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Paper Citation Record · LEDGER

Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2306.12964.

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

pith.paper-citation-record.v1
2306.12964 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:32:52.220894Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-16T12:16:17.039197Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0aa31962-496e-4817-923c-fe22f8c2ec27 · inbound

QuantBench: Benchmarking AI Methods for Quantitative Investment cites this paper.

QuantBench: Benchmarking AI Methods for Quantitative Investment Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-16T10:32:52.220894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:32:52.220894Z digest=sha256:e822186b63fa2253c90dd6607e129a28688ad6e789ffb9705accbf8f3a9b36ab

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

AQuA: Recursively Self-Improving Quantitative Trading Research Agents cites this paper.

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

Reference 11

Resolution
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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T22:14:12.429640Z digest=sha256:644f904be3fbf528f1ecc39ca45940aedd5ff874bb0aa9fa0f395c0e51b809a1