Paper Citation Record · LEDGER

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models

As of 9 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2602.18481.

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

pith.paper-citation-record.v1
2602.18481 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T02:44:08.758916Z

measured 34 of 34 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

34 of 34 outbound references displayed

verified exact0
verified fuzzy0
unresolved34
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b0812d55-f753-4046-9ea0-0e381415541c · outbound

This paper cites Finqa: A dataset of numerical reasoning over financial data.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Finqa: A dataset of numerical reasoning over financial data

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:05.582245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cd0d8aa-ee54-48ef-b60b-3b29c037708d · outbound

This paper cites TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:05.697941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66904b42-a271-423a-9ab9-9fc897c66736 · outbound

This paper cites ConvFinQA: Exploring the Chain of Numerical Reasoning in Conversational Finance Question Answering.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models ConvFinQA: Exploring the Chain of Numerical Reasoning in Conversational Finance Question Answering

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:05.867024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e44bb75-736b-4eb0-8432-266681f8b2ca · outbound

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

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models BloombergGPT: A Large Language Model for Finance

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:05.991095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0dd2e07-19ea-49f4-8ee1-6f3f67626372 · outbound

This paper cites FinGPT: Democratizing Internet-scale Data for Financial Large Language Models.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models FinGPT: Democratizing Internet-scale Data for Financial Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:06.137083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd4ed727-80d0-472b-879b-70f78bae9698 · outbound

This paper cites Pixiu: A comprehensive benchmark, instruction dataset and large language model for finance.Advances in Neural Information Processing Systems, 36:33469–33484, 2023.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Pixiu: A comprehensive benchmark, instruction dataset and large language model for finance.Advances in Neural Information Processing Systems, 36:33469–33484, 2023

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:06.238724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 492cbb36-17ba-4464-a0ec-d3d6563ce676 · outbound

This paper cites Finben: A holistic financial benchmark for large language models.Advances in Neural Information Processing Systems, 37:95716–95743, 2024.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Finben: A holistic financial benchmark for large language models.Advances in Neural Information Processing Systems, 37:95716–95743, 2024

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:06.362497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07a2e252-ee15-4c45-a8ba-aa8e1560ed87 · outbound

This paper cites Ai trading in real markets, 2026.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Ai trading in real markets, 2026

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:06.522805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9317503-4e02-48cd-9bc8-92f1aaf4c481 · outbound

This paper cites Fintextqa: A dataset for long-form financial question answering.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Fintextqa: A dataset for long-form financial question answering

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:06.669703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d44e0c3-bf8a-401f-80a0-f231444efbb2 · outbound

This paper cites Cfinbench: A comprehensive chinese financial benchmark for large language models.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Cfinbench: A comprehensive chinese financial benchmark for large language models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:06.753930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40502498-bae6-4b0e-a696-af2b772ce986 · outbound

This paper cites Fin-eva version 1.0: A chinese financial evaluation benchmark for large language models, 2025.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Fin-eva version 1.0: A chinese financial evaluation benchmark for large language models, 2025

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:06.874481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0147cbd5-4d7a-4036-a6d4-2a44d7e4a59c · outbound

This paper cites Ucfe: A user-centric financial expertise benchmark for large language models.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Ucfe: A user-centric financial expertise benchmark for large language models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:07.019460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c8b0b80-55d3-4dda-8914-7f6bdab3df46 · outbound

This paper cites an unresolved cited work.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:07.106304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffc08876-4477-4d3f-8879-0fdf22e3f47b · outbound

This paper cites Stockbench: Can llm agents trade stocks profitably in real-world markets?arXiv preprint arXiv:2510.02209, 2025.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Stockbench: Can llm agents trade stocks profitably in real-world markets?arXiv preprint arXiv:2510.02209, 2025

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:07.162419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b66d146-fa78-41ce-bda9-b42d5b6d1030 · outbound

This paper cites Can chatgpt forecast stock price movements? return predictability and large language models.arXiv preprint arXiv:2304.07619, 2023.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Can chatgpt forecast stock price movements? return predictability and large language models.arXiv preprint arXiv:2304.07619, 2023

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:07.229645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e178ece9-3097-41c5-bb6c-4a764f64e514 · outbound

This paper cites The Wall Street Neophyte: A Zero-Shot Analysis of ChatGPT Over MultiModal Stock Movement Prediction Challenges.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models The Wall Street Neophyte: A Zero-Shot Analysis of ChatGPT Over MultiModal Stock Movement Prediction Challenges

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:07.300849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b846f76a-6b64-4e39-87c8-21a4efec2624 · outbound

This paper cites Investorbench: A benchmark for financial decision-making tasks with llm-based agent.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Investorbench: A benchmark for financial decision-making tasks with llm-based agent

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:07.360921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 489bf3cf-e9a6-4c90-aebb-70e4b0b88100 · outbound

This paper cites Time travel is cheating: Going live with deepfund for real-time fund investment benchmarking.arXiv preprint arXiv:2505.11065, 2025.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Time travel is cheating: Going live with deepfund for real-time fund investment benchmarking.arXiv preprint arXiv:2505.11065, 2025

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:07.446248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 196c64bf-89fb-413e-b28c-2b56b81bc7d9 · outbound

This paper cites FutureX: An Advanced Live Benchmark for LLM Agents in Future Prediction.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models FutureX: An Advanced Live Benchmark for LLM Agents in Future Prediction

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:07.502114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82585ab6-0f13-4c0b-925d-d184c9a9054a · outbound

This paper cites Prophet arena: Live llm trading competition platform, 2025.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Prophet arena: Live llm trading competition platform, 2025

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:07.548788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e19e99d-f9a8-4330-b530-bbaa38210e2c · outbound

This paper cites Rockalpha: Llm-powered quantitative trading platform, 2025.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Rockalpha: Llm-powered quantitative trading platform, 2025

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:07.598923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ecd2a3f-133a-402d-bd54-6c89a014d2f6 · outbound

This paper cites Livetradebench: Seeking real-world alpha with large language models.arXiv preprint arXiv:2511.03628, 2025.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Livetradebench: Seeking real-world alpha with large language models.arXiv preprint arXiv:2511.03628, 2025

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:07.643930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32671425-aa86-448f-8cbc-fb29fadd9da5 · outbound

This paper cites Worldquant: Quantitative research platform.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Worldquant: Quantitative research platform

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:07.715015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82089f9b-b122-40e4-a4da-d7c42cb0f4c2 · outbound

This paper cites Joinquant: Quantitative research platform.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Joinquant: Quantitative research platform

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:07.914752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 464abaca-9544-4368-bb67-e144b7258f15 · outbound

This paper cites Qlib: An AI-oriented Quantitative Investment Platform.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Qlib: An AI-oriented Quantitative Investment Platform

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:08.000177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3d9cb15-5124-4e36-ae20-fb5636d9b2a8 · outbound

This paper cites Openfe: Automated feature generation with expert-level performance.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Openfe: Automated feature generation with expert-level performance

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:08.126594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c97c6e6-6780-4609-9006-597acf630081 · outbound

This paper cites Www’18 open challenge: financial opinion mining and question answering.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models Www’18 open challenge: financial opinion mining and question answering

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:08.234961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ab82573-c8b4-4ff3-98cd-54f87c614e1f · outbound

This paper cites most reasonable.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models most reasonable

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:08.357051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79ba0c93-5c2b-4e9a-8174-a58cf36a91e6 · outbound

This paper cites ema_{period}.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models ema_{period}

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:08.407766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccc1fc51-0f0c-4dae-8799-98613a528b34 · outbound

This paper cites std_{period}.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models std_{period}

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:08.494563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e60bf56c-c639-4a40-a2be-0c02f0a4178e · outbound

This paper cites max_{period}.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models max_{period}

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:08.542718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1811b103-936f-43e1-81b9-db227f8f9ba0 · outbound

This paper cites klow2"] •kmid2: Body Ratio (normalized by candle range). Measures body direction relative to candle range. Formula:kmid2 = (close - open) / (high - low)| Scale: -1 to 1 | Usage:df[.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models klow2"] •kmid2: Body Ratio (normalized by candle range). Measures body direction relative to candle range. Formula:kmid2 = (close - open) / (high - low)| Scale: -1 to 1 | Usage:df[

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:08.607132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df1d04c5-e08f-40e1-86b3-75027eb3e3fa · outbound

This paper cites vma_{period}.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models vma_{period}

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:08.680755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 513501b5-b9c3-4d9d-beae-a083a8e250b9 · outbound

This paper cites cntp_{period}.

AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models cntp_{period}

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T02:44:08.758916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.