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Paper Citation Record · LEDGER

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect

As of 8 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2607.14111.

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

pith.paper-citation-record.v1
2607.14111 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T14:41:02.495796Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

13 of 13 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6d64bd45-f16b-498f-b4b2-83caec73200d · outbound

This paper cites Looking Inward: Language Models Can Learn About Themselves by Introspection.

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-02T14:41:01.060123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:41:01.060123Z digest=sha256:d7e432d10b73214fc0ecfb1fb976567834844bee3bea7d03c164f1ea3562db7c

Observation b18f976d-cbfc-48db-a82c-2d973e88798e · outbound

This paper cites Uzay Macar, Li Yang, Atticus Wang, Peter Wallich, Emmanuel Ameisen, and Jack Lindsey.

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect Uzay Macar, Li Yang, Atticus Wang, Peter Wallich, Emmanuel Ameisen, and Jack Lindsey

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-02T14:41:01.984635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:41:01.984635Z digest=sha256:5e4151c9f3b9c6b8ca2860336a1e2888b4716b70d261856dd41328aa1c1ac2bc

Observation 8acff31c-bc84-4564-85de-a4843888c3c2 · outbound

This paper cites Mechanisms of Introspective Awareness.

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect Mechanisms of Introspective Awareness

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-02T14:41:02.128579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:41:02.128579Z digest=sha256:a11be78ad057e1aded2e5c7614d8cd8a7ad649b033cd08276ccd95279549c58f

Observation 6714a5b3-011e-4cda-8393-17b2a5290732 · outbound

This paper cites Meta AI Blog.

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect Meta AI Blog

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-02T14:41:02.204048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:41:02.204048Z digest=sha256:e9e265fc5d82c177127dad2f9d17e7bd1c6d05544e58ffeda36e248cb13d76b5

Observation 6ad6c776-e846-413d-8777-d1cdc034f55f · outbound

This paper cites 14 Alexander Matt Turner, Lisa Thiergart, Gavin Leech, David Udell, Juan J.

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect 14 Alexander Matt Turner, Lisa Thiergart, Gavin Leech, David Udell, Juan J

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-02T14:41:02.420907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:41:02.420907Z digest=sha256:5c0a8a90f773ee498743285c5eee9e9e3be539fe1dad6c9924b95cae7b3fb7e4

Observation de660273-d5e4-48bb-87e6-f07be1747891 · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-02T14:41:02.495796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:41:02.495796Z digest=sha256:64318b9f814cfdc394397ee5e9ae5853f3cb9ca1b93a23b9788db4a7e5e23847

Observation 7b94b606-69ea-42b0-b16e-8d30f178bb56 · outbound

This paper cites an unresolved cited work.

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect Unresolved cited work

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-02T14:41:02.383510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:41:02.383510Z digest=sha256:c7494843be41f5c9f908a00db2a79d151be2deb8bb6793344cbef6d404fbcdcc

Observation f2416c32-58bf-441d-a1d1-9b2cb09950a7 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect Measuring Massive Multitask Language Understanding

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-02T14:41:01.375483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:41:01.375483Z digest=sha256:92a0c15bcdb90fb2ee5172e2deae180280a295cb8c4351ea8e1abaecf29f9c99

Observation 1c7096b6-d065-47c9-be64-76c84f30b3f4 · outbound

This paper cites Activation oracles: Training and evaluating LLMs as general-purpose activation explainers.arXiv preprint arXiv:2512.15674,.

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect Activation oracles: Training and evaluating LLMs as general-purpose activation explainers.arXiv preprint arXiv:2512.15674,

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-02T14:41:01.711299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:41:01.711299Z digest=sha256:3c8ce7eaab8eea16bd8e00a2b43b12a2692be6351e4ab484bd66654c74d4c41d

Observation 7093ab82-e46b-455f-8108-ddaf0a7ccfc5 · outbound

This paper cites How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions.

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-02T14:41:02.279489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:41:02.279489Z digest=sha256:893fd6bf12c4ee8adef64abd64a526680b57947e3264ac289749b5be745f2691

Observation 233c0738-67ca-4a00-87b6-531f68fd16e4 · outbound

This paper cites Teaching Models to Express Their Uncertainty in Words.

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect Teaching Models to Express Their Uncertainty in Words

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-02T14:41:01.841763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:41:01.841763Z digest=sha256:55dcf01d3c744bb908a0e43f5435f45ee8da0d1a0fb6cddc65e3f27305df9cc2

Observation a06ed7db-62b2-42b5-a119-a149ebbfb89f · outbound

This paper cites Language Models (Mostly) Know What They Know.

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect Language Models (Mostly) Know What They Know

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-02T14:41:01.545439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:41:01.545439Z digest=sha256:c4b16c7d1a1dce982847558c8cc5bda82a9aa1bd2afba86731f12b5e922a8a39

Observation 3e9d38b2-d208-43b3-bf03-f53f9d63c216 · outbound

This paper cites Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt.

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt

Reference 2026

Resolution
unresolved
no resolver link, observed 2026-08-02T14:41:01.206300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:41:01.206300Z digest=sha256:6f0a8705a9470a9603eb47183db6b947d398b1e1e2c8bf2cea240c31be235613

Pith citing papers

No inbound Pith citation observations are available.