Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:54:43.733181Z
Paper Citation Record · LEDGER
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies
As of 21 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2507.02953.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
16 of 16 outbound references displayed
- verified exact0
- verified fuzzy6
- unresolved10
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 68031814-6257-4cd0-b8f0-abf4b0f6c546 · outbound
This paper cites Barbara, Ruigang Wang, and Ian R.
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies Barbara, Ruigang Wang, and Ian R
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:54:44.110245Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ac32c450-c7d8-4fa1-8910-10aee3d22b17 · outbound
This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:54:43.304291Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b5cadf90-4cdd-4e55-a4e8-704910adf056 · outbound
This paper cites Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:54:43.374298Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cb30de8c-9d57-42ee-b7da-127e8aef4638 · outbound
This paper cites Measure theory and fine properties of functions.
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies Measure theory and fine properties of functions
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:54:44.084494Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 8939fc97-3c1d-4aa8-8338-73c370226091 · outbound
This paper cites Sparsegpt: Massive language models can be accurately pruned in one-shot.
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies Sparsegpt: Massive language models can be accurately pruned in one-shot
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:54:43.540799Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 11fa7e59-32c5-40c5-ba11-5618b2dcd1be · outbound
This paper cites A Review of Safe Reinforcement Learning: Methods, Theory and Applications.
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies A Review of Safe Reinforcement Learning: Methods, Theory and Applications
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:54:43.614688Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ad9ef977-e278-477b-8f12-8e98788816a8 · outbound
This paper cites Second order derivatives for network pruning: Optimal brain surgeon.
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies Second order derivatives for network pruning: Optimal brain surgeon
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:54:43.636450Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation acc74348-4943-4f50-8ba2-8de514599c98 · outbound
This paper cites Delving deep into rectifiers: Surpassing human-level performance on imagenet classification.
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:54:43.646080Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fe2b7153-c516-482d-ab47-65bd43170578 · outbound
This paper cites Gaussian Error Linear Units (GELUs).
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies Gaussian Error Linear Units (GELUs)
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:54:43.653791Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1a2624cb-419a-43aa-b36d-e2d5b0f8ba39 · outbound
This paper cites Optimal brain damage.
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies Optimal brain damage
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:54:43.666564Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 621c0a69-4451-4555-82f8-7b6d1f3ac046 · outbound
This paper cites Rectifier nonlinearities improve neural network acoustic models.
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies Rectifier nonlinearities improve neural network acoustic models
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:54:43.692854Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c052c6bb-254c-4bb8-8b2a-25de66eb08ff · outbound
This paper cites Human-level control through deep reinforcement learning.
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies Human-level control through deep reinforcement learning
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:54:43.700268Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 04bd743e-85f8-4a15-8f42-b33d1faaa8e6 · outbound
This paper cites On the effects of pruning on evolved neural controllers for soft robots.
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies On the effects of pruning on evolved neural controllers for soft robots
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:54:43.986890Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation e25dfab3-e6f5-4fd7-ab97-8275632d26e3 · outbound
This paper cites Rectified linear units improve restricted boltzmann machines.
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies Rectified linear units improve restricted boltzmann machines
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:54:43.958730Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 061ac16d-3a26-4342-9616-28399e032014 · outbound
This paper cites Lipschitz regularity of deep neural networks: Analysis and efficient estimation.
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies Lipschitz regularity of deep neural networks: Analysis and efficient estimation
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:54:43.934786Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 779f8b3e-3901-4446-8aba-d512216052b9 · outbound
This paper cites Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective, October 2022.
Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective, October 2022
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:54:43.911517Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Pith citing papers
No inbound Pith citation observations are available.