching Towards Democratization of Subspeciality Medical Expertise

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-06T20:01:46.567450Z

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=2026-08-06T20:01:43.960781Z digest=sha256:af70f8dd2e995a6870d287d1281669d5b8c09a979486668a45d25edb533e03c4

Observation 755229fb-6832-44f3-b0d3-e2e37aee6581 · outbound

This paper cites Fine Tuning Large Language Models for Medicine: The Role and Importance of Direct Preference Optimization.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching Fine Tuning Large Language Models for Medicine: The Role and Importance of Direct Preference Optimization

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T20:01:44.023672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:01:44.023672Z digest=sha256:49bd84e1337a1bcb99b583d193d8235c91c9e5d7dcfa8e2f9a9b927193454a66

Observation dc603ba7-f9ce-4f01-a310-20f742650006 · outbound

This paper cites an unresolved cited work.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:01:47.717253Z

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=2026-08-06T20:01:44.093173Z digest=sha256:9f7f424ed46795ae19d20e361c235cb340dac2ab3846fde4aa757be926473c64

Observation 001eb42d-6342-44f7-b695-ca61cdeaabe2 · outbound

This paper cites JMLR: Joint Medical LLM and Retrieval Training for Enhancing Reasoning and Professional Question Answering Capability.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching JMLR: Joint Medical LLM and Retrieval Training for Enhancing Reasoning and Professional Question Answering Capability

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T20:01:44.210006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:01:44.210006Z digest=sha256:9c877fd3d94676d7cf3077b4909a0809c605e5825628b7a668049768a0be7c79

Observation 08eda640-9124-4153-80d1-664381f8a5f0 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T20:01:44.337724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:01:44.337724Z digest=sha256:1c2df556d12ab59b3b0f584e5ec014d9bdf129a5a28151bafe814c51301e9686

Observation 44f05754-39d1-4135-b491-3e1a231fddd4 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching Proximal Policy Optimization Algorithms

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T20:01:44.392416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:01:44.392416Z digest=sha256:20e2e38315be654c8d30d0457296c01b95a966172d48c2fe3c9bd492b86b296d

Observation 2f22cf46-d81d-41b4-970a-9f0f0a2984a6 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T20:01:44.443750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:01:44.443750Z digest=sha256:d3ba891f1a8519586ff83bbc363cb6c26d1ac497a9702f77a84fd8ee5d8b6078

Observation 4175c59e-8224-4ff4-8289-4b7226c494a5 · outbound

This paper cites Beyond Single-Turn: A Survey on Multi-Turn Interactions with Large Language Models.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching Beyond Single-Turn: A Survey on Multi-Turn Interactions with Large Language Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T20:01:44.587262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:01:44.587262Z digest=sha256:d77f921cdb90c9195e64bf590f0f261c462da29d5fa2a1e6a0e9a20f8eef49e3

Observation 8cddbe88-51a7-4687-93c1-08f27c024484 · outbound

This paper cites US Elsevier Health https://www.us.elsevierhealth.com/the-medical-interview-9780323052214.html.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching US Elsevier Health https://www.us.elsevierhealth.com/the-medical-interview-9780323052214.html

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:01:47.521488Z

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=2026-08-06T20:01:44.728062Z digest=sha256:38ca62c3268f016f42b9035207220341b74cc5bdac59998bef5c3dff1485adc1

Observation 30747c74-d84d-467a-9eb6-4bfd4d8e3087 · outbound

This paper cites Learning to branch with Tree MDPs.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching Learning to branch with Tree MDPs

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-06T20:01:46.229114Z

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=2026-08-06T20:01:44.927157Z digest=sha256:f71e62f5b257dff5c216112080ea38356af8e5e5e48f50f056625bafbd458ae6

Observation 026835ad-b87a-48a7-bc24-21fdf1d75606 · outbound

This paper cites & Chen, W.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching & Chen, W

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:01:47.376195Z

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=2026-08-06T20:01:45.110846Z digest=sha256:ba238bd842b81e2e3fd39572bb2f35e01879d60c671c4c4c25550dcc1a6c080a

Observation 1f0dc4f4-f5e2-4c7e-91bb-808ff5e823e3 · outbound

This paper cites SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T20:01:45.270627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:01:45.270627Z digest=sha256:693186d43e74d6334d5ea07a8933fe877b182374077afbc5cc77358c9cb48deb

Observation 6f65453d-6c5f-4325-88c5-f393af758795 · outbound

This paper cites What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T20:01:45.385242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:01:45.385242Z digest=sha256:5199bccecb7e4200a34213a25170c7fea9c0fe202ac9b16429042ca5c9cd0299

Observation ebbb0cb5-17b1-49c8-a137-50e113bd89c1 · outbound

This paper cites https://huggingface.co/meta-llama/Llama- 3.1-8B-Instruct (2024).

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching https://huggingface.co/meta-llama/Llama- 3.1-8B-Instruct (2024)

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:01:47.227192Z

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=2026-08-06T20:01:45.509959Z digest=sha256:b7712e0aca55fb45dffc32943922f7986bb54b9af56e08bc6fda5803ad0eb033

Observation b78a7175-7309-4e5a-8c6a-c9a4a95c9504 · outbound

This paper cites https://huggingface.co/mistralai/Ministral- 8B-Instruct-2410.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching https://huggingface.co/mistralai/Ministral- 8B-Instruct-2410

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:01:46.997475Z

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=2026-08-06T20:01:45.651039Z digest=sha256:efe31add23c2955362b555bdc7914186ebcfbec9cec779e509e1dd8c29a8a642

Observation 7612c144-f160-4fce-a610-0097b64df3a8 · outbound

This paper cites https://platform.openai.com.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching https://platform.openai.com

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:01:46.812795Z

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=2026-08-06T20:01:45.773828Z digest=sha256:dd24b5be6bb6483be6efae6f8b8bc120db965b3dfb1a51afc20462e982bfaae2

Observation 0a3e0925-f9e2-44ff-8887-5c85b88b41fb · outbound

This paper cites A Diversity-Promoting Objective Function for Neural Conversation Models.

Conversation Forests: The Key to Fine Tuning Large Language Models for Multi-Turn Medical Conversations is Branching A Diversity-Promoting Objective Function for Neural Conversation Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T20:01:45.923680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:01:45.923680Z digest=sha256:355cf8ff3bd648b9b0aa46ecdec1cd0e25da3ce697f90cecd1734c3ed2dcded9

Pith citing papers

No inbound Pith citation observations are available.