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Paper Citation Record · LEDGER

Fast Feedforward Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2308.14711.

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

pith.paper-citation-record.v1
2308.14711 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:35:43.474963Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6075bcdb-7196-458f-a53a-448fb0cb73ea · inbound

Position: A Theory of Deep Learning Must Include Compositional Sparsity cites this paper.

Position: A Theory of Deep Learning Must Include Compositional Sparsity Fast Feedforward Networks

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T20:35:43.474963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:35:43.474963Z digest=sha256:711766ae30121089895ebf62e4be357f7f465b0681b4994b4d7e1f866d71c581

Observation c5286010-d432-4e66-8f60-6aecb6989a70 · inbound

LAWS: Learning from Actual Workloads Symbolically -- A Self-Certifying Parametrized Cache Architecture for Neural Inference, Robotics, and Edge Deployment cites this paper.

LAWS: Learning from Actual Workloads Symbolically -- A Self-Certifying Parametrized Cache Architecture for Neural Inference, Robotics, and Edge Deployment Fast Feedforward Networks

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:56:05.269113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T15:43:14.768649Z digest=sha256:39f3cf170d35b2ba9c830ca9587d036057a62e33a7646eab44df236095ca983b

Observation 2e2eee0f-56ee-406b-b9bc-dd33889c46c4 · inbound

HASTE: A Framework for Training-Free, Dynamic, and Steerable Compression of Pre-Trained Convolutional Neural Networks cites this paper.

HASTE: A Framework for Training-Free, Dynamic, and Steerable Compression of Pre-Trained Convolutional Neural Networks Fast Feedforward Networks

Reference 31

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T06:34:18.278049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T06:27:05.897385Z digest=sha256:8e73f558052b5f7bff24fc7cd6647be3554b59d6b1d8f37f1ab61f734813425e

Observation f7f05fb8-35ea-4b27-8153-8468bd6900d6 · inbound

Amplitude-Only FFN Intervention for Tool-Structured LLM Inference Method: Gated Evaluation Protocol, and Cross-Model Empirical Results cites this paper.

Amplitude-Only FFN Intervention for Tool-Structured LLM Inference Method: Gated Evaluation Protocol, and Cross-Model Empirical Results Fast Feedforward Networks

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-14T06:26:24.512653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T06:26:24.512653Z digest=sha256:4902181d681063e7640ee41debd042c24fb596f440875d4f41be0ef85f7085d8

Observation 59854b7d-b2c3-4865-b66e-6dc50c122360 · inbound

Amplitude-Only FFN Intervention for Tool-Structured LLM Inference Method: Gated Evaluation Protocol, and Cross-Model Empirical Results cites this paper.

Amplitude-Only FFN Intervention for Tool-Structured LLM Inference Method: Gated Evaluation Protocol, and Cross-Model Empirical Results Fast Feedforward Networks

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-15T08:58:21.654258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T08:58:21.654258Z digest=sha256:c92e0138156b9661a35e7780646bd8ce897ffa2741217260abe156372cc9c795