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Paper Citation Record · LEDGER

AQuA: Recursively Self-Improving Quantitative Trading Research Agents

As of 16 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2608.12841.

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

pith.paper-citation-record.v1
2608.12841 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:14:12.659861Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

55 of 55 outbound references displayed

  • verified exact16
  • verified fuzzy5
  • unresolved29
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3836d9d5-9928-4fa1-a341-058b17ed44fc · outbound

This paper cites Proceedings of the 32nd International Conference on Machine Learning , series =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Proceedings of the 32nd International Conference on Machine Learning , series =

Reference 1

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raw_fallback, observed 2026-08-15T22:14:14.333081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.367925Z digest=sha256:6e68b0f4ba26c979282977af470f70d3ced8e62962d7c265170f17ad542b8198

Observation 35bf828a-ff72-41b6-ac1f-8ae196e2bdcc · outbound

This paper cites 2024 , doi =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents 2024 , doi =

Reference 2

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raw_fallback, observed 2026-08-15T22:14:14.314458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.376610Z digest=sha256:a38f62baeb159cb501aaf3ba2a9bdd253bf1d9e9c5877724fb87c0b5ecc9b90c

Observation 6c085224-c4c6-42d3-b6fa-f453adec84cd · outbound

This paper cites 2025 , doi =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents 2025 , doi =

Reference 3

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raw_fallback, observed 2026-08-15T22:14:14.296321Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.383235Z digest=sha256:0577e611e3e9b521acacbefc320aac376061c99927767fba0b7ad4f4ed062f18

Observation 072ebc16-3b10-4948-92cf-5eae400b8035 · outbound

This paper cites 2026 , doi =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents 2026 , doi =

Reference 4

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raw_fallback, observed 2026-08-15T22:14:14.279109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.389067Z digest=sha256:d69a02a0d57868b94bd3655c8d4e5f4c90e0f59b24f2ecc3e242874c3b15eb32

Observation fa62b863-8fc0-4ae7-9484-eae986c4c6d9 · outbound

This paper cites The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

Reference 5

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source=arxiv_source observed=2026-08-15T22:14:12.394143Z digest=sha256:8112e77e35187bc1e52a55e834e81fbfd4b5891e77a232c393d9e3a0b779174a

Observation 0a1fa2b4-bba2-4e10-bf32-9399cbd7d921 · outbound

This paper cites QuantaAlpha: An Evolutionary Framework for LLM-Driven Alpha Mining.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents QuantaAlpha: An Evolutionary Framework for LLM-Driven Alpha Mining

Reference 6

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source=arxiv_source observed=2026-08-15T22:14:12.400037Z digest=sha256:390e4fae5142a718ebe61f185afb3446f6bae333e2cf084ec9e63db9a1670e32

Observation 15071457-af5a-40e9-b571-41fe5cf554a5 · outbound

This paper cites DeepLOB: Deep Convolutional Neural Networks for Limit Order Books.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents DeepLOB: Deep Convolutional Neural Networks for Limit Order Books

Reference 7

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source=arxiv_source observed=2026-08-15T22:14:12.405794Z digest=sha256:0cf4664a4b78cb642044d8d1a9493afb0d113e06b2274e0b4feb3393ddae42c3

Observation a267b815-0df6-422e-bdd8-a04b973116b7 · outbound

This paper cites 101 Formulaic Alphas.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents 101 Formulaic Alphas

Reference 8

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source=arxiv_source observed=2026-08-15T22:14:12.411508Z digest=sha256:327b9d2c3cae2c6431fbead3e0d081471ba3d9cfb247e9d69558b5da297b02eb

Observation 9f3cbceb-e021-452f-91b5-2bfb1acc1c72 · outbound

This paper cites AutoAlpha: an Efficient Hierarchical Evolutionary Algorithm for Mining Alpha Factors in Quantitative Investment.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents AutoAlpha: an Efficient Hierarchical Evolutionary Algorithm for Mining Alpha Factors in Quantitative Investment

Reference 9

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source=arxiv_source observed=2026-08-15T22:14:12.418198Z digest=sha256:5407f2c4cd6ef01d7bba7c25e9b7120ca078adf25d9644259036c08da7c37adb

Observation 6c3e2308-4210-46a5-8b50-e97b855da29b · outbound

This paper cites doi:10.1145/3448016.3457324 , booktitle =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents doi:10.1145/3448016.3457324 , booktitle =

Reference 10

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source=arxiv_source observed=2026-08-15T22:14:12.423941Z digest=sha256:46ef6c9f5ab8ffbd47ed1e2207ec73043b51055d4685504092402b5a287a2dc1

Observation ba93d070-1d42-4f41-84e3-e4457e7efe2f · outbound

This paper cites Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning

Reference 11

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verified exact
local_arxiv, observed 2026-08-15T22:14:13.676139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 55523763-2469-4fb9-9c78-8c96547b0495 · outbound

This paper cites Notices of the American Mathematical Society , author =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Notices of the American Mathematical Society , author =

Reference 12

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Unavailable: canonical work link unavailable.

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Observation db95d1f0-3d0b-4a45-82b6-8ddf0cc8e1d8 · outbound

This paper cites The probability of backtest overfitting , issn =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents The probability of backtest overfitting , issn =

Reference 13

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source=arxiv_source observed=2026-08-15T22:14:12.441374Z digest=sha256:508b67d5dbe16bec4de9cb7a178578456a2e04cc06202704e725948e753dd3dd

Observation 24f3455d-5c5d-4cef-83b1-a610b7ac80db · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 14

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source=arxiv_source observed=2026-08-15T22:14:12.446841Z digest=sha256:138de26cfd711c253deca43f88ce9a083d2758d3e37f287db2754c5d95ec2ad5

Observation 9fe47032-a48b-4cb9-bf8f-1f149be559d0 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 15

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source=arxiv_source observed=2026-08-15T22:14:12.452184Z digest=sha256:8df29e462b903c4c45b50de68191790e9e48622c167ea9a90890d167e822bacc

Observation c29da2a7-0179-4240-a8ad-c4d7a88b6914 · outbound

This paper cites Attention Is All You Need.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Attention Is All You Need

Reference 16

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source=arxiv_source observed=2026-08-15T22:14:12.458285Z digest=sha256:794437208cd583fdff18e4c5086039683d5d1baa8dd2171a35dfe62f94f628cc

Observation 9f06d17a-6522-4a87-85d8-e02118126828 · outbound

This paper cites 2026 , note=.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents 2026 , note=

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.463927Z digest=sha256:ba5c63aab34fd18e0e96a9e3773a3ab15f8119c230b7d57efdd131bc5efe60ee

Observation c406d12f-7297-4e9f-bf5e-8bd389289761 · outbound

This paper cites an unresolved cited work.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Unresolved cited work

Reference 18

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.469058Z digest=sha256:f0324adf4db6cd1019eb4bdd7a15b98b6f77e20b9afe92647ada55a344082870

Observation a6b20f78-e387-46db-ab2d-762efb84edfa · outbound

This paper cites FactorEngine: A Program-level Knowledge-Infused Factor Mining Framework for Quantitative Investment.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents FactorEngine: A Program-level Knowledge-Infused Factor Mining Framework for Quantitative Investment

Reference 19

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local_arxiv, observed 2026-08-15T22:14:13.571232Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.474284Z digest=sha256:1681189eb754e17c195638acda599ab905459f39df532ae292f113b17b018939

Observation 33f23523-7f58-4d28-ac8f-4a86c5ba941d · outbound

This paper cites doi:10.48550/arXiv.2602.11917 , publisher =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents doi:10.48550/arXiv.2602.11917 , publisher =

Reference 20

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verified exact
doi, observed 2026-08-15T22:14:13.546160Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.479612Z digest=sha256:8e333a49eeab37d6630ea617994fa04feb6681de2908043b0ae147863978904b

Observation 4789eb68-466a-477d-b124-72f4450b00d3 · outbound

This paper cites doi:10.48550/arXiv.2602.14670 , publisher =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents doi:10.48550/arXiv.2602.14670 , publisher =

Reference 21

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verified exact
doi, observed 2026-08-15T22:14:13.475936Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.484337Z digest=sha256:99e60241b877d1c5c91cb2beab50f8392daf384e25a24f22c508abc2d7f49662

Observation 808702c7-fbe9-4c83-8e97-03f6aaa41ea7 · outbound

This paper cites Hubble: An LLM-Driven Agentic Framework for Safe, Diverse, and Reproducible Alpha Factor Discovery.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Hubble: An LLM-Driven Agentic Framework for Safe, Diverse, and Reproducible Alpha Factor Discovery

Reference 22

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source=arxiv_source observed=2026-08-15T22:14:12.489250Z digest=sha256:babe2d6494ab40ed6b5fc6cf161035b3ef56967b75a452acc44b7aa6fa9f4f73

Observation 7a882c17-af19-4237-8172-9e472a5a1e30 · outbound

This paper cites doi:10.48550/arXiv.2603.20247 , publisher =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents doi:10.48550/arXiv.2603.20247 , publisher =

Reference 23

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doi, observed 2026-08-15T22:14:13.367987Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation cadb4b47-bd3f-49a0-abdf-512131dca573 · outbound

This paper cites AlphaMemo: Structured Search-Process Memory for Self-Evolving Alpha Mining Agents.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents AlphaMemo: Structured Search-Process Memory for Self-Evolving Alpha Mining Agents

Reference 24

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local_arxiv, observed 2026-08-15T22:14:13.289202Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.499122Z digest=sha256:641d5b0221da1cfec779e6a1b59e06cf43c90c7d2e34bf8680b793008cf6d295

Observation 015d67b1-8258-4a82-9c8d-b4c900f82cc0 · outbound

This paper cites From Feedback Loops to Policy Updates: Reinforcement Fine-Tuning for LLM-Based Alpha Factor Discovery.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents From Feedback Loops to Policy Updates: Reinforcement Fine-Tuning for LLM-Based Alpha Factor Discovery

Reference 25

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Observation c3597b02-9ac4-4644-b6d6-e99f730db957 · outbound

This paper cites The Review of Financial Studies , author =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents The Review of Financial Studies , author =

Reference 26

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Observation 6b2ee9b7-6d9a-403f-bb0b-6a84f13555b0 · outbound

This paper cites Review of Financial Studies , author =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Review of Financial Studies , author =

Reference 27

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Observation 9cdcdbf1-c361-453b-9eec-6e2fdc855b39 · outbound

This paper cites Neural Computation , author =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Neural Computation , author =

Reference 28

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Observation 3892daeb-f099-412d-b8a6-913ee0c3224c · outbound

This paper cites Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Reference 29

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source=arxiv_source observed=2026-08-15T22:14:12.526222Z digest=sha256:34c094cdb835d3858c7873cdf552429a5b705bedd50f4e48c12e49a6a5cad889

Observation e8bb3a87-b249-4f1d-8152-66c9e1dd1797 · outbound

This paper cites xLSTM: Extended Long Short-Term Memory.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents xLSTM: Extended Long Short-Term Memory

Reference 30

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Observation cfa2fffe-74a7-4b6d-b8de-f0e7bd3dd106 · outbound

This paper cites Nature , author =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Nature , author =

Reference 31

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source=arxiv_source observed=2026-08-15T22:14:12.536438Z digest=sha256:f8e7fec74d934eed1459a9014878f3087e06c21d255f93e22cbee3f3ffeb72b5

Observation 0d8ffd47-0c27-460e-89c6-a4b99ebcda35 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , author =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Proceedings of the AAAI Conference on Artificial Intelligence , author =

Reference 32

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Observation da9519b8-da6b-4ec1-96e6-bab16a9096e4 · outbound

This paper cites doi:10.1109/TSP.2025.3576781 , journal =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents doi:10.1109/TSP.2025.3576781 , journal =

Reference 33

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raw_fallback, observed 2026-08-15T22:14:14.152791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 8cec9f00-195e-4c07-85ae-92613e985770 · outbound

This paper cites doi:10.1145/3711896.3736838 , booktitle =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents doi:10.1145/3711896.3736838 , booktitle =

Reference 34

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Observation f2963326-4e1a-435a-b6ad-dbc238843dfb · outbound

This paper cites doi:10.1109/ICASSP55912.2026.11463591 , booktitle =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents doi:10.1109/ICASSP55912.2026.11463591 , booktitle =

Reference 35

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Observation 16e344b9-db74-4b9b-b6e1-891b97ce3345 · outbound

This paper cites Chain-of-.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Chain-of-

Reference 36

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verified exact
doi, observed 2026-08-15T22:14:13.146654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation d5ae5aa8-89a5-4b2e-8b39-d3168c06a680 · outbound

This paper cites Learning from Expert Factors: Trajectory-level Reward Shaping for Formulaic Alpha Mining.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Learning from Expert Factors: Trajectory-level Reward Shaping for Formulaic Alpha Mining

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-15T22:14:12.565598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:14:12.565598Z digest=sha256:18fb519ea5bab222324ab43529cf8308f1b9258a9da53a18999ad69efa01b50d

Observation 7947d7c5-620c-4569-81c3-e74f78061549 · outbound

This paper cites an unresolved cited work.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Unresolved cited work

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-15T22:14:12.570758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:14:12.570758Z digest=sha256:e51e2419468077f5850d4166d9691cf7b1cdbff373bae9619dba8eeaa21328d3

Observation de4667c3-b4ab-4419-b9ed-8e8782d6dfe1 · outbound

This paper cites Exploring the.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Exploring the

Reference 39

Resolution
verified exact
doi, observed 2026-08-15T22:14:13.046766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.575667Z digest=sha256:5a4101e2896cd384d67e2b82fc2a92f48a377fae23f05398e7fb04e6b9752208

Observation 34dc652f-95d9-4628-819b-f1420d2b6165 · outbound

This paper cites EurekAgent: Agent Environment Engineering is All You Need For Autonomous Scientific Discovery.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents EurekAgent: Agent Environment Engineering is All You Need For Autonomous Scientific Discovery

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T22:14:12.581033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:14:12.581033Z digest=sha256:245d396c9462c6215cd538b2aba912f8d467906030f0c7c52cdef45602169911

Observation 593f3293-0684-4276-a0ac-6121c85e01bd · outbound

This paper cites Autonomous Agents for Scientific Discovery: Orchestrating Scientists, Language, Code, and Physics.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Autonomous Agents for Scientific Discovery: Orchestrating Scientists, Language, Code, and Physics

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T22:14:12.586921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:14:12.586921Z digest=sha256:2cff6add415d76515e0e37ce861b24bb18d78351dd1c077eb8c6fd5026c3df7c

Observation a2076432-6327-4359-a214-6c6b1530c1bd · outbound

This paper cites an unresolved cited work.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Unresolved cited work

Reference 42

Resolution
verified exact
doi, observed 2026-08-15T22:14:12.925073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.592150Z digest=sha256:3d57bd17c6f6843f9b248d5da9647b1798bf36343ec85b8e1d9df6c8ff0ac361

Observation 4c99400c-bfc3-4b91-a9d5-0e49ebb16001 · outbound

This paper cites doi:10.2139/ssrn.5580590 , author =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents doi:10.2139/ssrn.5580590 , author =

Reference 43

Resolution
verified exact
doi, observed 2026-08-15T22:14:12.908152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.597470Z digest=sha256:718de3562437c7727850797bc1974af206d57d593e43080d2256dc017e8e45d8

Observation 2e8ef099-a137-4db1-b340-70ff491162af · outbound

This paper cites 2025 , pages =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents 2025 , pages =

Reference 44

Resolution
verified exact
doi, observed 2026-08-15T22:14:12.891013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.602121Z digest=sha256:a3befc836efcbd4b7b225183f09edfc48b4860f3d8085af01bfd3eecd7f94a37

Observation ed9cf89d-bbed-4ba5-8810-19131f44a7d4 · outbound

This paper cites Journal of Risk and Financial Management , author =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Journal of Risk and Financial Management , author =

Reference 45

Resolution
verified exact
doi, observed 2026-08-15T22:14:12.873487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.607069Z digest=sha256:5b38de875a341f4755bca2cb3ecfae7595259c8229f11a779db8f26a185b32cd

Observation 2de136e1-1108-4d3d-a3d5-d462d63f1228 · outbound

This paper cites Forecasting , author =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Forecasting , author =

Reference 46

Resolution
verified exact
doi, observed 2026-08-15T22:14:12.856331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.612520Z digest=sha256:3067dc79b87ba235e7bfd89f01ab894799888bcc15c78ebba08bc9c21733e402

Observation 56b713c3-efb2-4261-9b6a-b49580d304d6 · outbound

This paper cites Deep learning and machine learning models for portfolio optimization:.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Deep learning and machine learning models for portfolio optimization:

Reference 47

Resolution
metadata mismatch
raw_fallback, observed 2026-08-15T22:14:13.864885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.617426Z digest=sha256:3141eacb8c4cdf9ae3737d8979d72101a452d6c83a7b022605b933aa78eb8060

Observation e5907b98-5ba0-4b9b-87f3-3cf4cd4e5170 · outbound

This paper cites Enhancing.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Enhancing

Reference 48

Resolution
verified exact
doi, observed 2026-08-15T22:14:12.837772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.622670Z digest=sha256:f37f9262654707a919950719e41491857b0d4ee0c1f4eb930eee0bcec6d4ee74

Observation ac622067-03ad-4331-84c6-c5061bd72e3b · outbound

This paper cites doi:10.2139/ssrn.6085266 , author =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents doi:10.2139/ssrn.6085266 , author =

Reference 49

Resolution
verified exact
doi, observed 2026-08-15T22:14:12.819427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.629062Z digest=sha256:2cd4aafd19dd4484260d3c862bb3a2a2e16a7ebd1b18c472a3d906f5eb591648

Observation ff0169e4-9d6d-4b7c-abe3-189b4f733872 · outbound

This paper cites doi:10.2139/ssrn.5166656 , author =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents doi:10.2139/ssrn.5166656 , author =

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-15T22:14:12.634320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:14:12.634320Z digest=sha256:3f88defbdc857df042a420edcc1b49626ddea77329db799f66c8477b536c2c59

Observation 28619646-db8a-4185-bd68-76bc781c00c6 · outbound

This paper cites doi:10.2139/ssrn.6906675 , author =.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents doi:10.2139/ssrn.6906675 , author =

Reference 51

Resolution
verified exact
doi, observed 2026-08-15T22:14:12.791477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.639469Z digest=sha256:b9313a40d02df9170b780a1a4923c5c5f65d544f8e06b7692a6c1e9416e63563

Observation cbcf93c7-94fd-4576-a2ed-47fd140c5273 · outbound

This paper cites From Hypotheses to Factors: Constrained LLM Agents in Cryptocurrency Markets.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents From Hypotheses to Factors: Constrained LLM Agents in Cryptocurrency Markets

Reference 52

Resolution
verified exact
local_arxiv, observed 2026-08-15T22:14:12.774905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.644224Z digest=sha256:cb5ab333b398bdfc81f25dcd501e54cfd01353f91a3b8c23269a83642920d17a

Observation 87d6f0ba-0f46-4e69-bb9e-afee8e37ca2e · outbound

This paper cites AlphaSchema: Exploring the Space of Trading Semantics for LLM-Based Alpha Mining.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents AlphaSchema: Exploring the Space of Trading Semantics for LLM-Based Alpha Mining

Reference 53

Resolution
metadata mismatch
local_arxiv, observed 2026-08-15T22:14:12.751205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.649482Z digest=sha256:3212910d9ee997c8ecab2647b0efd66c908b861069fbbade99b49177718ff959

Observation bcca0885-d8d6-4cb8-9798-13b2c0896a81 · outbound

This paper cites Cognitive Alpha Mining via LLM-Driven Code-Based Evolution.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Cognitive Alpha Mining via LLM-Driven Code-Based Evolution

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-15T22:14:12.654762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:14:12.654762Z digest=sha256:f85adff2053e1cce41052dd01b511f6895a39ab54fa9c6d3b8f3590e507fd544

Observation 644d1471-d813-4323-9535-260af9191680 · outbound

This paper cites Towards Autonomous Formulaic Alpha Discovery: An Evolutionary Computation Perspective.

AQuA: Recursively Self-Improving Quantitative Trading Research Agents Towards Autonomous Formulaic Alpha Discovery: An Evolutionary Computation Perspective

Reference 55

Resolution
verified exact
local_arxiv, observed 2026-08-15T22:14:12.708626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.659861Z digest=sha256:80c1b1838d6391c9fec00488de3754c20d9f479be6edf80f78291708ea6f5cde

Pith citing papers

No inbound Pith citation observations are available.