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Paper Citation Record · LEDGER

Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2205.03195.

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

pith.paper-citation-record.v1
2205.03195 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 2026-08-04T06:34:03.388597+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-11T01:04:26.288913Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T04:45:59.952124Z

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 656a4b93-5f90-4ad6-a59d-63b05bb65bf2 · inbound

Conditional Flow-VAE for Safety-Critical Traffic Scenario Generation cites this paper.

Conditional Flow-VAE for Safety-Critical Traffic Scenario Generation Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation

Reference 39

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T06:30:44.786196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-08T18:22:42.314202Z digest=sha256:ac57da63c5ce346a7edba225dbf24c6c9ae1c5155bda9628f8c9c662819a23ec

Observation 909f5260-dea1-450b-bbd2-9106ab459670 · inbound

Response Time Enhances Alignment with Heterogeneous Preferences cites this paper.

Response Time Enhances Alignment with Heterogeneous Preferences Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation

Reference 126

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:45:59.960739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-11T01:04:26.288913Z digest=sha256:5b883d432f978010201fca95537ea433728da50e95877642006397c8dd03a9ae