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Paper Citation Record · LEDGER

Baichuan4-Finance Technical Report

As of 22 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 5 inbound Pith citation observations for arXiv:2412.15270.

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

pith.paper-citation-record.v1
2412.15270 v2

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:55:19.114542Z

measured 30 of 30 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:41:29.467512Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T05:30:23.456663Z

Reference resolution

25 of 25 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved24
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

1
pith, observed 2026-08-10T05:30:23.456663Z

Outbound references

Observation c2c1ee5d-a595-4c02-926d-9f393dc1b6bb · outbound

This paper cites GPT-4 Technical Report.

Baichuan4-Finance Technical Report GPT-4 Technical Report

Reference 1

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source=pdf_text observed=2026-08-11T13:55:18.960763Z digest=sha256:c7776da7baa33942508be4dc7b7697d6f166f46502c75ba8d59b155ad72121f7

Observation 186a5634-0cef-4771-a894-df85986163e0 · outbound

This paper cites Qwen Technical Report.

Baichuan4-Finance Technical Report Qwen Technical Report

Reference 3

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source=pdf_text observed=2026-08-11T13:55:18.972375Z digest=sha256:aa7d2dc65f038ef87e7b29e02971fd878763649957c8cc7204241c7fd116e886

Observation f4a9eecc-30db-4d0b-8f2e-f75cb762623d · outbound

This paper cites On the resemblance and containment of documents.

Baichuan4-Finance Technical Report On the resemblance and containment of documents

Reference 4

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source=pdf_text observed=2026-08-11T13:55:18.978580Z digest=sha256:00be9b77c3f470cb51dfcd73332e9082b694bef9af0cd54ac3b3a47f10ed0a40

Observation e9ef2381-69d5-47e4-b313-5a9aada75ef8 · outbound

This paper cites The Llama 3 Herd of Models.

Baichuan4-Finance Technical Report The Llama 3 Herd of Models

Reference 8

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source=pdf_text observed=2026-08-11T13:55:19.008034Z digest=sha256:074c44b4862be42fb192a9e316716ee21e6ecb39f4837f212f0c172cbe9e770b

Observation 93b4b6a1-1779-4de4-a738-d4e8976473d0 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Baichuan4-Finance Technical Report Measuring Massive Multitask Language Understanding

Reference 9

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source=pdf_text observed=2026-08-11T13:55:19.014055Z digest=sha256:782c7aad468748916747adbc690347129adecf10d37f55b89d0f21087b6756ed

Observation 940660b8-ec88-4703-b959-ce81e4e0be19 · outbound

This paper cites Mistral 7B.

Baichuan4-Finance Technical Report Mistral 7B

Reference 10

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source=pdf_text observed=2026-08-11T13:55:19.020680Z digest=sha256:c0f556580156c753b082c2ad265ec303e8c68f38e90f2cbf626e36fd8997bbf8

Observation ac93dcc6-ec76-4c8e-9e20-f03e1600b80d · outbound

This paper cites A Survey of Large Language Models in Finance (FinLLMs).

Baichuan4-Finance Technical Report A Survey of Large Language Models in Finance (FinLLMs)

Reference 11

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source=pdf_text observed=2026-08-11T13:55:19.026761Z digest=sha256:703f6d0a348e31b3713531327dd98b13c1cef5e0480da24aa734388a4b4f9232

Observation 1502058d-32f0-4178-9466-6719eed70cae · outbound

This paper cites Boosting Deductive Reasoning with Step Signals In RLHF.

Baichuan4-Finance Technical Report Boosting Deductive Reasoning with Step Signals In RLHF

Reference 12

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source=pdf_text observed=2026-08-11T13:55:19.033130Z digest=sha256:e247df45ce6d7e12aad48f36478d424420d015a8b4d5570c678f8af0bd539d10

Observation 26a9386f-8354-4243-ae5c-958a4b9bec42 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Baichuan4-Finance Technical Report Proximal Policy Optimization Algorithms

Reference 14

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source=pdf_text observed=2026-08-11T13:55:19.047669Z digest=sha256:bb704e32224761b618e27894d93f1cbf1665864331b710f98cbb53f04c32de8e

Observation 67606a6a-413e-41bb-9d6e-84ef5c270a41 · outbound

This paper cites org/10.1016/j.

Baichuan4-Finance Technical Report org/10.1016/j

Reference 16

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source=pdf_text observed=2026-08-11T13:55:19.060203Z digest=sha256:c3227ce4d5a899c51ed29238a93d2a1562a6c3b46b22ba03963b58dc4ea405b1

Observation 905b3d50-ed04-43dd-b9da-a921352b9968 · outbound

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

Baichuan4-Finance Technical Report Gemini: A Family of Highly Capable Multimodal Models

Reference 17

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source=pdf_text observed=2026-08-11T13:55:19.066705Z digest=sha256:9398a51ef483045cf9ccd63df47b3c674fea6c7a0d987454216b442f39b24627

Observation 29ed667b-ce15-4de1-8cf5-db021cfba89a · outbound

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

Baichuan4-Finance Technical Report Gemma: Open Models Based on Gemini Research and Technology

Reference 18

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source=pdf_text observed=2026-08-11T13:55:19.071790Z digest=sha256:10b686b099fd6ce1eba0d3e10e602e6cc4e3bb76d1853bd7191104259b5c6629

Observation d6bce222-b2e3-4756-9fd8-549bc665bf85 · outbound

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

Baichuan4-Finance Technical Report LLaMA: Open and Efficient Foundation Language Models

Reference 19

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source=pdf_text observed=2026-08-11T13:55:19.079771Z digest=sha256:f6cea56f9b993670c1f6324f866e22db376fdd8310af702ba72ac2da21dde0d0

Observation f0f86c2e-9aa8-4529-9ead-a9db61458b52 · outbound

This paper cites PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance.

Baichuan4-Finance Technical Report PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance

Reference 22

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source=pdf_text observed=2026-08-11T13:55:19.098397Z digest=sha256:fd9f265670ca98b2e97fd0ede1237c69e9d0375b517dd54de07eeea163518fab

Observation 127c338a-825f-433d-9939-9d844b6dc90d · outbound

This paper cites Reward-Robust RLHF in LLMs.

Baichuan4-Finance Technical Report Reward-Robust RLHF in LLMs

Reference 23

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source=pdf_text observed=2026-08-11T13:55:19.103768Z digest=sha256:d6e25289bde1c6be5bae321922116566db87baa6614e68f59cc37e67c639bc39

Observation bd4ad5b1-409c-4e5f-b15b-109b5826ae69 · outbound

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

Baichuan4-Finance Technical Report Baichuan 2: Open Large-scale Language Models

Reference 24

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source=pdf_text observed=2026-08-11T13:55:19.109632Z digest=sha256:d320ad38f19aaf40949ddb9322cfb0265e7d79fbbda08e12cc4bac5f616aaebd

Observation f5113d73-dbbe-44ce-94c8-f306f9bda44e · outbound

This paper cites Fingpt: Open-source financial large language models.

Baichuan4-Finance Technical Report Fingpt: Open-source financial large language models

Reference 25

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source=pdf_text observed=2026-08-11T13:55:19.114542Z digest=sha256:dd39f755e3aa87fda34ef859eec633028ba70655eeefdfff5fb6a2b2fa6e0335

Observation ac5887a3-e18c-48ca-9282-580337b2fdc3 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Baichuan4-Finance Technical Report Evaluating Large Language Models Trained on Code

Reference 1997

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source=pdf_text observed=2026-08-11T13:55:18.985708Z digest=sha256:d877706a73129685bd6d5d82b29e40be075dff65bf76279a1fa994a3226244b7

Observation 5a8fc72b-e15b-4776-9181-875c1376d5e3 · outbound

This paper cites WHEN FLUE MEETS FLANG: Benchmarks and Large Pre-trained Language Model for Financial Domain.

Baichuan4-Finance Technical Report WHEN FLUE MEETS FLANG: Benchmarks and Large Pre-trained Language Model for Financial Domain

Reference 2017

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source=pdf_text observed=2026-08-11T13:55:19.053942Z digest=sha256:25a447a4e43ae57d89879fe87b608140e53069669990cb72d1a1bdda63bf7db4

Observation 6dc57b94-5027-49a9-9ddd-0a6a58681c77 · outbound

This paper cites BloombergGPT: A Large Language Model for Finance.

Baichuan4-Finance Technical Report BloombergGPT: A Large Language Model for Finance

Reference 2019

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source=pdf_text observed=2026-08-11T13:55:19.093047Z digest=sha256:c3e23e4f2b072e6850d8fe8951c6be6775fec9ab0536cb425c4bb11a5c7ef022

Observation db617fec-61af-448a-b437-7bd0e86d5623 · outbound

This paper cites CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data.

Baichuan4-Finance Technical Report CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 2020

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source=pdf_text observed=2026-08-11T13:55:19.086184Z digest=sha256:cd19ee749b216f954ffd749a165093c55dbb2e2ec10077d94690ef0b7f53b9f0

Observation 3c59e556-0d9a-4a8f-b406-5d98264c8fbe · outbound

This paper cites Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference.

Baichuan4-Finance Technical Report Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference

Reference 2021

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source=pdf_text observed=2026-08-11T13:55:18.992506Z digest=sha256:4802d0c551ee10ab4fe898333d272954a88d5b7f602f26b3987a0dfc4b6f68db

Observation a4ed6e2b-fd56-4eb8-b3a0-032ec82e8204 · outbound

This paper cites D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models.

Baichuan4-Finance Technical Report D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models

Reference 2022

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source=pdf_text observed=2026-08-11T13:55:19.039774Z digest=sha256:382317f9d69162796abb7cf7000f0ca95e211e825e6db59d10c56e6f460bdc70

Observation 07691379-05fd-4db0-85fb-de3922ef097c · outbound

This paper cites GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints.

Baichuan4-Finance Technical Report GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints

Reference 2023

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source=pdf_text observed=2026-08-11T13:55:18.967077Z digest=sha256:912f1a87951b824a07f01b30c7d99c9798db793112c11aaad519e0b98feeac78

Observation 033b03ca-aff1-41c5-a1cf-0ef6135ed001 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Baichuan4-Finance Technical Report Training Verifiers to Solve Math Word Problems

Reference 2024

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source=pdf_text observed=2026-08-11T13:55:18.999939Z digest=sha256:698fe588a0132e0ca720bb1c04e174a18739dda868166bb139a05c4b2a6781ab

Pith citing papers

Observation 64780c40-da07-49b7-9e1e-21d071822b50 · inbound

FinMaster: A Holistic Benchmark for Mastering Full-Pipeline Financial Workflows with LLMs cites this paper.

FinMaster: A Holistic Benchmark for Mastering Full-Pipeline Financial Workflows with LLMs Baichuan4-Finance Technical Report

Reference 25

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source=pdf_text observed=2026-08-15T20:41:29.467512Z digest=sha256:549f2d6d6d6feea674ef663f7a86be4f987bf14d663ff8eb84a6635171c79a20

Observation f5784ce9-745f-4753-ba6d-ce8acd40f066 · inbound

RiverEcho: Real-Time Interactive Digital System for Ancient Yellow River Culture cites this paper.

RiverEcho: Real-Time Interactive Digital System for Ancient Yellow River Culture Baichuan4-Finance Technical Report

Reference 13

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source=pdf_text observed=2026-08-06T22:20:12.834247Z digest=sha256:44102322f43165e7e2a38a32ebf2e61ebfc8592ef72c196c1dea4811decf8132

Observation 98e7686d-812c-45a5-97e9-fe968d4f5823 · inbound

Agentar-Fin-R1: Enhancing Financial Intelligence through Domain Expertise, Training Efficiency, and Advanced Reasoning cites this paper.

Agentar-Fin-R1: Enhancing Financial Intelligence through Domain Expertise, Training Efficiency, and Advanced Reasoning Baichuan4-Finance Technical Report

Reference 30

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source=pdf_text observed=2026-08-06T15:07:39.872807Z digest=sha256:341db5188567389fe7a0fca2c3656268e0a63687264ec400c2bafa3571caf1f0

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

Baichuan-M2: Scaling Medical Capability with Large Verifier System cites this paper.

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

Reference 22

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local_arxiv, observed 2026-08-05T11:50:19.252968Z

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

source=pdf_text observed=2026-08-05T11:50:14.555136Z digest=sha256:f31920f4d6ff659734787f2bd5bfaa141f544746f2dcc3d04271ea5b32e841c0

Observation 5acaca72-960c-4d91-bf02-7062b6e316ed · inbound

MedCollab: IBIS-Guided Multi-Agent Collaboration with Hierarchical Disease Relation Chains for Clinical Diagnosis cites this paper.

MedCollab: IBIS-Guided Multi-Agent Collaboration with Hierarchical Disease Relation Chains for Clinical Diagnosis Baichuan4-Finance Technical Report

Reference 28

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source=pdf_text observed=2026-08-02T19:47:39.172007Z digest=sha256:e30e15a6b6aa3cfa9e1ff790ab4f34094ea70ef54a982fe16f954b3e5d38f7bf