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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:dc19b1713c071f0e3ea70f12af52b0f4cc71d7fe2fbba980d6f08150dc21ac05

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=sha256:06a116dbbd0a5457aa0e8a8c9510107f96ea0fe62a25170d7b9b15f5cde8ee7a

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

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=2026-08-15T22:14:12.383235Z digest=sha256:de8e768e6ebe05c339231118d6df083f3d1a40b204d3c8fcc1d57fc205bf1447

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:d0220d93d43c4900894160572c46e3f7b288c07f8b3d29e9357f704e714c14ea

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:14:12.394143Z digest=sha256:fd64e82db3aea5163a67d86c96755711e8dee8d616e3bb468a347a2677566018

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:da6d57f7c488f4cc8331aae27453e96ffe9e39ca13a5a0b946ef1c2703dd16b3

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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no resolver link, observed 2026-08-15T22:14:12.405794Z

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source=arxiv_source observed=2026-08-15T22:14:12.405794Z digest=sha256:c1646e1715e145845c4195bc767ded0dd917a06811c83156f4d18871bf874fdd

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=sha256:8f63964487be4c1be606334b1c886564e7e3a66e9ce9080ac2893150a949b0f7

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=sha256:54e94e90177837fafeb3130d4fb955cb7eb8663c75049e9db678d3551a636371

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=sha256:072461d233c0b1c82c42eac069839b9191301dc73d65ad77e16b641ec769b525

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.

source=arxiv_source observed=2026-08-15T22:14:12.429640Z digest=sha256:5cdb6a7e2074c5bf118f70ddc6b2b6a85fd6450222b3576104541bfa390e07fa

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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source=arxiv_source observed=2026-08-15T22:14:12.435808Z digest=sha256:2eadfe26e64f3c8c6d0565a8824945c2324487354d975468045352786531c22d

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=sha256:5b6b0c7f1d5c8fe8cd26239ba2e289168f5b4ada9a6f946dd299289703c25af0

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:f8530f20c4072b7c715f99720bb4dab6d10a127b56b4e617a25c6bdcb26493c1

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:c4595e63b22ab5d8575eeae7414b2c1b6cc03de30a0db2828f456433d657796e

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=sha256:86690d130851738bfaf599e01bbcbef2053136b355f7015860cc7346af2516c9

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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raw_fallback, observed 2026-08-15T22:14:14.260149Z

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=sha256:70b0510cd64e28b13bab21a0245591d2e6062401651c5dd8620238ac7a31d3c0

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:da25ffd59a095089c43998302ce34d22c0e955a0bbf31448c8d8114bc22ee1f7

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.

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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:de45755268c18dce9083ff4915bffb3f26cc5fc7a9363c4aea788dcef2c0f751

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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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=sha256:2ad0ba32676d142d31ef99443d31e75ed57b4f6b738127bb953b4dbf35295a28

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:a7d7fbac4bc6417693a31538ddb45de78860a278645e12662f378347b3681127

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.

source=arxiv_source observed=2026-08-15T22:14:12.494251Z digest=sha256:5960c6dd67ce0b650074539f14cf31385602366ed3900c439d7d9ebeeef621f4

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:b272d2335bb85cace7ce7ab7c76446acc2158c29965d0d0f3d28755ce8a82a98

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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source=arxiv_source observed=2026-08-15T22:14:12.515425Z digest=sha256:48874845a1923de5aabd33bc0cfc9bfb1ef1cb4325b26ed84462003409c6d382

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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source=arxiv_source observed=2026-08-15T22:14:12.520934Z digest=sha256:f3e59aa68de5326e911069c718c02dc15f87d771f28c488c846522aebad972ae

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=sha256:6713f56f8078bacb6b18a5b5e491ec64329d7df8b39eda4b91ca257041e3636b

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=sha256:3b5d634404d6121df751b7b4b38d0f1f61ae147ca654f49a890ffdd9f271d7e7

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.

source=arxiv_source observed=2026-08-15T22:14:12.546310Z digest=sha256:95eb6bade466bb553c16193c5823c3b65ac4f937b481c61983eb2d2be5e700d3

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.

source=arxiv_source observed=2026-08-15T22:14:12.560679Z digest=sha256:6783001835debaf984ba7f8491791faa68d12fb8400c5d31abae0f17f572fde8

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

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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=sha256:27c06d7ac5b7bfaa7ae9b9c6a26a8d802efce034db8aefffa9860d08072bd80e

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

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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:d58bd5601e613dc231fed7da6d929774e2d89cddf8b715d627af9f4f1db39d71

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=sha256:331e389c7358e523122c3009e9dc525c72a49357b6d39ac71c339b2a6c0a3f40

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=sha256:515acbb7ec52e310a2fbf72bef5e387c33cdb47fb3e20d499d60c1efa3d54e1b

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

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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=sha256:45cc10e4aee4ba94813dade292ff5dd01d1c4b57bede0c73d0894729e428a497

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=sha256:0592b15d3b0e288a6c7f185dcd408e3011ff84186062ed1d64d331bbdef9f258

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:b6b41bbeeacadc81fd2ea8a9ed3d4ca72e7c372098ba1154bb4e81bf2aebc55d

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:c3a3f940165f0ead52e409b27c43356fa62f0849bfdd6b3aa6b95efe59ba7314

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

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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:ea0904d0ca0cccd6dd730a40c294c33121b5f9e985c9b86df04f6acaf9bacc86

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:ff2a54d84fb4a46b993fffd2423e6f45f9c8e6de6b858ce8749c90fe6290d36b

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

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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=sha256:2f5bb3169965332895b76abba5a84cd2af8e6e18df6ac3a319b8f88d2b3b7a67

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=sha256:93c5607a84c7d198c245237c1782d17ae66da51029afb9b9e232726f0fce7644

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=sha256:97c13de4046a62b01be7b6e5bbecc1fe1143c2a47217eb3e5bd140a4f67d21de

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

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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:f30825dc89a50cbfa3d44747df87d10779b71c517fca02fd4b14c8e7d69b12b9

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=sha256:8b31be749f908a4affe4dd2ff9297ce457ea3ef44850e3b84d4e67417aac2f92

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=sha256:9a29a0d450c612d1c61b7fede074f27d2f2a726172230c0925ba2c4605637ae8

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=sha256:2a27c6b1705f2bbbe760a34a99533f49fe71a014086145b091d82c773b88abe8

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=sha256:3e4ad36c0af41d23b960d0b2a8c1608378fe948c19be428540d3effc667acac3

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=sha256:06c9ef131ee08ca0adef3e46c617783a2e5645d9e42aa5e0fed8e1c1854c7415

Pith citing papers

No inbound Pith citation observations are available.