Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T14:58:09.302540Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 1 inbound Pith citation observation for arXiv:2507.17211.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T14:58:09.302540Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-29T16:55:21.649886Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T17:03:41.278033Z
13 of 13 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 31cc2d36-7f32-46d5-a8bf-8f2ba2d7076b · outbound
EFS: Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models Unresolved cited work
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d4622d9b-5f13-4732-8513-e886ac575ca3 · outbound
EFS: Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models Unresolved cited work
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 25e4ca4f-07f1-4745-932c-b51eca6dda4b · outbound
EFS: Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models Unresolved cited work
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 74c0a857-9597-44c0-9d63-a34399d5aa7f · outbound
EFS: Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models Unresolved cited work
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 3fb5c133-1d10-4856-bacf-3980a4f561a8 · outbound
EFS: Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models ACTION SPACE:
Reference 5
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 44e16aa6-395a-48d8-81a4-d6a695fdeb6e · outbound
EFS: Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models Unresolved cited work
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 82a65d5f-0f93-4596-97af-a64e9637606e · outbound
EFS: Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models Unresolved cited work
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation dddbb1da-b306-4d37-83ea-7cd4c4136b2a · outbound
EFS: Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models Unresolved cited work
Reference 10
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation bd784b1c-846a-44e6-b82c-c3821ecc4d0a · outbound
EFS: Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models def test run avg(*args, **kwargs):\n a=np.array(prices) \n if a: \n print(a) \n return np.mean(kwargs[’prices’]) \n
Reference 11
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 91c4a757-a8d1-4e2e-afd0-6c4d89b1ad70 · outbound
EFS: Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models Tanh norm converts deviations to [0,1) range: Values near 0 → Price hovering near EMA (no momentum) Values approaching 1 → Strong directional breakout
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 3356262d-d0b3-4177-9f57-58926c73aad4 · outbound
EFS: Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models Unresolved cited work
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 83a5b873-9a3f-49ef-955e-25c5422ef5ca · outbound
EFS: Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models Qlib: An AI-oriented Quantitative Investment Platform
Reference 2024
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0823f3e7-a483-4047-add9-d461e375d1a7 · outbound
EFS: Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models To reduce potential bias caused by the overall underperformance of the Hong Kong market before mid-2024, we randomly select and add 15 large-cap blue-chip stocks from the HSI index
Reference 2025
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation cbf331bb-1d06-4a36-a2cd-e02d53e641f6 · inbound
AlphaMemo: Structured Search-Process Memory for Self-Evolving Alpha Mining Agents EFS: Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models
Reference 52
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.