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Paper Citation Record · LEDGER

Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2411.13117.

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

pith.paper-citation-record.v1
2411.13117 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 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:03:02.401440Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T21:15:04.062112Z

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 80efe505-6c96-40c4-806b-a586fdc29537 · inbound

Position: Mechanistic Interpretability Should Prioritize Feature Consistency in SAEs cites this paper.

Position: Mechanistic Interpretability Should Prioritize Feature Consistency in SAEs Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T14:03:02.401440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:03:02.401440Z digest=sha256:f698b58721d069c4bca17389da5cce56e760acb47e83e91fa89453052ecdfc07

Observation 60780d5f-74a1-4385-9266-7171d2fca26a · inbound

Towards Atoms of Large Language Models cites this paper.

Towards Atoms of Large Language Models Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-04T15:20:32.189070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T15:20:32.189070Z digest=sha256:8186a1b3898dfda34e0a59a5f29fa5780463c99ae6ee027c44635e2446fc0f5d

Observation d8e9d419-4a36-4703-b04e-0132ba5e24e8 · inbound

The Rate-Distortion-Polysemanticity Tradeoff in SAEs cites this paper.

The Rate-Distortion-Polysemanticity Tradeoff in SAEs Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-06-30T21:15:04.064124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T21:13:01.880935Z digest=sha256:53aa1d8e8d8d04e5102fa8bddb86d5c161929abb07400e009034ef0ad21fca09

Observation c80f9484-f02d-4bb3-9f08-95fb4162280a · inbound

Sign-Aware Gated Sparse Autoencoders: Modeling Anticorrelated Features with Bi-Jump-ReLU Activations cites this paper.

Sign-Aware Gated Sparse Autoencoders: Modeling Anticorrelated Features with Bi-Jump-ReLU Activations Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders

Reference 20

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T14:23:30.755282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-29T14:16:44.232080Z digest=sha256:f4b58fe2c790b31b9050c2af7be927a609fc076b43c0e485e37a4f7e6c4df919

Observation 9c450dd6-7568-4c30-a481-f097195c9688 · inbound

Sign-Aware Gated Sparse Autoencoders: Modeling Anticorrelated Features with Bi-Jump-ReLU Activations cites this paper.

Sign-Aware Gated Sparse Autoencoders: Modeling Anticorrelated Features with Bi-Jump-ReLU Activations Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-04T05:02:51.324984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:02:51.324984Z digest=sha256:d074f88f37bc4d23d14a1b7b13f0daadd2a36b3b34d2caf581c67b3fa94c0510