Paper Citation Record · LEDGER

Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2402.14811.

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

pith.paper-citation-record.v1
2402.14811 v1

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 2026-08-22T06:32:14.747728+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:27:58.521943Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T12:40:54.759914Z

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 e97f6fc8-79c8-4a18-973a-cd055ca8bd33 · inbound

Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models cites this paper.

Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-05-13T13:15:10.730539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0cf3952d-9339-4a64-b857-1d59fa3d3edb · inbound

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

Refusal in Language Models Is Mediated by a Single Direction Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 174

Resolution: verified exact; arxiv_id, observed 2026-05-13T10:47:56.083492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation eddc5b66-1a5a-4d45-9070-f00abb5a2b41 · inbound

Understanding Multimodal LLMs: the Mechanistic Interpretability of Llava in Visual Question Answering cites this paper.

Understanding Multimodal LLMs: the Mechanistic Interpretability of Llava in Visual Question Answering Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T19:10:15.502732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c2781e9-ebb0-4604-b3f2-610a0f4dc7fb · inbound

Do I Know This Entity? Knowledge Awareness and Hallucinations in Language Models cites this paper.

Do I Know This Entity? Knowledge Awareness and Hallucinations in Language Models Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T15:28:21.697751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fc41602-6be4-48a6-aff1-0576a43855a8 · inbound

EAP-GP: Mitigating Saturation Effect in Gradient-based Automated Circuit Identification cites this paper.

EAP-GP: Mitigating Saturation Effect in Gradient-based Automated Circuit Identification Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T20:36:01.323353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdcfd47e-57bd-4cba-aa6f-c13a8ff8b1cf · inbound

On Mechanistic Circuits for Extractive Question-Answering cites this paper.

On Mechanistic Circuits for Extractive Question-Answering Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T11:01:28.916768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41eb134e-2757-4c52-8cc1-c34d9860df28 · inbound

Scaling Laws for State Dynamics in Large Language Models cites this paper.

Scaling Laws for State Dynamics in Large Language Models Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T15:31:30.782712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f37de5b-2db4-49e4-b48c-b9944b38fe96 · inbound

Unveiling Instruction-Specific Neurons & Experts: An Analytical Framework for LLM's Instruction-Following Capabilities cites this paper.

Unveiling Instruction-Specific Neurons & Experts: An Analytical Framework for LLM's Instruction-Following Capabilities Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T13:43:22.390818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 220b3f2a-b984-4fad-8f9b-823aa2d83e28 · inbound

Simple Mechanistic Explanations for Out-Of-Context Reasoning cites this paper.

Simple Mechanistic Explanations for Out-Of-Context Reasoning Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T18:28:43.993057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7af43f6a-da75-4816-85b6-e438c219a61a · inbound

Scalpel vs. Hammer: GRPO Amplifies Existing Capabilities, SFT Replaces Them cites this paper.

Scalpel vs. Hammer: GRPO Amplifies Existing Capabilities, SFT Replaces Them Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T17:52:01.642501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 379e2dfb-4cea-4cbe-aff6-b26c96443f14 · inbound

LLMs Encode Harmfulness and Refusal Separately cites this paper.

LLMs Encode Harmfulness and Refusal Separately Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T17:03:16.194871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aca1dfab-4f75-4f84-bad7-05d9b79535cd · inbound

On the transferability of Sparse Autoencoders for interpreting compressed models cites this paper.

On the transferability of Sparse Autoencoders for interpreting compressed models Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:45.774976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb8b5def-cde5-48d9-befd-88b7ab6ece46 · 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 Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T19:27:58.521943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbbec385-2bcb-47ed-8ec3-ee518c0a4134 · inbound

Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models cites this paper.

Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 244

Resolution: verified exact; arxiv_id, observed 2026-05-16T12:40:54.762097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 82ccf1a4-b135-4324-b722-633dbcb13f58 · inbound

Mechanism Shift During Post-training from Autoregressive to Masked Diffusion Language Models cites this paper.

Mechanism Shift During Post-training from Autoregressive to Masked Diffusion Language Models Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T09:12:55.440127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec8a0575-b5fc-4a55-beba-a37cf7937208 · inbound

Cell-Based Representation of Relational Binding in Language Models cites this paper.

Cell-Based Representation of Relational Binding in Language Models Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T13:06:04.773919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 50ef22f3-fff3-4990-aa32-7d87f41117fe · inbound

Slot Machines: How LLMs Keep Track of Multiple Entities cites this paper.

Slot Machines: How LLMs Keep Track of Multiple Entities Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-11T14:01:04.079136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8425f7bb-f3f5-4c15-9975-5fd3134d97b9 · inbound

Circuit Claims Depend on What Is Extracted and How It Is Compared cites this paper.

Circuit Claims Depend on What Is Extracted and How It Is Compared Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T14:03:18.731513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.