Paper Citation Record · LEDGER

EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2402.09801.

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

pith.paper-citation-record.v1
2402.09801 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:43:35.177456Z

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

0
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 47ea7bc3-9d4f-41df-814d-39825d370b21 · inbound

Hallucination of Multimodal Large Language Models: A Survey cites this paper.

Hallucination of Multimodal Large Language Models: A Survey EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models

Reference 181

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:33:33.210685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fede79b0-6efd-413c-94bc-753022952baa · inbound

Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images cites this paper.

Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T05:43:35.177456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 683058b4-dacf-49ff-bc4e-069659e4a78c · inbound

Mitigating Object Hallucinations via Sentence-Level Early Intervention cites this paper.

Mitigating Object Hallucinations via Sentence-Level Early Intervention EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models

Reference 70

Resolution: verified exact; arxiv_id, observed 2026-05-25T08:35:32.755135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 60bcbc35-bd93-4503-b7db-56c3ff6e5c18 · inbound

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey cites this paper.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models

Reference 195

Resolution: unresolved; no resolver link, observed 2026-08-05T20:29:02.710704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a52ba67-cec8-4bea-a320-f134e0de08ec · inbound

Not All Needles Are Found: How Fact Distribution and Don't Make It Up Prompts Shape Retrieval, Reasoning, and Hallucination in Long-Context LLMs cites this paper.

Not All Needles Are Found: How Fact Distribution and Don't Make It Up Prompts Shape Retrieval, Reasoning, and Hallucination in Long-Context LLMs EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-03T12:42:38.006298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 177a07e5-dfc3-4ea8-8ae0-ab93cc5b72a1 · inbound

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering cites this paper.

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models

Reference 267

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T23:54:45.791984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.