Paper Citation Record · LEDGER

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model

As of 15 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2411.10863.

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

pith.paper-citation-record.v1
2411.10863 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:18:16.045848Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

28 of 28 outbound references displayed

verified exact3
verified fuzzy13
unresolved12
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 188d6a9c-3f3d-4a69-ac34-c8beb0b62bad · outbound

This paper cites Facial expression recognition using residual masking network,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Facial expression recognition using residual masking network,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:18:16.260880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c64d7128-8b40-4ef0-9305-39c35e84b894 · outbound

This paper cites A dual-direction attention mixed feature network for facial expression recognition,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model A dual-direction attention mixed feature network for facial expression recognition,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:18:16.253589Z

Source-reported events for the cited work

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Observation f074c2d2-bca8-4615-86c4-1e80144744cb · outbound

This paper cites Mobilefacenets: Efficient cnns for accurate real-time face verification on mobile devices,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Mobilefacenets: Efficient cnns for accurate real-time face verification on mobile devices,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:18:16.245946Z

Source-reported events for the cited work

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Observation 05bd0d5d-8446-454d-92d8-e1447d6527a3 · outbound

This paper cites POSTER++: A simpler and stronger facial expression recognition network.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model POSTER++: A simpler and stronger facial expression recognition network

Reference 4

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Source-reported events for the cited work

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Observation 381a925c-7d28-4258-9f33-a51c8d06997c · outbound

This paper cites From Static to Dynamic: Adapting Landmark-Aware Image Models for Facial Expression Recognition in Videos.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model From Static to Dynamic: Adapting Landmark-Aware Image Models for Facial Expression Recognition in Videos

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:18:16.136849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7bc173d2-335b-4261-b7a6-57ae2c49a261 · outbound

This paper cites Improved classification for pneumonia detection using transfer learning with gan based synthetic image augmentation,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Improved classification for pneumonia detection using transfer learning with gan based synthetic image augmentation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:18:16.237759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8677ce1e-c0dc-4f62-a3f0-8d0615338945 · outbound

This paper cites Enhancement of image classification using transfer learning and gan-based synthetic data augmentation,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Enhancement of image classification using transfer learning and gan-based synthetic data augmentation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:18:16.229950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 06d3d63a-6488-4a59-9367-183d2d622ddd · outbound

This paper cites Diffusion-based data augmen- tation for skin disease classification: Impact across original medical datasets to fully synthetic images,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Diffusion-based data augmen- tation for skin disease classification: Impact across original medical datasets to fully synthetic images,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:18:16.222345Z

Source-reported events for the cited work

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Observation d6bf533c-c497-4f96-b3e3-ed8ccc311bda · outbound

This paper cites Is synthetic data from generative models ready for image recognition?.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Is synthetic data from generative models ready for image recognition?

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T19:18:15.990889Z

Source-reported events for the cited work

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Observation a40766a9-185b-4e52-a326-acda35b002de · outbound

This paper cites Spatial deep feature augmentation technique for fer using genetic algorithm,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Spatial deep feature augmentation technique for fer using genetic algorithm,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:18:16.214445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e39518fa-f7b3-4809-a340-bc4a968a9048 · outbound

This paper cites ResEmoteNet: Bridging Accuracy and Loss Reduction in Facial Emotion Recognition.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model ResEmoteNet: Bridging Accuracy and Loss Reduction in Facial Emotion Recognition

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T19:18:15.996977Z

Source-reported events for the cited work

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Observation a260df1e-f3ec-405f-8b1a-feb108d0a2b2 · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model High- resolution image synthesis with latent diffusion models,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T19:18:16.000687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3d7606f-5df5-4409-ac15-3c76d6f391c5 · outbound

This paper cites Scaling rectified flow transformers for high-resolution image synthesis,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Scaling rectified flow transformers for high-resolution image synthesis,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:18:16.202036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation caa0af4e-2c72-4835-8352-5bdf1d563330 · outbound

This paper cites Progressive Distillation for Fast Sampling of Diffusion Models.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Progressive Distillation for Fast Sampling of Diffusion Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T19:18:16.006153Z

Source-reported events for the cited work

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Observation c3f784b1-ce69-4b51-bdea-67402d71591f · outbound

This paper cites LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T19:18:16.009092Z

Source-reported events for the cited work

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Observation 9a5d4e44-f1a0-4cfc-8327-d3fe79dea603 · outbound

This paper cites Scalable diffusion models with transformers,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Scalable diffusion models with transformers,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T19:18:16.012034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9bcab69-18e9-4866-9aea-a4f33015b173 · outbound

This paper cites Imagenet large scale visual recognition challenge,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Imagenet large scale visual recognition challenge,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T19:18:16.014597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cc33977-e9fc-44f4-b3a4-fbcd784e0fae · outbound

This paper cites Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:18:16.187120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b45a77ad-a7e7-46cd-926c-c60bd6daa93c · outbound

This paper cites Challenges in representation learning,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Challenges in representation learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:18:16.179588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9bf66abb-ca32-4bda-9e42-b6dfa3ca3fd0 · outbound

This paper cites Reliable crowdsourcing and deep locality- preserving learning for expression recognition in the wild,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Reliable crowdsourcing and deep locality- preserving learning for expression recognition in the wild,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:18:16.170928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 99e65b3e-1487-470a-9e53-364929f7314a · outbound

This paper cites An overview of gradient descent optimization algorithms.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model An overview of gradient descent optimization algorithms

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T19:18:16.026888Z

Source-reported events for the cited work

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Observation 00b1d178-5a9a-4427-8d1c-135549bb3fed · outbound

This paper cites Generalized cross entropy loss for training deep neural networks with noisy labels,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Generalized cross entropy loss for training deep neural networks with noisy labels,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T19:18:16.029657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de2e62e6-be69-4090-bcc3-0e717e522ef0 · outbound

This paper cites A Lightweight Attention-based Deep Network via Multi-Scale Feature Fusion for Multi-View Facial Expression Recognition.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model A Lightweight Attention-based Deep Network via Multi-Scale Feature Fusion for Multi-View Facial Expression Recognition

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:18:16.095448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation edc44ac7-c99b-4d74-94d9-6a6c5afc0237 · outbound

This paper cites Local learning with deep and handcrafted features for facial expression recognition,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Local learning with deep and handcrafted features for facial expression recognition,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:18:16.159282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0f9f9ea6-ba7f-4995-b0ef-694f7a05179d · outbound

This paper cites Cross-Task Multi-Branch Vision Transformer for Facial Expression and Mask Wearing Classification.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Cross-Task Multi-Branch Vision Transformer for Facial Expression and Mask Wearing Classification

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T19:18:16.037741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcb742a6-ff22-405b-88b0-c5990089ce36 · outbound

This paper cites Emonext: an adapted convnext for facial emotion recognition,.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Emonext: an adapted convnext for facial emotion recognition,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:18:16.151161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0895908b-791b-4d9c-b68f-06c80208dc0f · outbound

This paper cites MixCut:A Data Augmentation Method for Facial Expression Recognition.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model MixCut:A Data Augmentation Method for Facial Expression Recognition

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:18:16.078229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4a137ba6-cb5f-4fb1-9a02-6045624c67c6 · outbound

This paper cites Representation Learning and Identity Adversarial Training for Facial Behavior Understanding.

Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model Representation Learning and Identity Adversarial Training for Facial Behavior Understanding

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T19:18:16.045848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.