Paper Citation Record · LEDGER

A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2503.01854.

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

pith.paper-citation-record.v1
2503.01854 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:44:23.313148Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T15:47:23.271119Z

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 a6c0d282-3272-4465-ae5b-ae389312df35 · inbound

Get Experience from Practice: LLM Agents with Record & Replay cites this paper.

Get Experience from Practice: LLM Agents with Record & Replay A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:44:23.313148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e5d3ddd-d4d4-47c3-b843-058c58bc6c12 · inbound

VSCBench: Bridging the Gap in Vision-Language Model Safety Calibration cites this paper.

VSCBench: Bridging the Gap in Vision-Language Model Safety Calibration A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:13:11.081906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef42f86e-ef8d-4b6f-8983-e1032f7e8297 · inbound

Model Unlearning via Sparse Autoencoder Subspace Guided Projections cites this paper.

Model Unlearning via Sparse Autoencoder Subspace Guided Projections A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T12:28:02.569189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7515cc1a-c3f5-4783-8e11-d4618ebe8263 · inbound

LLM Unlearning Should Be Form-Independent cites this paper.

LLM Unlearning Should Be Form-Independent A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T05:33:35.407298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1a4a438-8b34-4580-ae28-612bbe2073f3 · inbound

Towards Reliable Forgetting: A Survey on Machine Unlearning Verification cites this paper.

Towards Reliable Forgetting: A Survey on Machine Unlearning Verification A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:37:14.102758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9168932f-3c04-4f0e-979e-3cb72137e104 · inbound

BalDRO: A Distributionally Robust Optimization based Framework for Large Language Model Unlearning cites this paper.

BalDRO: A Distributionally Robust Optimization based Framework for Large Language Model Unlearning A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T10:45:41.437703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f363f5ef-b5a8-4cea-97cf-9469fa271ba3 · inbound

Anatomy of Unlearning: The Dual Impact of Fact Salience and Model Fine-Tuning cites this paper.

Anatomy of Unlearning: The Dual Impact of Fact Salience and Model Fine-Tuning A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T21:38:00.581865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b52d1256-6d52-4dc2-a06e-560751d34370 · inbound

WIN-U: Woodbury-Informed Newton-Unlearning as a retain-free Machine Unlearning Framework cites this paper.

WIN-U: Woodbury-Informed Newton-Unlearning as a retain-free Machine Unlearning Framework A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-10T14:30:31.210980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e6ae33e7-2d7b-4d34-a04b-886904ce1627 · inbound

Unlearners Can Lie: Evaluating and Improving Honesty in LLM Unlearning cites this paper.

Unlearners Can Lie: Evaluating and Improving Honesty in LLM Unlearning A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:31:24.500346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 76679903-acaa-4442-8a2c-5bc9449ff451 · inbound

Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning cites this paper.

Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T21:52:48.266242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0304e2e3-fb55-4333-8286-38e3eb8ef3cb · inbound

Trustworthy Agent Network: Trust in Agent Networks Must Be Baked In, Not Bolted On cites this paper.

Trustworthy Agent Network: Trust in Agent Networks Must Be Baked In, Not Bolted On A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-20T10:33:12.346094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e8547078-bc1c-4a35-8dfc-7a6571253ec6 · inbound

Visual-Noise Guided In-Context Distillation for Multimodal Large Language Model Unlearning cites this paper.

Visual-Noise Guided In-Context Distillation for Multimodal Large Language Model Unlearning A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 19

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T19:03:51.493739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 143be240-087d-46d4-a3de-069f969877b8 · inbound

Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks cites this paper.

Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 72

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T15:47:23.272282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4e872636-f77f-4a4a-9f81-8b2ba5c0d7c3 · inbound

One Modality to Forget Them All: Enhancing Cross-Modal Unlearning in Vision-Language Models cites this paper.

One Modality to Forget Them All: Enhancing Cross-Modal Unlearning in Vision-Language Models A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T21:01:04.731778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb0a8d0e-46a0-4aae-8e67-f5545104aa69 · inbound

Gradient Concentration, Not Weight Saliency, Explains Representation-Level Class Unlearning cites this paper.

Gradient Concentration, Not Weight Saliency, Explains Representation-Level Class Unlearning A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T07:47:11.800199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.