Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
NR-DFERNet: Noise-Robust Network for Dynamic Facial Expression Recognition
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2206.04975.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:41:13.868192Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T20:17:22.410885Z
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 cdf53b70-942b-4837-a620-b459d7c9cd1b · inbound
Recent Advances in Multimodal Affective Computing: An NLP Perspective cites this paper.
Recent Advances in Multimodal Affective Computing: An NLP Perspective NR-DFERNet: Noise-Robust Network for Dynamic Facial Expression Recognition
Reference 271
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T21:23:27.729784Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 317b2d5b-ccf1-44f3-b460-bbe7032a5bff · inbound
Action Unit Enhance Dynamic Facial Expression Recognition cites this paper.
Action Unit Enhance Dynamic Facial Expression Recognition NR-DFERNet: Noise-Robust Network for Dynamic Facial Expression Recognition
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:41:13.868192Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5c53bea4-72b1-4926-8ec7-ed45a3ceb9b8 · inbound
From Coarse to Nuanced: Cross-Modal Alignment of Fine-Grained Linguistic Cues and Visual Salient Regions for Dynamic Emotion Recognition cites this paper.
From Coarse to Nuanced: Cross-Modal Alignment of Fine-Grained Linguistic Cues and Visual Salient Regions for Dynamic Emotion Recognition NR-DFERNet: Noise-Robust Network for Dynamic Facial Expression Recognition
Reference 65
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:08:58.322047Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 625d899b-dd17-4890-abd4-bbc18caacd69 · inbound
Text-guided Weakly Supervised Framework for Dynamic Facial Expression Recognition cites this paper.
Text-guided Weakly Supervised Framework for Dynamic Facial Expression Recognition NR-DFERNet: Noise-Robust Network for Dynamic Facial Expression Recognition
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:22:01.726119Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e68b8038-11c6-4d0f-9b09-c9f5ca6f6fc0 · inbound
Bidirectional Learning of Facial Action Units and Expressions via Structured Semantic Mapping across Heterogeneous Datasets cites this paper.
Bidirectional Learning of Facial Action Units and Expressions via Structured Semantic Mapping across Heterogeneous Datasets NR-DFERNet: Noise-Robust Network for Dynamic Facial Expression Recognition
Reference 73
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T09:16:00.964032Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1d35fb8e-457c-4cd3-9738-d7a721c5a3a6 · inbound
Cognition-Inspired Dual-Stream Semantic Enhancement for Vision-Based Dynamic Emotion Modeling cites this paper.
Cognition-Inspired Dual-Stream Semantic Enhancement for Vision-Based Dynamic Emotion Modeling NR-DFERNet: Noise-Robust Network for Dynamic Facial Expression Recognition
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T11:26:03.062346Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3eee09b2-c98a-4223-b04f-6c2cbf287f2c · inbound
Beyond Universality: The GCC-FER Dataset and Culture-Aware Adaptation for Dynamic Facial Expression Recognition cites this paper.
Beyond Universality: The GCC-FER Dataset and Culture-Aware Adaptation for Dynamic Facial Expression Recognition NR-DFERNet: Noise-Robust Network for Dynamic Facial Expression Recognition
Reference 66
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T20:17:22.412300Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c5f3c006-8ad5-4e65-b523-27cbbf0a1a3d · inbound
Reweighting Framewise Attention in Video Transformers for Facial Expression Understanding cites this paper.
Reweighting Framewise Attention in Video Transformers for Facial Expression Understanding NR-DFERNet: Noise-Robust Network for Dynamic Facial Expression Recognition
Reference 33
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-30T13:34:41.193430Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4d55def9-e991-4cf8-85d9-26b8e08de0f0 · inbound
Reweighting Framewise Attention in Video Transformers for Facial Expression Understanding cites this paper.
Reweighting Framewise Attention in Video Transformers for Facial Expression Understanding NR-DFERNet: Noise-Robust Network for Dynamic Facial Expression Recognition
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T10:31:49.351169Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.