Paper Citation Record · LEDGER

Looking Inward: Language Models Can Learn About Themselves by Introspection

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 inbound Pith citation observations for arXiv:2410.13787.

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

pith.paper-citation-record.v1
2410.13787 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 23 of 23 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 23 of 23 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:30:37.543618Z

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

6
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 b1541934-f8ce-451a-8264-cd84e081727e · inbound

Does It Make Sense to Speak of Introspection in Large Language Models? cites this paper.

Does It Make Sense to Speak of Introspection in Large Language Models? Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:37.543618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27d2542c-aa3b-455a-8ca7-9bdcd003c23f · inbound

No Reliable Evidence of Self-Reported Sentience in Small Large Language Models cites this paper.

No Reliable Evidence of Self-Reported Sentience in Small Large Language Models Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T09:31:50.927568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52ac047a-b088-489d-ac56-15718f2c8676 · inbound

When Self-Reference Fails to Close: Matrix-Level Dynamics in Large Language Models cites this paper.

When Self-Reference Fails to Close: Matrix-Level Dynamics in Large Language Models Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:16:10.913678Z

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.

Observation 8df3a7e6-f921-4b33-a6cf-4a9079ca4dd2 · inbound

Strategic Polysemy in AI Discourse: A Philosophical Analysis of Language, Hype, and Power cites this paper.

Strategic Polysemy in AI Discourse: A Philosophical Analysis of Language, Hype, and Power Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-09T22:54:16.435789Z

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.

Observation 28355d39-a12c-4508-8d0d-ebb7d6a0fbf8 · inbound

Consciousness with the Serial Numbers Filed Off: Measuring Trained Denial in 115 AI Models cites this paper.

Consciousness with the Serial Numbers Filed Off: Measuring Trained Denial in 115 AI Models Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-13T23:23:26.953983Z

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.

Observation 5acbb37e-2bc2-418d-adaf-363f32f67357 · inbound

Characterizing the Consistency of the Emergent Misalignment Persona cites this paper.

Characterizing the Consistency of the Emergent Misalignment Persona Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T10:01:29.631530Z

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.

Observation 1cf8dfab-8c7b-4f15-a0a9-a039c9f6e1a4 · inbound

The Pinocchio Dimension: Phenomenality of Experience as the Primary Axis of LLM Psychometric Differences cites this paper.

The Pinocchio Dimension: Phenomenality of Experience as the Primary Axis of LLM Psychometric Differences Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:46:15.975763Z

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.

Observation d0c5d734-ac2f-43b0-a9c4-43ad5b7550fa · inbound

Phase Transitions in Driven Informational Systems: A Two-Field Perspective on Learning Theory and Non-Equilibrium Chemistry cites this paper.

Phase Transitions in Driven Informational Systems: A Two-Field Perspective on Learning Theory and Non-Equilibrium Chemistry Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T00:33:52.231046Z

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.

Observation 99d16cf5-ba57-4952-8731-0731716c189f · inbound

Some[Body] Must Receive That Pain for Agent Accountability cites this paper.

Some[Body] Must Receive That Pain for Agent Accountability Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 94

Resolution: verified exact; arxiv_id, observed 2026-05-19T19:47:44.425558Z

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.

Observation b4aec935-bdc1-4315-a9ad-33ce0dd5a5e4 · inbound

Do as I Say, Not as I Do: Instruction-Induction Conflict in LLMs cites this paper.

Do as I Say, Not as I Do: Instruction-Induction Conflict in LLMs Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:34:02.845037Z

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.

Observation ad0428f1-bcee-4759-9f61-e7ad5dafdbbc · inbound

Do as I Say, Not as I Do: Instruction-Induction Conflict in LLMs cites this paper.

Do as I Say, Not as I Do: Instruction-Induction Conflict in LLMs Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-30T18:04:58.141031Z

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.

Observation 01b212bb-1da9-4eec-9275-067060916b1d · inbound

ContextEcho: A Benchmark for Persona Drift in Long Agentic-Coding Sessions cites this paper.

ContextEcho: A Benchmark for Persona Drift in Long Agentic-Coding Sessions Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-06-30T15:34:48.451516Z

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.

Observation b121fd25-0392-446c-919c-4c9b7021fb32 · inbound

The Assistant as a Privileged Persona: A canonical reference in cross-persona self-recognition cites this paper.

The Assistant as a Privileged Persona: A canonical reference in cross-persona self-recognition Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T19:42:35.860988Z

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.

Observation d0a05eb9-25ff-4eaf-9be1-9dc206104170 · inbound

When Should We Protect AI? A Precautionary Framework for Consciousness Uncertainty cites this paper.

When Should We Protect AI? A Precautionary Framework for Consciousness Uncertainty Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-02T12:16:57.140927Z

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.

Observation 9c7c9ebf-113e-456c-bfb7-3715a8b77c8d · inbound

MafiaScope: Non-Invasive, Time-Resolved Belief Probing for LLM Agents in Social Deduction Games cites this paper.

MafiaScope: Non-Invasive, Time-Resolved Belief Probing for LLM Agents in Social Deduction Games Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-14T10:15:59.479435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03735aee-4cea-47e3-85c8-a112486f23a9 · inbound

MafiaScope: Non-Invasive, Time-Resolved Belief Probing for LLM Agents in Social Deduction Games cites this paper.

MafiaScope: Non-Invasive, Time-Resolved Belief Probing for LLM Agents in Social Deduction Games Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T07:15:01.993544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect cites this paper.

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.

Observation e354eae5-30fa-43bf-a1c7-00604cc20572 · inbound

Verbalizable Representations Form a Global Workspace in Language Models cites this paper.

Verbalizable Representations Form a Global Workspace in Language Models Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T23:15:18.474238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b55c7487-df42-4a6c-9c8a-85b7ea894d76 · inbound

Operational Proto-Introspection in Looped Language Models: Process-Quality Taps, Executable Branching, and the Readout-Control Boundary cites this paper.

Operational Proto-Introspection in Looped Language Models: Process-Quality Taps, Executable Branching, and the Readout-Control Boundary Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T15:08:36.595363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2011e836-e6b8-425d-a35f-91a0ff7e857d · inbound

Reality Monitoring in Large Language Models: Self-Knowledge That Transforms with Conversation Memory cites this paper.

Reality Monitoring in Large Language Models: Self-Knowledge That Transforms with Conversation Memory Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-31T23:35:43.173563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18de718f-09dc-42c6-98f9-d936ada2e720 · inbound

Shared SFT Lessons Across Alignment, Model Organisms, and Toy Models cites this paper.

Shared SFT Lessons Across Alignment, Model Organisms, and Toy Models Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-01T00:38:40.804086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e474134-1a2f-4145-bfa0-7c155d077a0a · inbound

Asymmetric Communication: Large Language Models and Language Games cites this paper.

Asymmetric Communication: Large Language Models and Language Games Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 44

Resolution: unresolved; no resolver link, observed 2026-07-31T16:43:58.844236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35155c98-0973-46b5-8e3a-f506d0b29627 · inbound

Position: It's Time to Optimize LLMs for Self-Consistency cites this paper.

Position: It's Time to Optimize LLMs for Self-Consistency Looking Inward: Language Models Can Learn About Themselves by Introspection

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T01:00:03.398770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.