Paper Citation Record · LEDGER

ContinualFlow: Learning and Unlearning with Neural Flow Matching

As of 21 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2506.18747.

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

pith.paper-citation-record.v1
2506.18747 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:50:58.795919Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

verified exact0
verified fuzzy9
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9d9e5440-af13-4885-b4f4-5659dda161be · outbound

This paper cites safe completion.

ContinualFlow: Learning and Unlearning with Neural Flow Matching safe completion

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:50:59.058153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2210aac9-a33d-4179-916a-c3e53f533501 · outbound

This paper cites Flow Matching Toward Soft Mass-Subtracted Distributions.

ContinualFlow: Learning and Unlearning with Neural Flow Matching Flow Matching Toward Soft Mass-Subtracted Distributions

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:50:59.031266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6d90708b-6766-43c1-a8f1-bf04ff0cdc98 · outbound

This paper cites Generation from the full distribution (left), and after suppressing all classes except automobile (middle) and airplane (right), which are assigned low energy.

ContinualFlow: Learning and Unlearning with Neural Flow Matching Generation from the full distribution (left), and after suppressing all classes except automobile (middle) and airplane (right), which are assigned low energy

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:50:58.962518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c8263a1d-8bc7-4d51-a34a-a051e8649b12 · outbound

This paper cites ReLearn: Unlearning via Learning for Large Language Models.

ContinualFlow: Learning and Unlearning with Neural Flow Matching ReLearn: Unlearning via Learning for Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T18:50:58.754179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53ecae73-e7cc-4e9c-ba89-0e4e5738b062 · outbound

This paper cites 0”, andDforget includes digits “1–9.

ContinualFlow: Learning and Unlearning with Neural Flow Matching 0”, andDforget includes digits “1–9

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:50:58.978083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 06eb6d7d-1da8-46bd-82d4-9b8c09c6ad02 · outbound

This paper cites an unresolved cited work.

ContinualFlow: Learning and Unlearning with Neural Flow Matching Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:50:59.017035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 73e866cf-4c84-4bfa-a355-b6bdc91d934c · outbound

This paper cites (8) OT-CFM Justification.

ContinualFlow: Learning and Unlearning with Neural Flow Matching (8) OT-CFM Justification

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:50:59.004183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bbbce51d-1bb8-41b2-85ee-2a9b0be627b6 · outbound

This paper cites The right panel illustrates the learned and unlearned trajectories for four 2D benchmarks: Circles, Moons, 6 Gaussians, and Checkerboard.

ContinualFlow: Learning and Unlearning with Neural Flow Matching The right panel illustrates the learned and unlearned trajectories for four 2D benchmarks: Circles, Moons, 6 Gaussians, and Checkerboard

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:50:58.949327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation debf5e72-b871-4c2c-8f25-208c90db96cd · outbound

This paper cites F., Choquette-Choo, C.

ContinualFlow: Learning and Unlearning with Neural Flow Matching F., Choquette-Choo, C

Reference 2005

Resolution: unresolved; no resolver link, observed 2026-08-15T18:50:58.735917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3094703-de4e-4eb0-b1e1-ee3eda30069d · outbound

This paper cites DEPN: Detecting and editing privacy neurons in pretrained language models.

ContinualFlow: Learning and Unlearning with Neural Flow Matching DEPN: Detecting and editing privacy neurons in pretrained language models

Reference 2011

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:50:59.083327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 69515aa7-9060-4a45-9c74-bba3a9bf6723 · outbound

This paper cites However, these methods typically address fixed, one-shot unlearning tasks and rely on access to the data to be removed.

ContinualFlow: Learning and Unlearning with Neural Flow Matching However, these methods typically address fixed, one-shot unlearning tasks and rely on access to the data to be removed

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:50:59.045109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bc59c30b-7e0c-4507-acf4-27f4164606a9 · outbound

This paper cites Empirically, this yields competitive flows and maintains convergence benefits without incurring the overhead of solving full OT across the dataset.

ContinualFlow: Learning and Unlearning with Neural Flow Matching Empirically, this yields competitive flows and maintains convergence benefits without incurring the overhead of solving full OT across the dataset

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:50:58.992064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a689d407-a64f-4bbe-9208-b03cd73ff375 · outbound

This paper cites Continual Unlearning for Foundational Text-to-Image Models without Generalization Erosion.

ContinualFlow: Learning and Unlearning with Neural Flow Matching Continual Unlearning for Foundational Text-to-Image Models without Generalization Erosion

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-15T18:50:58.740399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5fba5ee-856a-4004-af3a-e3ac1c5571dc · outbound

This paper cites an unresolved cited work.

ContinualFlow: Learning and Unlearning with Neural Flow Matching Unresolved cited work

Reference 2024

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:50:59.069979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 289ee234-c5c4-4fec-a9a7-0cff63af70ea · outbound

This paper cites Improving and generalizing flow-based generative models with minibatch optimal transport.

ContinualFlow: Learning and Unlearning with Neural Flow Matching Improving and generalizing flow-based generative models with minibatch optimal transport

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-15T18:50:58.745084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.