Paper Citation Record · LEDGER

What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2410.23743.

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

pith.paper-citation-record.v1
2410.23743 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:23:22.079601Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T19:03:51.834471Z

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 92a18ce8-6f92-4aae-80a1-7f1ee0280512 · inbound

When More is Less: Understanding Chain-of-Thought Length in LLMs cites this paper.

When More is Less: Understanding Chain-of-Thought Length in LLMs What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T13:23:22.079601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8148d11-4e9b-4667-b687-3b5f65736822 · inbound

Reasoning Can Hurt the Inductive Abilities of Large Language Models cites this paper.

Reasoning Can Hurt the Inductive Abilities of Large Language Models What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T12:36:13.280627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1083498-799d-4ade-94ce-86090ac20c60 · inbound

Spectral Insights into Data-Oblivious Critical Layers in Large Language Models cites this paper.

Spectral Insights into Data-Oblivious Critical Layers in Large Language Models What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T12:11:24.934062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b26c2b7-7cf4-4c1d-9933-cff2d5aae3f3 · inbound

What makes Reasoning Models Different? Follow the Reasoning Leader for Efficient Decoding cites this paper.

What makes Reasoning Models Different? Follow the Reasoning Leader for Efficient Decoding What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T05:52:18.391931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5f17dd1-7cd4-439e-a439-a55953373809 · inbound

Re-Emergent Misalignment: How Narrow Fine-Tuning Erodes Safety Alignment in LLMs cites this paper.

Re-Emergent Misalignment: How Narrow Fine-Tuning Erodes Safety Alignment in LLMs What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T20:12:31.713901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dc1b848-912e-46c8-b377-ca4aa5f724da · inbound

Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling cites this paper.

Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-06-29T19:03:51.835964Z

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.