Paper Citation Record · LEDGER

Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2311.12786.

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

pith.paper-citation-record.v1
2311.12786 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:11:37.835041Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:39:17.226668Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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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 bf92982b-bea4-4097-8d07-e28c777fc209 · inbound

Refusal in Language Models Is Mediated by a Single Direction cites this paper.

Refusal in Language Models Is Mediated by a Single Direction Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 140

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T10:47:55.996047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 28523d1f-b8cb-4ee2-9e95-8f6261a2797f · inbound

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey cites this paper.

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:58:26.265077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 14c943d6-00c6-4c7f-b1d7-5c59e01f7a74 · inbound

ICLR: In-Context Learning of Representations cites this paper.

ICLR: In-Context Learning of Representations Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.487532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a6959af-b66a-4d24-bbff-0436b88a3e3c · inbound

Open Problems in Machine Unlearning for AI Safety cites this paper.

Open Problems in Machine Unlearning for AI Safety Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-10T21:24:10.243969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bad5977-5ee9-49b1-a799-7ab9661c9872 · inbound

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities cites this paper.

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-09T14:47:15.146775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cfd8403-661a-4daa-9039-b58b17411291 · inbound

Latent Adversarial Training Improves the Representation of Refusal cites this paper.

Latent Adversarial Training Improves the Representation of Refusal Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T10:11:37.835041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccc7623c-1d06-4b4a-981f-d2ef55405bd1 · inbound

Unified Multi-Task Learning & Model Fusion for Efficient Language Model Guardrailing cites this paper.

Unified Multi-Task Learning & Model Fusion for Efficient Language Model Guardrailing Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T06:00:23.894731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20848180-274a-4d69-a981-68c6b2675f35 · inbound

Is Random Attention Sufficient for Sequence Modeling? Disentangling Trainable Components in the Transformer cites this paper.

Is Random Attention Sufficient for Sequence Modeling? Disentangling Trainable Components in the Transformer Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T11:57:22.716704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7998681-d363-4953-a5c0-af9becae64ee · inbound

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing cites this paper.

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T19:27:58.440969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 222ab62a-eff7-478f-b07d-541fd0edfdff · inbound

A Theory of How Pretraining Shapes Inductive Bias in Fine-Tuning cites this paper.

A Theory of How Pretraining Shapes Inductive Bias in Fine-Tuning Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T21:30:51.482772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc77d75f-2b06-411e-b7b1-0f83340470da · inbound

Hierarchical Latent Structures in Data Generation Process Unify Mechanistic Phenomena across Scale cites this paper.

Hierarchical Latent Structures in Data Generation Process Unify Mechanistic Phenomena across Scale Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-03T04:35:07.949317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f206335c-160d-4337-be15-02a7eb20ed98 · inbound

Steerable but Not Decodable: Function Vectors Operate Beyond the Logit Lens cites this paper.

Steerable but Not Decodable: Function Vectors Operate Beyond the Logit Lens Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T21:03:20.236079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cfa41a25-21fd-4f2a-964d-f0765106ed23 · inbound

Shortcuts in the Tail: Debiasing via Post-Hoc Spectral Compression of Fine-Tuning Updates cites this paper.

Shortcuts in the Tail: Debiasing via Post-Hoc Spectral Compression of Fine-Tuning Updates Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-06-28T23:32:47.022541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 36bd2b0d-d515-47c5-9701-b8b362e7c33a · inbound

Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal cites this paper.

Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 44

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T09:07:47.795633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 36bb660a-f011-4001-b6f7-ad9bb8a9c298 · inbound

Breaking the Solver Bottleneck: Training Task Generators at the Learnable Frontier cites this paper.

Breaking the Solver Bottleneck: Training Task Generators at the Learnable Frontier Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 109

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T08:57:48.288504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8070742c-7e33-4830-92c2-c0ac316f4b44 · inbound

Tracking Representation Dynamics in Large Language Models with Persistent Homology cites this paper.

Tracking Representation Dynamics in Large Language Models with Persistent Homology Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:39:17.233705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 42c25006-371f-4524-bb77-4cc4f5c4498f · inbound

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning cites this paper.

Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T19:03:52.264030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 799ffe17-1cd9-4c2a-9d04-4facd9be5921 · inbound

SOS-LoRA: Static Orthogonal-Subspace Low-Rank Adaptation with Fixed Multi-Scale Scaling cites this paper.

SOS-LoRA: Static Orthogonal-Subspace Low-Rank Adaptation with Fixed Multi-Scale Scaling Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 154

Resolution: unresolved; no resolver link, observed 2026-08-02T09:51:03.633366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.