Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-25T01:29:49.752455Z
Paper Citation Record · LEDGER
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning
As of 4 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:1907.03402.
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 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
43 of 43 outbound references displayed
- verified exact8
- verified fuzzy30
- unresolved5
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation a2c59b34-7889-4060-b24d-77d91b0874fc · outbound
This paper cites In Neural Networks , volume 64, pages 59 – 63.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning In Neural Networks , volume 64, pages 59 – 63
Reference 1
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 51c025d5-5a88-4bbb-babd-63ca31574221 · outbound
This paper cites Learning efficient object detection mod- els with knowledge distillation.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Learning efficient object detection mod- els with knowledge distillation
Reference 2
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 54d54502-37d1-475e-af41-c3100c4e23b1 · outbound
This paper cites Neil: Extracting visual knowledge from web data.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Neil: Extracting visual knowledge from web data
Reference 3
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 536dbd75-c69d-4727-b268-42d02e9e3ac3 · outbound
This paper cites Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks
Reference 4
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 15bea58c-4910-459f-a097-968ae2479da4 · outbound
This paper cites Stargan: Unified genera- tive adversarial networks for multi-domain image-to-image translation.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Stargan: Unified genera- tive adversarial networks for multi-domain image-to-image translation
Reference 5
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2b23989f-1f40-4736-ad4b-29effc290ab5 · outbound
This paper cites Facenet2expnet: Regularizing a deep face recognition net for expression recognition.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Facenet2expnet: Regularizing a deep face recognition net for expression recognition
Reference 6
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 797a433c-6207-4cfe-99aa-66c64667eaeb · outbound
This paper cites Eidinger, R.
Reference 7
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ff1d2126-2637-4f47-8bf4-901032181364 · outbound
This paper cites Object detection with discriminatively trained part-based models.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Object detection with discriminatively trained part-based models
Reference 8
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a3521ded-e457-4c4d-95c5-acf3ef6b207a · outbound
This paper cites Born Again Neural Networks.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Born Again Neural Networks
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T01:30:10.666336Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f2c9dde5-2c11-4366-93e8-26df621da1a0 · outbound
This paper cites Cross Modal Distillation for Supervision Transfer.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Cross Modal Distillation for Supervision Transfer
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T01:30:10.638729Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2bff6e37-0ebf-4824-a9e3-ff28be2bfff3 · outbound
This paper cites Distilling the knowledge in a neural network.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Distilling the knowledge in a neural network
Reference 11
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 17e9b969-ce5c-4930-86d5-fb6ce0c464c9 · outbound
This paper cites Hospedales, Neil Martin Robertson, and Yongxin Yang.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Hospedales, Neil Martin Robertson, and Yongxin Yang
Reference 12
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 543c56c4-5c35-411d-9fc8-5b969318b35b · outbound
This paper cites A Spatio-Temporal Descriptor Based on 3D-Gradients.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning A Spatio-Temporal Descriptor Based on 3D-Gradients
Reference 13
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2dc231b2-f773-4d66-bb4b-7fac821df580 · outbound
This paper cites Imagenet classification with deep convolutional neural net- works.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Imagenet classification with deep convolutional neural net- works
Reference 14
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e825b685-05a2-470e-842b-f581591a2331 · outbound
This paper cites Temporal Ensembling for Semi-Supervised Learning.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Temporal Ensembling for Semi-Supervised Learning
Reference 15
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1c7938f9-fbbe-47c2-aea8-2548cd137fdd · outbound
This paper cites Facial expression recog- nition with faster r-cnn.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Facial expression recog- nition with faster r-cnn
Reference 16
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d4ea2647-60ae-43cd-9184-29f753378252 · outbound
This paper cites an unresolved cited work.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Unresolved cited work
Reference 17
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5f8b17d9-502e-421b-868f-10d0fc0ea702 · outbound
This paper cites Deep Facial Expression Recognition: A Survey.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Deep Facial Expression Recognition: A Survey
Reference 18
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 53024f3f-70ff-48c0-9c27-19e0369ecde5 · outbound
This paper cites an unresolved cited work.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Unresolved cited work
Reference 19
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9145315c-7be2-4785-b236-a9b9b4626238 · outbound
This paper cites Lucey, J.
Reference 20
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c43159cc-503a-4efc-a299-7a8b887c483c · outbound
This paper cites Model compression via distillation and quantization.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Model compression via distillation and quantization
Reference 21
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a52deeab-c9f4-497d-824e-f6ab4388cbc6 · outbound
This paper cites Data Distillation: Towards Omni-Supervised Learning.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Data Distillation: Towards Omni-Supervised Learning
Reference 22
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2a44486c-1e28-4e0f-85cc-f5b4725f7e84 · outbound
This paper cites Semi-Supervised Learning with Ladder Networks.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Semi-Supervised Learning with Ladder Networks
Reference 23
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- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 66521a34-3ec2-438b-99b2-bda7b0221411 · outbound
This paper cites Cross-Domain Self-supervised Multi-task Feature Learning using Synthetic Imagery.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Cross-Domain Self-supervised Multi-task Feature Learning using Synthetic Imagery
Reference 24
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ff350253-2df1-4dd9-8ff9-f9cd99a1456c · outbound
This paper cites Ricanek and T.
Reference 25
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 28b5d12e-9bb0-4584-8f8b-549b601f68f9 · outbound
This paper cites Fitnets: Hints for thin deep nets.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Fitnets: Hints for thin deep nets
Reference 26
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 786b43a1-718f-48ff-a156-bebf523944ff · outbound
This paper cites Adapting visual category models to new domains.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Adapting visual category models to new domains
Reference 27
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 06eba38f-6345-4b44-a2c0-570fa45ab5ab · outbound
This paper cites an unresolved cited work.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Unresolved cited work
Reference 28
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 57d7232c-4199-4045-bb31-e94abf619e8e · outbound
This paper cites A survey on semi- supervised feature selection methods.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning A survey on semi- supervised feature selection methods
Reference 29
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 62d5f1a0-ceed-4046-af1d-dac3baacd08c · outbound
This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Very Deep Convolutional Networks for Large-Scale Image Recognition
Reference 30
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 972ef2b3-e651-4ec8-a3ac-2b372d439bef · outbound
This paper cites an unresolved cited work.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Unresolved cited work
Reference 31
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d267ab93-34c6-48bb-b786-a872861eca0c · outbound
This paper cites Mitra, Yangyan Li, and Leonidas Guibas.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Mitra, Yangyan Li, and Leonidas Guibas
Reference 32
- Resolution
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- raw_fallback, observed 2026-05-25T01:30:11.132186Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fb9160de-7fd8-4f2d-9ffc-5360766e61eb · outbound
This paper cites Deeply learned face representations are sparse, selective, and robust.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Deeply learned face representations are sparse, selective, and robust
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T01:30:11.217025Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5ae427e4-dc6b-46ef-ac63-14c8f062af13 · outbound
This paper cites Scalable, High-Quality Object Detection.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Scalable, High-Quality Object Detection
Reference 34
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T01:30:10.644525Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 872f71f4-6609-48b5-b61e-1146debff2ab · outbound
This paper cites Taini, G.
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T01:30:11.194444Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fabd1aef-c373-465b-b225-0b010a62905b · outbound
This paper cites Facial ex- pression recognition by de-expression residue learning.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Facial ex- pression recognition by de-expression residue learning
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T01:30:11.224667Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f41ef9d9-aafd-4a70-be53-c2f7bb79765b · outbound
This paper cites Unsupervised word sense disambiguation rivaling supervised methods.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Unsupervised word sense disambiguation rivaling supervised methods
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T01:30:11.128519Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e259b12c-92a5-4bd7-a322-355b83d7173f · outbound
This paper cites Paying more at- tention to attention: Improving the performance of convolu- tional neural networks via attention transfer.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Paying more at- tention to attention: Improving the performance of convolu- tional neural networks via attention transfer
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T01:30:11.179616Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8761cfdc-cd9f-4dab-8368-b1bb5b8d942c · outbound
This paper cites Facial expres- sion recognition with inconsistently annotated datasets.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Facial expres- sion recognition with inconsistently annotated datasets
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T01:30:11.206410Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0cd72e82-da95-401d-990f-80eb0d6eb994 · outbound
This paper cites Joint pose and expression modeling for facial expression recognition.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Joint pose and expression modeling for facial expression recognition
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T01:30:11.212981Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9db3281a-4661-42af-b54e-c3f97cd56d56 · outbound
This paper cites Facial landmark detection by deep multi-task learning.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Facial landmark detection by deep multi-task learning
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T01:30:11.121280Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1211337e-be52-437e-ae07-7ae3652b2c3b · outbound
This paper cites an unresolved cited work.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Unresolved cited work
Reference 42
- Resolution
- unresolved
- raw_fallback, observed 2026-05-25T01:30:11.199120Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c2f0eed2-3301-49fd-ba4e-b88a561b5c85 · outbound
This paper cites Semi-supervised learning literature survey.
Distill-2MD-MTL: Data Distillation based on Multi-Dataset Multi-Domain Multi-Task Frame Work to Solve Face Related Tasksks, Multi Task Learning, Semi-Supervised Learning Semi-supervised learning literature survey
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T01:30:11.202706Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Pith citing papers
No inbound Pith citation observations are available.