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Paper Citation Record · LEDGER

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss

As of 22 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2608.11205.

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

pith.paper-citation-record.v1
2608.11205 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:18:45.955865Z

measured 15 of 15 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 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

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  • verified fuzzy1
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dd5585ea-579e-4cbf-ae1a-260e31dc80d5 · outbound

This paper cites Flow Matching for Generative Modeling.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss Flow Matching for Generative Modeling

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 173d08d4-88f4-4b29-95a5-4e4a3a582478 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss DINOv2: Learning Robust Visual Features without Supervision

Reference 9

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source=pdf_text observed=2026-08-15T14:18:45.545419Z digest=sha256:5b8ce00c6f64af3227fee5a7727f6db871b89a31cff80f48774521e6fda78f19

Observation 5867df1e-1ad3-4a8d-ae4a-779552d85dd5 · outbound

This paper cites Fast high-resolution image synthesis with latent adversarial diffusion distillation.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss Fast high-resolution image synthesis with latent adversarial diffusion distillation

Reference 11

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raw_fallback, observed 2026-08-15T14:18:46.463790Z

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.

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Observation f559193b-c555-43ea-a599-759d6d80b4a7 · outbound

This paper cites Improved distribution matching distillation for fast image synthesis.Ad- vances in neural information processing systems, 37:47455–47487, 2024a.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss Improved distribution matching distillation for fast image synthesis.Ad- vances in neural information processing systems, 37:47455–47487, 2024a

Reference 14

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source=pdf_text observed=2026-08-15T14:18:45.950813Z digest=sha256:a410d63f391cf6dddfb83a1dee1cead856e0db69c9dc50b4d1d04f088db58d3b

Observation b4179dc1-5a9d-496a-8875-dfe8da79c88c · outbound

This paper cites Diffusion Transformers with Representation Autoencoders.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss Diffusion Transformers with Representation Autoencoders

Reference 15

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source=pdf_text observed=2026-08-15T14:18:45.955865Z digest=sha256:7bff08c381d858a0a1de89d27b45699e1101d67e469319738a907269c1742178

Observation 379aea10-a9e0-46cd-8486-74d7a35f1e3f · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss Score-Based Generative Modeling through Stochastic Differential Equations

Reference 2015

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:18:45.788299Z digest=sha256:93f4fee4b31ca95949030b5e092defc827225c79cac8a6b26c4207b664168448

Observation b3af3431-01ab-4e87-aefc-ac5b146ab298 · outbound

This paper cites MIND: Monge Inception Distance for Generative Models Evaluation.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss MIND: Monge Inception Distance for Generative Models Evaluation

Reference 2017

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source=pdf_text observed=2026-08-15T14:18:45.030759Z digest=sha256:4a54dea9c04b2aca83188b1e0bc2373436e96149f107325505539b76321fdb0c

Observation aa557ce6-b92c-4be7-bab9-da6c15bbe0d8 · outbound

This paper cites Large Scale GAN Training for High Fidelity Natural Image Synthesis.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 2018

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source=pdf_text observed=2026-08-15T14:18:45.164542Z digest=sha256:e7cc9e47bc83cf4ab169046372ea4175b14c9906fe4ca8d2222e6ce89e56df3d

Observation 2e0fba82-322f-43f8-9b0e-bf1617f720a9 · outbound

This paper cites Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models

Reference 2019

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source=pdf_text observed=2026-08-15T14:18:45.311287Z digest=sha256:4ff9d7e22597afee54e32a6b9a7259ab611395b04a1a67e281892cd710d57038

Observation 09e72b48-cb66-4e2c-b774-e92793343701 · outbound

This paper cites Image Generation Via Minimizing Fr\'echet Distance in Discriminator Feature Space.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss Image Generation Via Minimizing Fr\'echet Distance in Discriminator Feature Space

Reference 2021

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Observation 6bda5aed-63d4-446c-9fc4-70c8c8fdf617 · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 2022

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Observation f8a640ee-02bd-4701-b42a-f659c474d4d0 · outbound

This paper cites The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models

Reference 2023

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Unavailable: canonical work link unavailable.

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Observation 10361188-a01e-4ea5-a154-6d253d746eea · outbound

This paper cites Representation Fr\'echet Loss for Visual Generation.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss Representation Fr\'echet Loss for Visual Generation

Reference 2024

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source=pdf_text observed=2026-08-15T14:18:45.799220Z digest=sha256:47171363e4e49f28c5dad3167169e41084dbcbfc938af27ad7b31c29cfb07790

Observation 947af2ef-9b5d-4e76-8dae-1698323c3e38 · outbound

This paper cites One-step Latent-free Image Generation with Pixel Mean Flows.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss One-step Latent-free Image Generation with Pixel Mean Flows

Reference 2025

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source=pdf_text observed=2026-08-15T14:18:45.493576Z digest=sha256:95c935a5758f7195c0c3aa1042baad30320f25e71239eca7b281d1087e508246

Observation 9b4602da-775a-4714-aac2-a30638f5a471 · outbound

This paper cites Demystifying MMD GANs.

AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss Demystifying MMD GANs

Reference 2026

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Pith citing papers

No inbound Pith citation observations are available.