Paper Citation Record · LEDGER

You can remove GPT2's LayerNorm by fine-tuning

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2409.13710.

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

pith.paper-citation-record.v1
2409.13710 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:03:43.075377Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:07:28.650206Z

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 8bee0277-3c9b-4745-a9f6-044593e18eb2 · inbound

Weight-based Analysis of Detokenization in Language Models: Understanding the First Stage of Inference Without Inference cites this paper.

Weight-based Analysis of Detokenization in Language Models: Understanding the First Stage of Inference Without Inference You can remove GPT2's LayerNorm by fine-tuning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T14:03:43.075377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 696aec1f-3d23-47dd-893c-e4920248d475 · inbound

Key and Value Weights Are Probably All You Need: On the Necessity of the Query, Key, Value weight Triplet in Self-Attention Transformers cites this paper.

Key and Value Weights Are Probably All You Need: On the Necessity of the Query, Key, Value weight Triplet in Self-Attention Transformers You can remove GPT2's LayerNorm by fine-tuning

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-18T03:40:50.489589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 97e7c7a8-9661-4146-b28e-1310bdd64260 · inbound

Interactions Between Crosscoder Features: A Compact Proofs Perspective cites this paper.

Interactions Between Crosscoder Features: A Compact Proofs Perspective You can remove GPT2's LayerNorm by fine-tuning

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:07:28.651968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dbfe7642-9732-4edd-9462-061916c160c1 · inbound

Induction in Both Directions: A Mechanistic Analysis of In-Context Learning in Masked Diffusion Language Models cites this paper.

Induction in Both Directions: A Mechanistic Analysis of In-Context Learning in Masked Diffusion Language Models You can remove GPT2's LayerNorm by fine-tuning

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T22:03:47.847142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.