Paper Citation Record · LEDGER

Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2406.02596.

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

pith.paper-citation-record.v1
2406.02596 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:53:23.212007Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:49:45.643005Z

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 ffd089dd-42eb-4230-bd46-73206291d18d · inbound

Recovering Plasticity of Neural Networks via Soft Weight Rescaling cites this paper.

Recovering Plasticity of Neural Networks via Soft Weight Rescaling Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:23.212007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b49c048-11a0-4e9c-8383-615fe4c44c38 · inbound

A Simple Baseline for Stable and Plastic Neural Networks cites this paper.

A Simple Baseline for Stable and Plastic Neural Networks Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:26.512653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f31e223d-ed04-4978-b17c-ea41dc475b74 · inbound

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes cites this paper.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:49.456993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49c88cb4-8ef3-4756-9411-7671451229cf · inbound

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control cites this paper.

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:15:49.790439Z

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 067ef0a9-fa1e-4f63-8a33-04bb20ebaadb · inbound

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control cites this paper.

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:12:41.375942Z

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 0c76c794-8a12-4c00-8095-5a1b1600f720 · inbound

Plasticity-Enhanced Multi-Agent Mixture of Experts for Dynamic Objective Adaptation in UAVs-Assisted Emergency Communication Networks cites this paper.

Plasticity-Enhanced Multi-Agent Mixture of Experts for Dynamic Objective Adaptation in UAVs-Assisted Emergency Communication Networks Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:55:58.947609Z

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 ec4c2042-aa0d-4e31-9cd0-a1a3ba690824 · inbound

C-voting: Confidence-Based Test-Time Voting without Explicit Energy Functions cites this paper.

C-voting: Confidence-Based Test-Time Voting without Explicit Energy Functions Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:05:24.952928Z

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 87d2804d-f76f-430e-9e27-7f69e2d45b49 · inbound

Balancing Plasticity and Stability with Fast and Slow Successor Features cites this paper.

Balancing Plasticity and Stability with Fast and Slow Successor Features Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-06-29T22:24:00.757804Z

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 461870a2-4fd7-48ce-9bed-c2f10d417315 · inbound

EMAgnet: Parameter-Space EMA Regularization for Policy Gradient Self-Play in Large Games cites this paper.

EMAgnet: Parameter-Space EMA Regularization for Policy Gradient Self-Play in Large Games Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:49:45.644943Z

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 0165518d-d6da-4831-8f33-afa3515f3912 · inbound

Relative Value Learning cites this paper.

Relative Value Learning Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T08:32:00.061250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.