Paper Citation Record · LEDGER

Gradients without Backpropagation

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 inbound Pith citation observations for arXiv:2202.08587.

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

pith.paper-citation-record.v1
2202.08587 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 23 of 23 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:33:39.180370Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T01:27:31.206726Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 222146c7-4163-45cb-a9b5-93dbf14d86e8 · inbound

Training neural networks without backpropagation using particles cites this paper.

Training neural networks without backpropagation using particles Gradients without Backpropagation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T20:33:39.180370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1f71400-d157-4058-8168-bc3f6a521f3f · inbound

Noise-based Local Learning using Stochastic Magnetic Tunnel Junctions cites this paper.

Noise-based Local Learning using Stochastic Magnetic Tunnel Junctions Gradients without Backpropagation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T13:47:52.903982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed367f58-65ea-4e7d-ad3a-5e4438f7df16 · inbound

ZeroFlow: Overcoming Catastrophic Forgetting is Easier than You Think cites this paper.

ZeroFlow: Overcoming Catastrophic Forgetting is Easier than You Think Gradients without Backpropagation

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-10T22:41:42.354044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca7f3293-642e-43ab-915e-7c7db1915219 · inbound

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices cites this paper.

Efficient Zeroth-Order Federated Finetuning of Language Models on Resource-Constrained Devices Gradients without Backpropagation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T18:56:25.709239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9afa3096-b2ac-4ee3-af76-49d4c46a5072 · inbound

Backpropagation-Free Metropolis-Adjusted Langevin Algorithm cites this paper.

Backpropagation-Free Metropolis-Adjusted Langevin Algorithm Gradients without Backpropagation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:43:01.608123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d5d04ee-0b0e-464a-b628-b78ce3daef28 · inbound

MobiEdit: Resource-efficient Knowledge Editing for Personalized On-device LLMs cites this paper.

MobiEdit: Resource-efficient Knowledge Editing for Personalized On-device LLMs Gradients without Backpropagation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T10:44:02.577676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ba97522-e0d2-4c4c-8e9e-2ed397839ccc · inbound

Memory Savings at What Cost? A Study of Alternatives to Backpropagation cites this paper.

Memory Savings at What Cost? A Study of Alternatives to Backpropagation Gradients without Backpropagation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T22:24:36.653035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65cb2da8-1ade-4ef7-9343-8835e291098a · inbound

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models cites this paper.

TITAN-Guide: Taming Inference-Time AligNment for Guided Text-to-Video Diffusion Models Gradients without Backpropagation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T10:18:57.082183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation adb53da0-4298-4311-a4ff-364e4a65fd1e · inbound

Forward-Only Continual Learning cites this paper.

Forward-Only Continual Learning Gradients without Backpropagation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T12:31:25.842702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1ebab72-a92b-4d38-acd7-8da84b0d3b6e · inbound

Dimensional Type Systems and Deterministic Memory Management: Design-Time Semantic Preservation in Native Compilation cites this paper.

Dimensional Type Systems and Deterministic Memory Management: Design-Time Semantic Preservation in Native Compilation Gradients without Backpropagation

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-15T09:49:54.564670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 52ccdc9d-ec56-4708-9fef-8d587f86a7ed · inbound

Dimensional Type Systems and Deterministic Memory Management: Design-Time Semantic Preservation in Native Compilation cites this paper.

Dimensional Type Systems and Deterministic Memory Management: Design-Time Semantic Preservation in Native Compilation Gradients without Backpropagation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-13T23:46:05.243960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a6aa66f-73b5-4c44-9ba0-df1d61bd7ab1 · inbound

The Program Hypergraph: Multi-Way Relational Structure for Geometric Algebra, Spatial Compute, and Physics-Aware Compilation cites this paper.

The Program Hypergraph: Multi-Way Relational Structure for Geometric Algebra, Spatial Compute, and Physics-Aware Compilation Gradients without Backpropagation

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-15T08:45:19.212932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5c7b749b-63b8-437f-a417-1c35b6da3869 · inbound

The Program Hypergraph: Multi-Way Relational Structure for Geometric Algebra, Spatial Compute, and Physics-Aware Compilation cites this paper.

The Program Hypergraph: Multi-Way Relational Structure for Geometric Algebra, Spatial Compute, and Physics-Aware Compilation Gradients without Backpropagation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-13T23:04:18.864523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83773abc-406a-414b-97a1-800320a9a716 · inbound

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI cites this paper.

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI Gradients without Backpropagation

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-15T09:09:53.218284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a0055ec3-8f09-423a-8e81-850e790116ad · inbound

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI cites this paper.

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI Gradients without Backpropagation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-13T23:03:58.008815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97623669-2071-4793-aeb8-826e91f7ebf2 · inbound

Decidable By Construction: Design-Time Verification for Trustworthy AI cites this paper.

Decidable By Construction: Design-Time Verification for Trustworthy AI Gradients without Backpropagation

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-15T00:48:25.071455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 48393e32-96ae-4d70-97eb-90f22317ef62 · inbound

Introducing Echo Networks for Computational Neuroevolution cites this paper.

Introducing Echo Networks for Computational Neuroevolution Gradients without Backpropagation

Reference 19

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T05:25:59.217084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cee5fcef-2c74-438a-8faf-22e2c0fce4b9 · inbound

Randomized Subspace Nesterov Accelerated Gradient cites this paper.

Randomized Subspace Nesterov Accelerated Gradient Gradients without Backpropagation

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T16:06:29.764989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d982e09d-9ac5-44fb-b4ff-550b948d5ba3 · inbound

Training Non-Differentiable Networks via Optimal Transport cites this paper.

Training Non-Differentiable Networks via Optimal Transport Gradients without Backpropagation

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:11:01.470626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1c354816-e07d-4bd7-97d9-65c9b02236a8 · inbound

Position: Zeroth-Order Optimization in Deep Learning Is Underexplored, Not Underpowered cites this paper.

Position: Zeroth-Order Optimization in Deep Learning Is Underexplored, Not Underpowered Gradients without Backpropagation

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-20T21:23:44.551703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cfdf8548-d089-4b23-9bd1-5487c7fa2961 · inbound

Adaptive directional gradients for parameterised quantum circuits cites this paper.

Adaptive directional gradients for parameterised quantum circuits Gradients without Backpropagation

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-03T01:27:31.208141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 107afcb8-e171-4628-ae80-07d89811f368 · inbound

Backpropagation-Free Trunk Training via the Split Forward Gradients cites this paper.

Backpropagation-Free Trunk Training via the Split Forward Gradients Gradients without Backpropagation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T20:29:57.728447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3b18939-7876-4a58-ba79-5f313db9355a · inbound

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks cites this paper.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Gradients without Backpropagation

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-01T14:54:28.180797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.