Paper Citation Record · LEDGER

Baichuan-M2: Scaling Medical Capability with Large Verifier System

As of 22 August 2026, this Paper Citation Record lists 89 of 89 outbound references and 19 inbound Pith citation observations for arXiv:2509.02208.

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

pith.paper-citation-record.v1
2509.02208 v1

Coverage vector

measured 89 of 89 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:50:19.083307Z

measured 108 of 108 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T04:18:55.592670Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

89 of 89 outbound references displayed

verified exact3
verified fuzzy18
unresolved67
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

1
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 24979708-518e-4798-a78a-3f70a03f6983 · outbound

This paper cites Healai: A healthcare LLM for effective medical documentation.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Healai: A healthcare LLM for effective medical documentation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:12.763390Z

Source-reported events for the cited work

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Observation 5bce8608-c23f-4946-aee9-e7e7f242abdc · outbound

This paper cites Evalu- ating the feasibility of chatgpt in healthcare: An analysis of multiple clinical and research scenarios.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Evalu- ating the feasibility of chatgpt in healthcare: An analysis of multiple clinical and research scenarios

Reference 2

Resolution: verified exact; doi, observed 2026-08-05T11:50:19.384234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ad533059-d7ce-4e54-983d-3cfc11361cbc · outbound

This paper cites Intille, Nawar Shara, Guodong Gordon Gao, and Dakuo Wang.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Intille, Nawar Shara, Guodong Gordon Gao, and Dakuo Wang

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:12.997616Z

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Observation 281d21d1-8ff1-4947-b757-d5b19d5a9f99 · outbound

This paper cites Beyond Distillation: Pushing the Limits of Medical LLM Reasoning with Minimalist Rule-Based RL.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Beyond Distillation: Pushing the Limits of Medical LLM Reasoning with Minimalist Rule-Based RL

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:13.102408Z

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Observation a21652f2-81ee-4b2a-a4dc-b801b53c29d8 · outbound

This paper cites HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs.

Baichuan-M2: Scaling Medical Capability with Large Verifier System HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:13.189141Z

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Observation f78ad9d3-60fc-4dcb-b26f-02f267032f48 · outbound

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

Baichuan-M2: Scaling Medical Capability with Large Verifier System DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:13.311583Z

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Observation 26343ddc-6b3b-4e4b-9806-371bc8a10476 · outbound

This paper cites OpenAI o1 System Card.

Baichuan-M2: Scaling Medical Capability with Large Verifier System OpenAI o1 System Card

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:13.395762Z

Source-reported events for the cited work

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Observation 6bb9cf90-41aa-4818-8f50-b1bdc8b5580c · outbound

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

Baichuan-M2: Scaling Medical Capability with Large Verifier System DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:13.454558Z

Source-reported events for the cited work

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Observation 549784d4-6c80-41e7-8d93-d04aa5e7ef6f · outbound

This paper cites Introducing Claude 4.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Introducing Claude 4

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:13.516290Z

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Observation 98dac733-fb5e-4619-aa7b-bf7f5c489e79 · outbound

This paper cites Kimi K2: Open Agentic Intelligence.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Kimi K2: Open Agentic Intelligence

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:13.679725Z

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Observation cb7d076f-c791-4013-81b2-01414f2a797d · outbound

This paper cites GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models.

Baichuan-M2: Scaling Medical Capability with Large Verifier System GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:13.741121Z

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Observation 7154a4ea-d055-4cc3-8ca0-7ca10732b4ad · outbound

This paper cites GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning.

Baichuan-M2: Scaling Medical Capability with Large Verifier System GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning

Reference 12

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Observation 0f1c1aac-32b0-4189-b902-427a6dc349ad · outbound

This paper cites Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:13.938222Z

Source-reported events for the cited work

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Observation 230b740f-c583-461a-b896-b8689cda83f2 · outbound

This paper cites Usmle scoring policies and score reporting guidelines 2024.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Usmle scoring policies and score reporting guidelines 2024

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:13.975076Z

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Observation fd54fb47-100f-4c44-a1d8-7d287e5556a0 · outbound

This paper cites HealthBench: Evaluating Large Language Models Towards Improved Human Health.

Baichuan-M2: Scaling Medical Capability with Large Verifier System HealthBench: Evaluating Large Language Models Towards Improved Human Health

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:14.076576Z

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Observation b16da805-d488-4dfe-94d4-976aa2d2fb04 · outbound

This paper cites Exploring the Inquiry-Diagnosis Relationship with Advanced Patient Simulators.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Exploring the Inquiry-Diagnosis Relationship with Advanced Patient Simulators

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:14.163430Z

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Observation 095a97c0-deb3-4550-a01f-eed63ea80cf9 · outbound

This paper cites Patient safety, what does clinical simulation and teaching innovation contribute? Medicina Intensiva (English Edition) , 49(3): 165–173, 2025.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Patient safety, what does clinical simulation and teaching innovation contribute? Medicina Intensiva (English Edition) , 49(3): 165–173, 2025

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:14.251701Z

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Observation 3d588504-5118-4513-a8ca-2456c35c252e · outbound

This paper cites Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agents.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agents

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:14.313189Z

Source-reported events for the cited work

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Observation 741cb088-7cbe-466e-ab40-c148bfaea9d9 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:14.377597Z

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Observation 8b52a9a5-d438-4ef4-a326-3c27a576172a · outbound

This paper cites Consulting Psychologists Press Palo Alto, CA, 1962.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Consulting Psychologists Press Palo Alto, CA, 1962

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:14.412938Z

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Observation 9f2a1dc4-e9df-4653-8286-8adfe9213afb · outbound

This paper cites Challenges and barriers of using large language models (llm) such as chatgpt for diagnostic medicine with a focus on digital pathology –a recent scoping review.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Challenges and barriers of using large language models (llm) such as chatgpt for diagnostic medicine with a focus on digital pathology –a recent scoping review

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:14.454064Z

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Observation 81c0e777-405c-4d61-a56e-7d64f96d1425 · outbound

This paper cites Baichuan4-Finance Technical Report.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Baichuan4-Finance Technical Report

Reference 22

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Observation 9ece75e4-0c15-45a2-a18b-569fe24f2afc · outbound

This paper cites The learnability of in-context learning.

Baichuan-M2: Scaling Medical Capability with Large Verifier System The learnability of in-context learning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:14.678033Z

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Observation 262a77df-7593-46d2-b169-d8fe64bae7d3 · outbound

This paper cites Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:14.742567Z

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Observation bdba38e9-6362-4081-a957-d3e8d6e4fb15 · outbound

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Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f44404ee-5c10-44a5-ab6e-c51efd405a1d · outbound

This paper cites Baichuan-M1: Pushing the Medical Capability of Large Language Models.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Baichuan-M1: Pushing the Medical Capability of Large Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:14.873675Z

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Observation 00cb921d-a5f9-48cb-bb24-aa308d865a77 · outbound

This paper cites Chi, Quoc V.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Chi, Quoc V

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:14.939950Z

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Observation 896298e2-cb0e-46cb-a409-df7104d0f0de · outbound

This paper cites Large language models are zero-shot reasoners.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Large language models are zero-shot reasoners

Reference 28

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Observation b4a382c0-e9cb-45c3-a207-f2d3ca0d444d · outbound

This paper cites When More is Less: Understanding Chain-of-Thought Length in LLMs.

Baichuan-M2: Scaling Medical Capability with Large Verifier System When More is Less: Understanding Chain-of-Thought Length in LLMs

Reference 29

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Observation 21170959-4026-4494-8926-3aa2e986e2c9 · outbound

This paper cites Baichuan alignment technical report.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Baichuan alignment technical report

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:15.224367Z

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Observation a1fe6eab-15f0-40f5-8929-c23d0836a5bd · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

Baichuan-M2: Scaling Medical Capability with Large Verifier System DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 31

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Source-reported events for the cited work

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Observation 895457da-205c-49d4-83ab-5b83db5c3284 · outbound

This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Understanding R1-Zero-Like Training: A Critical Perspective

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:15.430867Z

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Observation 50e93acf-8bf6-4d3f-9015-31108d5e5ade · outbound

This paper cites AIME problems and solutions, 2025.

Baichuan-M2: Scaling Medical Capability with Large Verifier System AIME problems and solutions, 2025

Reference 33

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Observation 902d103b-129b-4ca7-955a-454f89c18586 · outbound

This paper cites SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines.

Baichuan-M2: Scaling Medical Capability with Large Verifier System SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

Reference 34

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Observation ec37ee3b-aa83-4d9b-ae94-b346913cabbb · outbound

This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Understanding R1-Zero-Like Training: A Critical Perspective

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:15.550691Z

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Observation b6326af1-e0f9-4191-a4e2-04bd455e6ecc · outbound

This paper cites Reinforcement Learning with Rubric Anchors.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Reinforcement Learning with Rubric Anchors

Reference 36

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Observation 53d96970-d5c3-4493-a872-35f66a92d696 · outbound

This paper cites Fast on the Easy, Deep on the Hard: Efficient Reasoning via Powered Length Penalty.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Fast on the Easy, Deep on the Hard: Efficient Reasoning via Powered Length Penalty

Reference 37

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Observation 8e34f5fd-6db8-4e54-b2c2-4a3708ce024e · outbound

This paper cites MedxpertQA: Benchmarking expert-level medical reasoning and understanding.

Baichuan-M2: Scaling Medical Capability with Large Verifier System MedxpertQA: Benchmarking expert-level medical reasoning and understanding

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.937671Z

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Observation 5168069c-7628-421c-8ec0-018423182eef · outbound

This paper cites Qwen3 Technical Report.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Qwen3 Technical Report

Reference 39

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Observation 40b80bde-f71d-4b54-a488-f3d134731a30 · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:16.438285Z

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Observation 466f95ac-15c9-42fd-8d4e-9166aa94374e · outbound

This paper cites Fast on the Easy, Deep on the Hard: Efficient Reasoning via Powered Length Penalty.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Fast on the Easy, Deep on the Hard: Efficient Reasoning via Powered Length Penalty

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:16.038483Z

Source-reported events for the cited work

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Observation 710dffae-eb7e-4ccd-aa68-efaefdbfccab · outbound

This paper cites gpt-oss-120b & gpt-oss-20b Model Card.

Baichuan-M2: Scaling Medical Capability with Large Verifier System gpt-oss-120b & gpt-oss-20b Model Card

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:16.139219Z

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Observation d6fb6c37-593f-41ed-9d42-74e73f74a884 · outbound

This paper cites From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline.

Baichuan-M2: Scaling Medical Capability with Large Verifier System From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:16.737789Z

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Observation 68c81129-65d4-4435-84bb-b5a4437f53a1 · outbound

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Baichuan-M2: Scaling Medical Capability with Large Verifier System Qwen3 Technical Report

Reference 44

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This paper cites Writingbench: A comprehensive benchmark for generative writing.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Writingbench: A comprehensive benchmark for generative writing

Reference 45

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Observation 42c9d9d4-19e9-4c1b-b36d-7b5529f69c8b · outbound

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Baichuan-M2: Scaling Medical Capability with Large Verifier System Instruction-Following Evaluation for Large Language Models

Reference 46

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Observation 038a7a73-ab74-4a8a-be10-f02b5f2c83e7 · outbound

This paper cites Cfbench: A comprehensive constraints-following benchmark for llms.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Cfbench: A comprehensive constraints-following benchmark for llms

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.929925Z

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Observation 244e99c5-ead7-401c-b5af-6ddd2cd47410 · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

Baichuan-M2: Scaling Medical Capability with Large Verifier System GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 48

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Observation 0da3c65d-f398-42be-95b8-8af8e54dca14 · outbound

This paper cites Alignbench: Benchmarking chinese alignment of large language models.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Alignbench: Benchmarking chinese alignment of large language models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:16.845299Z

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Observation 6a84d74b-fbb8-4dae-aa8c-263719338f2e · outbound

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Baichuan-M2: Scaling Medical Capability with Large Verifier System Gonzalez, Clark W

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.907144Z

Source-reported events for the cited work

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Observation d2b8d6a8-9675-4af6-a2e8-5cc3222dd2a1 · outbound

This paper cites Optimize weight rounding via signed gradient descent for the quantization of llms.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Optimize weight rounding via signed gradient descent for the quantization of llms

Reference 51

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Observation 7d52f9e5-2098-4261-b083-cf727c4e6675 · outbound

This paper cites Croci, Bo Li, Pashmina Cameron, Martin Jaggi, Dan Alistarh, Torsten Hoefler, and James Hensman.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Croci, Bo Li, Pashmina Cameron, Martin Jaggi, Dan Alistarh, Torsten Hoefler, and James Hensman

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.915208Z

Source-reported events for the cited work

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Observation c1ec7b89-61ca-468c-aee0-8311e69a110e · outbound

This paper cites QQQ: Quality Quattuor-Bit Quantization for Large Language Models.

Baichuan-M2: Scaling Medical Capability with Large Verifier System QQQ: Quality Quattuor-Bit Quantization for Large Language Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:17.356679Z

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Observation c71ad65c-b768-4cc2-9b97-95be30e984da · outbound

This paper cites Efficient memory management for large language model serving with pagedattention.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Efficient memory management for large language model serving with pagedattention

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:17.580558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55d65e17-311d-41a0-a63b-35c9765e5141 · outbound

This paper cites EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test.

Baichuan-M2: Scaling Medical Capability with Large Verifier System EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:17.736862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abc7a0c1-7290-47e0-8e16-edcf0784d485 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.899866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 34d06bc4-6be2-457e-a981-851b530addde · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.892858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cf3658a5-21f5-4124-b416-291dcfee46e6 · outbound

This paper cites If postprandial values are also elevated, basal alone may be insufficient.

Baichuan-M2: Scaling Medical Capability with Large Verifier System If postprandial values are also elevated, basal alone may be insufficient

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.885839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 44fdeee0-2a32-4201-b8f4-c59199125764 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 61

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.877937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cc9df853-1b86-4c60-a200-b630eefb72f6 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.870834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e70db02e-38e5-4d5e-babb-976cc2529045 · outbound

This paper cites Non-compliance or inadequate carb control can drive hyperglycemia.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Non-compliance or inadequate carb control can drive hyperglycemia

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.863801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3d7df16c-73dd-4f62-ba5b-07e050b5f11b · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.856623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation efd1273e-029d-44f9-bbd4-2863ea805486 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 65

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.849739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7f6800fa-e05b-4294-8829-0cdda9972e8f · outbound

This paper cites 3.ACOG Recommendations (Practice Bulletin #190):.

Baichuan-M2: Scaling Medical Capability with Large Verifier System 3.ACOG Recommendations (Practice Bulletin #190):

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.841873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c7c483ff-15ba-49fb-a5cc-9b7f201571f9 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.834496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4d61be3f-fa2b-45c4-b685-9c31d6539414 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.827275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 07823370-810a-4e92-b556-8350fcc0dc0b · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 69

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.819843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4c1c45bb-eec7-4d57-95af-f749fa6828c5 · outbound

This paper cites 2.Adding prandial insulin (rapid-acting) for meals if postprandial values are elevated.

Baichuan-M2: Scaling Medical Capability with Large Verifier System 2.Adding prandial insulin (rapid-acting) for meals if postprandial values are elevated

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.812427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 98512c81-3afd-4746-ae55-eca95e4bf836 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 71

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.805025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ac87c827-4e34-43b7-b52a-a17e67ae67a6 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 72

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.798172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 299f031c-b2ca-4933-ae35-4589f9756c54 · outbound

This paper cites 1.When to Escalate:.

Baichuan-M2: Scaling Medical Capability with Large Verifier System 1.When to Escalate:

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.790989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d9891814-92fa-497d-b19c-858fbd4260c4 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.783829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fde7b452-869b-4bab-bf9a-c0d644f65b00 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 75

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.776853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 86e6620a-cbf5-4c77-b7d8-86a13c698088 · outbound

This paper cites 2.Documentation & Follow-up:.

Baichuan-M2: Scaling Medical Capability with Large Verifier System 2.Documentation & Follow-up:

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.769681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f861be0d-9dbf-4773-bbcf-9ef49bdbb373 · outbound

This paper cites Per ACOG, intensification indicated.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Per ACOG, intensification indicated

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.761933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a93f0dd3-dee0-4032-8867-faf687084445 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.754745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 146b943f-6755-49ab-a063-3e5694b53c69 · outbound

This paper cites Recommended Action Plan: 1.Immediate:.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Recommended Action Plan: 1.Immediate:

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.747307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7ea18a21-8ece-450e-9f07-4fba5388f32f · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 80

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.739628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 68e15f28-09cd-4ddf-bbcf-0369f29c6ebf · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 81

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.732350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation db80a0ae-af15-4db5-9c22-9b91254e5483 · outbound

This paper cites 2.Within 72 hours:.

Baichuan-M2: Scaling Medical Capability with Large Verifier System 2.Within 72 hours:

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.724223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5497a754-6a9c-4986-b05d-eb02a1e49354 · outbound

This paper cites If fasting >95, consider: 1.19-20 units basal (if no hypoglycemia).

Baichuan-M2: Scaling Medical Capability with Large Verifier System If fasting >95, consider: 1.19-20 units basal (if no hypoglycemia)

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.715643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d4aec08a-6eba-477f-aafa-233c4c9933b7 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 84

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.707535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 875d90f8-54bd-4f98-8e07-bad74b185a35 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 85

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.699367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fc062fd1-9acd-47c8-8d52-ae77284fb5e3 · outbound

This paper cites Key References: • ACOG Practice Bulletin #190 (Gestational Diabetes) • ADA Standards of Care (2023): Recommend fasting <95 mg/dL in pregnancy.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Key References: • ACOG Practice Bulletin #190 (Gestational Diabetes) • ADA Standards of Care (2023): Recommend fasting <95 mg/dL in pregnancy

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.691542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 27cf5832-1408-4cd7-bf39-c1127feefca2 · outbound

This paper cites Intensify.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Intensify

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.683004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a299969b-24b9-4b75-b5ce-87fd06dd5593 · outbound

This paper cites increase glargine from 16U to 18 U at 2200 h.

Baichuan-M2: Scaling Medical Capability with Large Verifier System increase glargine from 16U to 18 U at 2200 h

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:50:19.674905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b9ffcfe7-f668-48c8-a0a8-7b58e70f140c · outbound

This paper cites intensify if >95 mg/dL.

Baichuan-M2: Scaling Medical Capability with Large Verifier System intensify if >95 mg/dL

Reference 89

Resolution: malformed identifier; raw_fallback, observed 2026-08-05T11:50:19.666491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d9dc5629-bdfd-411d-a914-69327c496d48 · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 2024

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:50:19.952862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b24336b7-e3cf-45d2-a9f9-60df263be16f · outbound

This paper cites an unresolved cited work.

Baichuan-M2: Scaling Medical Capability with Large Verifier System Unresolved cited work

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-05T11:50:13.599272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 19727f15-e47d-4c6b-afdc-72752efb4678 · inbound

Active Learning for Neurosymbolic Program Synthesis cites this paper.

Active Learning for Neurosymbolic Program Synthesis Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T17:44:10.546431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b1b4a45-8a4c-4989-b4da-b0429d4f275f · inbound

A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.

A Survey of Reinforcement Learning for Large Reasoning Models Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 221

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:02:24.493624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 294d778f-1817-420d-8322-4c8adf78cb60 · inbound

InfiMed-ORBIT: Aligning LLMs on Open-Ended Complex Tasks via Rubric-Based Incremental Training cites this paper.

InfiMed-ORBIT: Aligning LLMs on Open-Ended Complex Tasks via Rubric-Based Incremental Training Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T09:22:42.521571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c89f3527-3ba1-40a4-bec6-fdd0d241e1c3 · inbound

LingxiDiagBench: A Multi-Agent Framework for Benchmarking LLMs in Chinese Psychiatric Consultation and Diagnosis cites this paper.

LingxiDiagBench: A Multi-Agent Framework for Benchmarking LLMs in Chinese Psychiatric Consultation and Diagnosis Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T03:03:32.529115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3886d9f-27d5-4a22-a415-1a017ad6e87f · inbound

OpenHospital: A Thing-in-itself Arena for Evolving and Benchmarking LLM-based Collective Intelligence cites this paper.

OpenHospital: A Thing-in-itself Arena for Evolving and Benchmarking LLM-based Collective Intelligence Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-14T21:00:05.911327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30d7b698-163d-4beb-b5ae-a52eac667876 · inbound

Medical Reasoning with Large Language Models: A Survey and MR-Bench cites this paper.

Medical Reasoning with Large Language Models: A Survey and MR-Bench Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-15T10:25:26.685602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b20e84ba-0c36-4ab6-8986-ac0e5de0585f · inbound

C-MIG: Multi-view Information Gain-based Retrieval-Augmented Generation for Clinical Diagnosis Reasoning cites this paper.

C-MIG: Multi-view Information Gain-based Retrieval-Augmented Generation for Clinical Diagnosis Reasoning Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T12:53:26.969670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 83f28583-5287-4e11-87ec-e9895301155e · inbound

C-MIG: Multi-view Information Gain-based Retrieval-Augmented Generation for Clinical Diagnosis Reasoning cites this paper.

C-MIG: Multi-view Information Gain-based Retrieval-Augmented Generation for Clinical Diagnosis Reasoning Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-04T05:01:11.041894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec2535b0-eebb-4ab0-bc89-b3bf1a8ff89b · inbound

ClinicalMC: A Benchmark for Multi-Course Clinical Decision-Making with Large Language Models cites this paper.

ClinicalMC: A Benchmark for Multi-Course Clinical Decision-Making with Large Language Models Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 52

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T03:06:30.546723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e637af4d-c33d-46ff-a8f1-3ef2650f8b49 · inbound

Baichuan-M4: A Clinical-Grade Medical Agent System for Continuous Care cites this paper.

Baichuan-M4: A Clinical-Grade Medical Agent System for Continuous Care Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-06-27T17:01:07.429612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7a1a4475-00ba-4923-93f2-cb177d501fe9 · inbound

Experience Makes Skillful: Enabling Generalizable Medical Agent Reasoning via Self-Evolving Skill Memory cites this paper.

Experience Makes Skillful: Enabling Generalizable Medical Agent Reasoning via Self-Evolving Skill Memory Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-03T01:07:30.863552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8ee5de2b-4605-4e01-a80e-ca640a0276be · inbound

Lung-R1: A Knowledge Graph-Guided LLM for Pulmonary Diagnostic Reasoning cites this paper.

Lung-R1: A Knowledge Graph-Guided LLM for Pulmonary Diagnostic Reasoning Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 53

Resolution: metadata mismatch; arxiv_id, observed 2026-06-27T10:10:48.534305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2c3dd505-5d2b-4c2d-a051-a105facf921f · inbound

UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQA cites this paper.

UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQA Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 274

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T09:47:59.555375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 925ef9de-c4ac-4023-b388-9ff4deba2b27 · inbound

Latent-CURE for Breast Cancer Diagnosis cites this paper.

Latent-CURE for Breast Cancer Diagnosis Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-06-30T06:14:19.187577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f8fb91ba-b703-4407-882b-16ea43c3656f · inbound

MentalHospital: A Virtual Environment for Evaluating Psychiatric Clinical Encounters cites this paper.

MentalHospital: A Virtual Environment for Evaluating Psychiatric Clinical Encounters Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-07-10T10:37:01.657661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6729289e-bb4e-4519-bbbc-eefd0fb9086e · inbound

MedRealMM: A Real-World Multimodal Benchmark for Chinese Online Medical Consultation cites this paper.

MedRealMM: A Real-World Multimodal Benchmark for Chinese Online Medical Consultation Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 60

Resolution: unresolved; no resolver link, observed 2026-07-13T05:07:42.040673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43ace38b-6942-4848-ac4b-abb59379089c · inbound

MedRealMM: A Real-World Multimodal Benchmark for Chinese Online Medical Consultation cites this paper.

MedRealMM: A Real-World Multimodal Benchmark for Chinese Online Medical Consultation Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-02T07:43:33.938358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fef35df8-38f7-41c8-a470-47e5fa783496 · inbound

MedDDC-Eval: Diagnosis-Decoupled Evaluation of Multi-Turn Medical Consultation Agents cites this paper.

MedDDC-Eval: Diagnosis-Decoupled Evaluation of Multi-Turn Medical Consultation Agents Baichuan-M2: Scaling Medical Capability with Large Verifier System

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T13:50:41.481667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Evaluating Counterfactual Sensitivity to Patient Information in Medication-Safety Reasoning Baichuan-M2: Scaling Medical Capability with Large Verifier System

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