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Paper Citation Record · LEDGER

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment

As of 11 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2501.02869.

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

pith.paper-citation-record.v1
2501.02869 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:05:15.786977Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

37 of 37 outbound references displayed

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  • verified fuzzy4
  • unresolved33
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4330dec0-6b32-4992-a0a6-569db9db295a · outbound

This paper cites URL https://openai.com/blog/chatgpt.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment URL https://openai.com/blog/chatgpt

Reference 1

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:05:15.588983Z digest=sha256:33df6878907d2736d2a96bffa4a0e97dcb89dd0c7b57e1d4deb5adf3f7969189

Observation f513ce6d-a8ba-4ba0-95cc-e1241d06414f · outbound

This paper cites GPT-4 Technical Report.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment GPT-4 Technical Report

Reference 2

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source=pdf_text observed=2026-08-10T22:05:15.594940Z digest=sha256:ddde4842e03fbee640caaabe0b975d9d7a5f603c5ea78bfb7675041da7559a98

Observation 10bbd475-d60b-4b30-9431-50ad9d5dbd46 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment LLaMA: Open and Efficient Foundation Language Models

Reference 3

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Observation 62b6d5c7-9f0d-4e33-8506-c6aee85527ad · outbound

This paper cites BLOOM: A 176B-Parameter Open-Access Multilingual Language Model.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Reference 4

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source=pdf_text observed=2026-08-10T22:05:15.606815Z digest=sha256:ac716aed527b3aa13751b8f971f52f28811d57e7b6175b864c9159b7df610356

Observation aec89d59-8cd0-4493-a8f7-770d9c353347 · outbound

This paper cites The Falcon Series of Open Language Models.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment The Falcon Series of Open Language Models

Reference 5

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source=pdf_text observed=2026-08-10T22:05:15.612850Z digest=sha256:eee69291fc7122c72a5441e4b02a5b83fa538ff3d5a8d2f00b4d55e615097699

Observation 8f5258a6-c76d-4872-aa93-a0b752967ba1 · outbound

This paper cites Efficient and Effective Text Encoding for Chinese LLaMA and Alpaca.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Efficient and Effective Text Encoding for Chinese LLaMA and Alpaca

Reference 6

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source=pdf_text observed=2026-08-10T22:05:15.618917Z digest=sha256:878b093cab17d67484f2ade4125d9aa3bf0dd976c24c96a65ea1fb5ea45e5d32

Observation 37e98863-2295-43a0-a28b-eb742496bffe · outbound

This paper cites Qwen Technical Report.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Qwen Technical Report

Reference 7

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source=pdf_text observed=2026-08-10T22:05:15.626746Z digest=sha256:18dd07282101cd7157545e099afc6036318d5b6cb77cfa7466f42ed88ccc36c8

Observation 82f2840d-b0ee-4bbf-af22-37010e8949a7 · outbound

This paper cites Baichuan 2: Open Large-scale Language Models.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Baichuan 2: Open Large-scale Language Models

Reference 8

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source=pdf_text observed=2026-08-10T22:05:15.633011Z digest=sha256:db65eabebc62bd5d0412b5bb65339392323a63924c7816f0df287e8ad8f4f4b5

Observation 8b89e696-75fd-49d6-91a1-ae2bcca3a28f · outbound

This paper cites A Survey of Large Language Models.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment A Survey of Large Language Models

Reference 9

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source=pdf_text observed=2026-08-10T22:05:15.638885Z digest=sha256:8912e799f260881cfe70f9c4c7c209fc05db29ffc3a4508c8d2865be672c2b35

Observation a66cdc01-4768-4f9c-957c-f8973488ff3f · outbound

This paper cites Singhal, S.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Singhal, S

Reference 10

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source=pdf_text observed=2026-08-10T22:05:15.646379Z digest=sha256:b8c4aaf81ac8897a1db92eb151dc0e773101e114c637178f8e74a20be25faf75

Observation 2cee493c-f207-4add-8c8d-c2e158627ead · outbound

This paper cites DoctorGLM: Fine-tuning your Chinese Doctor is not a Herculean Task.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment DoctorGLM: Fine-tuning your Chinese Doctor is not a Herculean Task

Reference 11

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source=pdf_text observed=2026-08-10T22:05:15.651711Z digest=sha256:98675e2ec8e395afd9232db8809d076f1f97dafc93d00ecc1b760eeb81f938ea

Observation 91c9a53f-e670-4195-b077-3e077abd4a4d · outbound

This paper cites HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledge.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledge

Reference 12

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source=pdf_text observed=2026-08-10T22:05:15.656586Z digest=sha256:3b0a5d5a0b4b87b5431a4cf725b76b84d3a3cb9ba5abf0505418e2f68e3c8895

Observation d41c88eb-b2c3-4bbc-ba39-3b352fd9e937 · outbound

This paper cites HuatuoGPT, towards Taming Language Model to Be a Doctor.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment HuatuoGPT, towards Taming Language Model to Be a Doctor

Reference 13

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source=pdf_text observed=2026-08-10T22:05:15.661886Z digest=sha256:49e007768b566311b29a8368ea7c3008c50c3aef218636a4a15b22b4135af41c

Observation ca7ab5eb-d335-4576-aa34-ae98dc49322c · outbound

This paper cites Zhongjing: Enhancing the Chinese Medical Capabilities of Large Language Model through Expert Feedback and Real-world Multi-turn Dialogue.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Zhongjing: Enhancing the Chinese Medical Capabilities of Large Language Model through Expert Feedback and Real-world Multi-turn Dialogue

Reference 14

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source=pdf_text observed=2026-08-10T22:05:15.667202Z digest=sha256:059eb16a26b169d7ac6fddeb9478c46584a3353d88c2281ace4f0333cd9aef7e

Observation f26aeb8d-c8c7-4ea2-857a-7ca2a5a46bda · outbound

This paper cites Pre-Trained Models: Past, Present and Future.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Pre-Trained Models: Past, Present and Future

Reference 15

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source=pdf_text observed=2026-08-10T22:05:15.672640Z digest=sha256:9e24c5ba736e2ba535c8a940cdc6ec4ebad4e57bb570bfae0a49862eda50a105

Observation 2a0f0594-d25b-434b-bb1a-8751be44968c · outbound

This paper cites LIMA: Less Is More for Alignment.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment LIMA: Less Is More for Alignment

Reference 16

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source=pdf_text observed=2026-08-10T22:05:15.678421Z digest=sha256:7572b99cf0ca2e8f0c984d40de76430576f77c504c86b7e032bc1e8fd37e75e6

Observation b5bf77cf-c4f6-49fd-8fe1-83653676386d · outbound

This paper cites an unresolved cited work.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Unresolved cited work

Reference 17

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source=pdf_text observed=2026-08-10T22:05:15.683833Z digest=sha256:ad70ead1cf7e0e5745d7498314fdaaa4dd2b16852b7a0a5d3ad76d698e3d416d

Observation 64f9c5d7-1d19-4ce2-ad75-234e9349bbf3 · outbound

This paper cites Howard, S.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Howard, S

Reference 18

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source=pdf_text observed=2026-08-10T22:05:15.689604Z digest=sha256:0b81b1dba936eb8ca17561116e270beb6997e16f79c1a2f747d377d5b51b2991

Observation f3faf965-a070-4ebd-9f8d-2dc33691a8e0 · outbound

This paper cites an unresolved cited work.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Unresolved cited work

Reference 19

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source=pdf_text observed=2026-08-10T22:05:15.696005Z digest=sha256:9bfaff67263d6bd4c968e090608d0c09a57580f2542cdd5d6fd321ea7351b685

Observation 7b4d32de-8dfc-451a-9597-8b202ba6d2e7 · outbound

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

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 20

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source=pdf_text observed=2026-08-10T22:05:15.701144Z digest=sha256:643ea0043d9e8065336d133449bccf96b5ec40e6de9c156d0a9b3c3fbbc224f2

Observation e103d313-3241-483b-a258-2dd98de48ed8 · outbound

This paper cites Policy Optimization in RLHF: The Impact of Out-of-preference Data.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Policy Optimization in RLHF: The Impact of Out-of-preference Data

Reference 21

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source=pdf_text observed=2026-08-10T22:05:15.706027Z digest=sha256:a4129f40b925a0f8ac5959ff62b0fd9131e68b29d74be5d588db53e5e4b3a357

Observation 5bd1c7ef-d7cf-41e4-b49a-5474a408c627 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 22

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source=pdf_text observed=2026-08-10T22:05:15.711361Z digest=sha256:b9d76e23c290ecce19c9fec404587da4001bfbd7a79602df1e3f4e89177bff52

Observation d1d7d6be-e960-46e2-a204-14554a4abb8c · outbound

This paper cites Proximal Policy Optimization Algorithms.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Proximal Policy Optimization Algorithms

Reference 23

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Observation 749ee04f-2c0c-445e-bb02-2ed508acb4ad · outbound

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

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 24

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source=pdf_text observed=2026-08-10T22:05:15.721039Z digest=sha256:a4abbf468480bb85ea9fc90e412366e10725d588149de8ba2c25444362d26970

Observation 33c2bc84-eab7-4701-bb11-9e5916ba6190 · outbound

This paper cites Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence

Reference 25

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Observation 156136cb-564c-486c-8640-d818d98ac631 · outbound

This paper cites an unresolved cited work.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Unresolved cited work

Reference 26

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source=pdf_text observed=2026-08-10T22:05:15.730714Z digest=sha256:763b5f6b093fdb28185b92e08abb8529f48e5c89c2d6f781f8616cf580cf5840

Observation c8b1618a-ac7a-41f4-b005-50f8ab124e20 · outbound

This paper cites an unresolved cited work.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Unresolved cited work

Reference 27

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source=pdf_text observed=2026-08-10T22:05:15.735889Z digest=sha256:6560fcbd9df41beb12debfd3f94e8b152c0f22013d12e17baea3e83a448119d0

Observation fa6c3b33-9a3c-4aff-8daa-3bfd76808fcf · outbound

This paper cites MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data

Reference 28

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source=pdf_text observed=2026-08-10T22:05:15.740630Z digest=sha256:f54e4f1dd572189bd900b85904d060eab280dd45beb6557f389f312f346d7cd3

Observation 48604f80-b04d-489e-809c-532d6ddffe4b · outbound

This paper cites ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge

Reference 29

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Observation 2816e9f4-662d-412f-b550-075203237019 · outbound

This paper cites an unresolved cited work.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Unresolved cited work

Reference 30

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Observation f91cbb31-ce5e-47d3-b9d5-39e3a1be8f4f · outbound

This paper cites The Curse of Recursion: Training on Generated Data Makes Models Forget.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment The Curse of Recursion: Training on Generated Data Makes Models Forget

Reference 31

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source=pdf_text observed=2026-08-10T22:05:15.756019Z digest=sha256:1bd921b62dd9e7f295304b8fcd2401f8c115d92baf160151a5ac003c38dbc7c6

Observation e58be108-c895-4cb5-88a1-e0454f62567d · outbound

This paper cites Aghajanyan, A.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Aghajanyan, A

Reference 32

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source=pdf_text observed=2026-08-10T22:05:15.761248Z digest=sha256:ad1f2c838d2b7955436b2798c22f6c2af3936843aa7f9d0f0ead6fbe13fc08fe

Observation 41deca27-fed1-4755-a513-2bf602de1e73 · outbound

This paper cites an unresolved cited work.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Unresolved cited work

Reference 33

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source=pdf_text observed=2026-08-10T22:05:15.766061Z digest=sha256:59d6853f0e7b620a6150c8631db127de43247837dabc3fc460105a8f64abe712

Observation 0e7280e9-f8c4-4aa5-876c-a3c4ad4434bc · outbound

This paper cites Loshchilov, F.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Loshchilov, F

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-10T22:05:16.336312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:05:15.771774Z digest=sha256:da834434ea1fb5485353419cc90050c493a78a3dc501bf11f44e66016dbc2770

Observation b6070f1f-c61a-40a8-84e3-4a581087e07d · outbound

This paper cites Huatuo-26M, a Large-scale Chinese Medical QA Dataset.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Huatuo-26M, a Large-scale Chinese Medical QA Dataset

Reference 35

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source=pdf_text observed=2026-08-10T22:05:15.776787Z digest=sha256:1d9273a76bd8b460eae81bdf2af55ef6bf05a2e4d5018275c314b5a068772e61

Observation 0b3799aa-78a4-450d-84be-64ffd12e4dcc · outbound

This paper cites - Clearly and concisely explain complex medical knowledge.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment - Clearly and concisely explain complex medical knowledge

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-10T22:05:16.318856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:05:15.782109Z digest=sha256:855b6dd7a2fde5451946e4a651502063b3d201c422d64ba2425f8ac6b19a61bb

Observation 4d60b46c-4151-4eda-9bfc-9a88e67765ec · outbound

This paper cites Answer1” relative to “Answer2.

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment Answer1” relative to “Answer2

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:05:16.300084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T22:05:15.786977Z digest=sha256:2e2c6cd0d4be6125903d7022404b7beb3a64592e1332415a959dc52f4d8ee0bc

Pith citing papers

No inbound Pith citation observations are available.