Paper Citation Record · LEDGER

Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering

As of 13 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2605.14022.

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

pith.paper-citation-record.v1
2605.14022 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-15T02:40:42.798632Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

12 of 12 outbound references displayed

verified exact9
verified fuzzy2
unresolved0
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5486493b-ac5f-4e0a-98f7-cc4c86a87652 · outbound

This paper cites Improving turbulence control through explainable deep learning.

Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering Improving turbulence control through explainable deep learning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-25T03:01:55.587182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0329d6dc-d095-454a-9dbc-9038db3e0a45 · outbound

This paper cites SE(3)-Stochastic Flow Matching for Protein Backbone Generation.

Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering SE(3)-Stochastic Flow Matching for Protein Backbone Generation

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:49:41.661655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9afdc0c1-9f2c-4a9e-bdf0-7991d69352c3 · outbound

This paper cites Harder, A.

Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering Harder, A

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:49:41.651421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1355a46f-4b3b-4558-ad0d-66dc14b64d09 · outbound

This paper cites Planning with Diffusion for Flexible Behavior Synthesis.

Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering Planning with Diffusion for Flexible Behavior Synthesis

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-15T02:49:41.667708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8705a388-6a82-4ef6-872d-06a89ca5f150 · outbound

This paper cites Continuous control with deep reinforcement learning.

Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering Continuous control with deep reinforcement learning

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-05-15T02:49:41.659000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 235f2a82-00b1-4035-a962-ac59d79f08ea · outbound

This paper cites an unresolved cited work.

Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering Unresolved cited work

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:49:41.665326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 14c5c004-367f-4be1-9529-901da637e480 · outbound

This paper cites Policy Distillation.

Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering Policy Distillation

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-15T02:49:41.670454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9dce3eb0-6353-4a66-a536-70373ab44ca5 · outbound

This paper cites Diff-SPORT: Diffusion-based Sensor Placement Optimization and Reconstruction of Turbulent flows in urban environments.

Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering Diff-SPORT: Diffusion-based Sensor Placement Optimization and Reconstruction of Turbulent flows in urban environments

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:49:41.647235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4c3c5408-ca27-4de5-b033-d9f835c3fb56 · outbound

This paper cites Physics-guided surrogate learning enables zero-shot control of turbulent wings.

Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering Physics-guided surrogate learning enables zero-shot control of turbulent wings

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-15T02:49:41.643168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 00b4490a-237e-416b-af1f-26c514304847 · outbound

This paper cites At the start of each episode, an initial condition is selected via a seeded random number generator to ensure reproducibility.

Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering At the start of each episode, an initial condition is selected via a seeded random number generator to ensure reproducibility

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T04:14:59.865681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 893c018c-20d3-45ed-bcad-6b4ed3744d4d · outbound

This paper cites Note that we applied the default parameters by StableBaselines3 [Raffin et al., 2021] for the rest.

Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering Note that we applied the default parameters by StableBaselines3 [Raffin et al., 2021] for the rest

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T04:14:59.860785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5ddf95a9-73fa-4317-ac0f-6814ec393bd3 · outbound

This paper cites an unresolved cited work.

Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering Unresolved cited work

Reference 12

Resolution: malformed identifier; raw_fallback, observed 2026-05-15T04:14:59.854372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.