Pith. sign in

Paper Citation Record · LEDGER

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization

As of 17 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2412.03179.

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

pith.paper-citation-record.v1
2412.03179 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:47:07.326630Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

57 of 57 outbound references displayed

  • verified exact1
  • verified fuzzy46
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6e994f92-c9c6-437b-aba7-811bf2f50fc1 · outbound

This paper cites Multimae: Multi-modal multi-task masked autoen- coders, 2022.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Multimae: Multi-modal multi-task masked autoen- coders, 2022

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:13.152972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:05.554756Z digest=sha256:0d90689ddbdb479806f3ee2d3962baf2ad685456ac58f35c1869cb1489783bab

Observation 6da85bf7-9154-4a7e-a3e8-b75ecc6bab40 · outbound

This paper cites Exploring rela- tional context for multi-task dense prediction, 2021.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Exploring rela- tional context for multi-task dense prediction, 2021

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:13.033658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:05.575787Z digest=sha256:a8ed63e843dff5e4092fe9e0afe10b4654df066320d172910e14908ff51fbe03

Observation d58f806d-83e4-4c7c-a358-6e9c16010aee · outbound

This paper cites Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:12.874747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:05.604179Z digest=sha256:5c5d3ea0ac2967c6cd8a2c5c3928055a56a35746473a68908e6b164b02c0751d

Observation 4920812a-aeda-4271-8737-a84202411843 · outbound

This paper cites Schwing, Alexan- der Kirillov, and Rohit Girdhar.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Schwing, Alexan- der Kirillov, and Rohit Girdhar

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:12.715004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:05.632505Z digest=sha256:41d32483e435b5eaac0efffbe71059294307ddf01e06ab9560bf64229dafec17

Observation b96ba6b8-4c24-40b0-b895-75ba8ad164db · outbound

This paper cites Se- mantic image segmentation: Two decades of research, 2023.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Se- mantic image segmentation: Two decades of research, 2023

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:12.594901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:05.654834Z digest=sha256:8156687a08880618f49253b748876872cf127bc763742b94470a68f30a9b9249

Observation 30dc2116-42fe-46d0-8695-b9a427d78afc · outbound

This paper cites Everingham, L.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Everingham, L

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:12.499633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:05.694747Z digest=sha256:8928993a69bb24c96dd77400e55e74e1239af3f2fd54177c0820c3659b51fb4d

Observation 9e269e70-f6ae-4a5d-a409-71c247fbe5c8 · outbound

This paper cites When multi-task learning meets partial supervision: A com- puter vision review, 2024.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization When multi-task learning meets partial supervision: A com- puter vision review, 2024

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:12.376020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:05.728303Z digest=sha256:5c4099b185ece636589f9088d578d36bfc142bccf4482ad6bb399abe73059e47

Observation 2b77314c-2495-489e-9883-6008622b53fa · outbound

This paper cites NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-11T22:47:07.827759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:05.744815Z digest=sha256:3b817c6719c4b43c5f5433c96f6a17a92f8a3e38b55bb1fc5582f21d8edd7d1a

Observation a0413e93-549f-4f22-8a4a-ef9f9c585d0d · outbound

This paper cites R-cnns for pose estimation and action detec- tion, 2014.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization R-cnns for pose estimation and action detec- tion, 2014

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:12.256144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:05.774828Z digest=sha256:ab16459f32d5502630cc812e3bdab825b070e2c6ae333e2da2a1382f7fe114d6

Observation 1ae49d9c-b776-432f-99a0-58b462ab83a9 · outbound

This paper cites Dynamic task prioritization for multitask learning.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Dynamic task prioritization for multitask learning

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:12.160747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:05.814744Z digest=sha256:7f7803025045ebca9fb8ea1fb55809b7d73e6fa41a0d608cca5b98a5bd42df13

Observation a1aca202-042f-47e4-ad60-ba0e13d8397d · outbound

This paper cites Unit: Multimodal mul- titask learning with a unified transformer, 2021.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Unit: Multimodal mul- titask learning with a unified transformer, 2021

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:12.082708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:05.850460Z digest=sha256:3fd83de494a531105b2c78103dbd5332ad8ddec401a6f76e0fc068e31a743867

Observation b9f874fd-9d5f-498c-ac79-c89da709a029 · outbound

This paper cites Lau, and Thomas S.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Lau, and Thomas S

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:11.991255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:05.874745Z digest=sha256:c7e108d35156bb74209196e4095c88eff9c336c3c10cbf869090273b81e80efb

Observation 19eb5853-e83f-4c75-b825-49bf8113c940 · outbound

This paper cites Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T22:47:05.901104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:47:05.901104Z digest=sha256:89d27d1d2df0ad28dae16d4445da79388e0b5a40cba591c20bfc12d130045e72

Observation 6d0bbed8-f5c6-45d5-a07a-e2955dfa5930 · outbound

This paper cites Pushing the boundaries of boundary de- tection using deep learning, 2016.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Pushing the boundaries of boundary de- tection using deep learning, 2016

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:11.895634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:05.924738Z digest=sha256:7056305fd57a40eca1741cdfc10e6af35f0bc1876e0207c6165bad39a33973f8

Observation 5c3201ca-024b-4811-904c-43a0b0afc483 · outbound

This paper cites UberNet: Training a `Universal' Convolutional Neural Network for Low-, Mid-, and High-Level Vision using Diverse Datasets and Limited Memory.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization UberNet: Training a `Universal' Convolutional Neural Network for Low-, Mid-, and High-Level Vision using Diverse Datasets and Limited Memory

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T22:47:05.960476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:47:05.960476Z digest=sha256:6565a230401f3c1f9a38167ebf9107141f332167714536a5f8c901c7324a90c4

Observation f7b8eda0-6ce3-4c6a-bfcb-a1386624c087 · outbound

This paper cites Learning multi- ple pixelwise tasks based on loss scale balancing.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Learning multi- ple pixelwise tasks based on loss scale balancing

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:11.796856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:05.984752Z digest=sha256:8c2eaf5d206fc9cb72155dc1476384981013791775317dd4fc01e418027ea30b

Observation 6053291b-0779-4b32-b1d7-62f43bf5f8e3 · outbound

This paper cites Transformed dynamic feature pyramid for small object detection.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Transformed dynamic feature pyramid for small object detection

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:11.706427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.004737Z digest=sha256:ef7b69660266583628f23d399e0123eacb391185223d9d43ea7e27d93bf48b0f

Observation 56653743-8ea7-4ce0-b9e2-2d4ce429d96a · outbound

This paper cites Auxiliary tasks in multi- task learning, 2018.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Auxiliary tasks in multi- task learning, 2018

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:11.625300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.034817Z digest=sha256:25954661cf28a11749c60e50bd8455cb7f1b689f383593b16ad8b605a5b347b0

Observation dd83813c-7903-4484-a8d7-412be366cbbd · outbound

This paper cites an unresolved cited work.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-11T22:47:11.565116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.073299Z digest=sha256:f82649a729d199eaee25d82918460fde7babf8c0d81d117049275eb6f8b4dd7c

Observation 756843e4-23d3-44c9-9243-60782e124c02 · outbound

This paper cites Rethinking boundary detection in deep learning models for medical image segmentation, 2023.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Rethinking boundary detection in deep learning models for medical image segmentation, 2023

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:11.504748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.103690Z digest=sha256:7514d5f98b6fd71da1d791adf7a4ed59854fc9951efdbb335a83cc74eb8fd17e

Observation a26a99cb-74f7-48c3-8e90-80123f8aa882 · outbound

This paper cites End-to-End Multi-Task Learning with Attention.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization End-to-End Multi-Task Learning with Attention

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-11T22:47:06.122012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:47:06.122012Z digest=sha256:7fa3de57c852545b4394900816573703204fd7f0482dd5bde9a0660203614d62

Observation 13c2629d-1020-4b80-885b-cc1f0228faa1 · outbound

This paper cites Swin trans- former: Hierarchical vision transformer using shifted win- dows, 2021.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Swin trans- former: Hierarchical vision transformer using shifted win- dows, 2021

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:11.424968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.144750Z digest=sha256:d21a53b7da967a7eef565638c48d4b2b3cbc760a9f96a3b92ca94c11a3c152e2

Observation 4dc1f821-4a00-4a65-bd39-cb5e5da613fb · outbound

This paper cites Cross- task attention mechanism for dense multi-task learning,.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Cross- task attention mechanism for dense multi-task learning,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:11.324745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.170741Z digest=sha256:abd95c376e3464f8dadc0b371a8e152c3aa6e76b2e2590c5ba2e2440a7261a03

Observation 09aead47-97f8-4a1e-b39b-30793cb2a53c · outbound

This paper cites Decoupled weight decay regularization, 2019.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Decoupled weight decay regularization, 2019

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-11T22:47:06.194745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:47:06.194745Z digest=sha256:0b38908d5266eba71aa73b1da40cd084bcae20fa742702e0bfd2a8524b21c2d3

Observation 7ae86475-6967-45d8-bb55-d3d027e83534 · outbound

This paper cites an unresolved cited work.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-08-11T22:47:11.140163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.221186Z digest=sha256:29d4d9412e5ed88d719ab3dff1001c6fa51eac06a05489dac70238c9e1dd0aa3

Observation 30db888f-8742-4b13-ab1d-629ddc26f334 · outbound

This paper cites Image seg- mentation using deep learning: A survey, 2020.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Image seg- mentation using deep learning: A survey, 2020

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:11.038496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.255231Z digest=sha256:0c6e7398a52e5c346d13c7347ac40aa185a43d56bce11ea2c4aa89aa53ae0784

Observation b0aa0f03-de47-40eb-b185-b09e938af08c · outbound

This paper cites Cross-stitch Networks for Multi-task Learning.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Cross-stitch Networks for Multi-task Learning

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T22:47:06.285077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:47:06.285077Z digest=sha256:c84ff4d9f10a717ed77b32802b14e01c065ca246ae10f5df76f858e58d4abcee

Observation f06a2746-c4fd-44a2-905a-98c2b07be543 · outbound

This paper cites Indoor segmentation and support inference from rgbd images.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Indoor segmentation and support inference from rgbd images

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:10.942126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.334738Z digest=sha256:27b0215f2190e813e4c3bc8d199e9019cddd62215269604755dd879780d5f6ad

Observation a7e4521b-2587-4ace-ac6d-0993eb1394f6 · outbound

This paper cites An overview of multi-task learning in deep neural networks, 2017.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization An overview of multi-task learning in deep neural networks, 2017

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:10.851219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.384748Z digest=sha256:0b7e56bc9598051391995a7723c15d54c221c849ba757c0bf0fcbb1915d6d206

Observation d3f2dca9-32cb-402e-a747-3e1c53c58067 · outbound

This paper cites Latent multi-task architecture learning,.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Latent multi-task architecture learning,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:10.731077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.424743Z digest=sha256:844f8e30f0a8d2c2e9d0752057e8c0ae2a4fe05741e60f564d1ef1bca12ab103

Observation 9fd3fcba-4bc8-4191-8de4-e9c91981033a · outbound

This paper cites Rusu, Neil C.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Rusu, Neil C

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:10.535095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.474748Z digest=sha256:86cfabb800ecc4ebbb8e08ab95f29c99a149c422efbcfafe0807677fa4e37114

Observation d38cfd2f-80db-4e69-97d7-42c6f8979a52 · outbound

This paper cites an unresolved cited work.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-11T22:47:10.446828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.524747Z digest=sha256:1887859d62aa144b7474f477adf770106ca716146e575036c6a322afcf5b67dd

Observation 3b167a4b-0d78-4c50-8001-a9784173c267 · outbound

This paper cites Efficient multitask dense predictor via binarization, 2024.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Efficient multitask dense predictor via binarization, 2024

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:10.354749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.564740Z digest=sha256:75d49db0ce2796555cc52c380f52ec4aba91098360746f9fb404fc92bed49dc5

Observation 88d0b00c-c949-4afa-ab7b-cb63b9eb7b0a · outbound

This paper cites Learning to multi-task by active sampling,.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Learning to multi-task by active sampling,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:10.263131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.593260Z digest=sha256:e85c5dc2e22badc02b39602513d4b7306612580fa9fbe54378390cdfaebd8ea7

Observation 5b3de09f-4ded-4660-984d-9d3aec85deb2 · outbound

This paper cites Usb: Universal-scale object detection bench- mark, 2021.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Usb: Universal-scale object detection bench- mark, 2021

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:10.154849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.621461Z digest=sha256:de55f891338691344ecfd90154dd7e5462866c540b942aac8809dc56ae810fad

Observation 316e0546-348c-4279-890a-073472087e4a · outbound

This paper cites Indoor segmentation and support inference from rgbd images.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Indoor segmentation and support inference from rgbd images

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:10.074776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.644744Z digest=sha256:c73b1b9b6d7b493e419a42ae56d38a22d27d7d944524fc0e34e433dab2d11ccc

Observation c785fd1d-f5cf-48dc-9aee-8fa5c63f1061 · outbound

This paper cites Training data-efficient image transformers and distillation through at- tention, 2021.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Training data-efficient image transformers and distillation through at- tention, 2021

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:09.976649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.677857Z digest=sha256:3e4026d93d911f8a2a80b9f01485550058ee958c20556e079ea17239c4a8b4dc

Observation de0dfe7a-4490-43a3-9625-e3236cfee6a1 · outbound

This paper cites Multi-task learning for dense prediction tasks: A sur- vey.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Multi-task learning for dense prediction tasks: A sur- vey

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:09.884828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.717832Z digest=sha256:a62210d108af1009df1d47e90e0792fb352587562f675cdc9d7d01aa12d455d9

Observation f5356f05-4e71-46cd-be3d-61328b767274 · outbound

This paper cites Mti-net: Multi-scale task interaction networks for multi-task learning, 2020.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Mti-net: Multi-scale task interaction networks for multi-task learning, 2020

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:09.775199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.744895Z digest=sha256:f2d063e755e48acd4046355c8f1fc06acb32bb64950a25c0ded5bb7ddda8dc0e

Observation d9076cb1-f9d5-49ae-9ed6-5816aeeeee03 · outbound

This paper cites Internim- age: Exploring large-scale vision foundation models with deformable convolutions, 2022.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Internim- age: Exploring large-scale vision foundation models with deformable convolutions, 2022

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:09.534739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.784925Z digest=sha256:7466beba05a1c42bb578a96ad62d4c7a5d54535019ce9f6dcbe7bdd5fef10187

Observation be80829f-6691-4538-8a44-0e96455682b5 · outbound

This paper cites Pyra- mid vision transformer: A versatile backbone for dense pre- diction without convolutions, 2021.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Pyra- mid vision transformer: A versatile backbone for dense pre- diction without convolutions, 2021

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:09.356242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.814743Z digest=sha256:f9404c3050a18c84214311d49df05af4969257cc4b67043f42d2989000b47d28

Observation 05856433-5099-44b2-b9f9-73f10049ebfd · outbound

This paper cites PVT v2: Improved baselines with pyramid vision transformer.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization PVT v2: Improved baselines with pyramid vision transformer

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:09.284738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.854747Z digest=sha256:d2f1c0962c96c7d4e2f9d871d0f2588a835d9478e04d8b784972096743963209

Observation 66520c3d-0a95-4fe4-8d3e-0536f41758d5 · outbound

This paper cites Gradient vaccine: Investigating and improving multi-task optimization in massively multilingual models.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Gradient vaccine: Investigating and improving multi-task optimization in massively multilingual models

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:09.207033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.894746Z digest=sha256:c44f380efbe8f8c823852b050a345fb41cefd48c61fafb4d80c0aab75d256acf

Observation f4412664-11d0-44c6-bb00-dfd86c0f4ee2 · outbound

This paper cites Cbam: Convolutional block attention module, 2018.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Cbam: Convolutional block attention module, 2018

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-11T22:47:06.957795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:47:06.957795Z digest=sha256:ef9721e65a4bfbacd5a7292361d2f6fbf3469cd56a9feb08fa1df220ad178cb9

Observation 3071582b-90cd-4a03-b636-1b29efba0d6e · outbound

This paper cites Pad-net: Multi-tasks guided prediction-and-distillation net- work for simultaneous depth estimation and scene parsing,.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Pad-net: Multi-tasks guided prediction-and-distillation net- work for simultaneous depth estimation and scene parsing,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:09.001644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:06.974262Z digest=sha256:3cd7e0beb4ca283fbc72d4e645b0bb27e4813797b20830e79fab17350f08abbd

Observation 940cdf01-c110-44ee-98c0-5d57b992c833 · outbound

This paper cites Mtformer: Multi-task learning via transformer and cross-task reasoning.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Mtformer: Multi-task learning via transformer and cross-task reasoning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:08.823443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:07.005956Z digest=sha256:acbadce92034974c9c3541744dbfab2b4d0820e5f93f6840e0f5367c12f2c1a8

Observation 7ba9d275-7638-49e9-acb1-b547db21438c · outbound

This paper cites Demt: De- formable mixer transformer for multi-task learning of dense prediction, 2023.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Demt: De- formable mixer transformer for multi-task learning of dense prediction, 2023

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:08.654748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:07.031074Z digest=sha256:f94f16d7cf4a9f3488be2d2efc2a7fa791bf910edc74104f8e33e8d3f0779c2d

Observation d7b79ecd-dd80-4bd2-9d54-78d3e5766ada · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data, 2024.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Depth anything: Unleashing the power of large-scale unlabeled data, 2024

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:08.538836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:07.055260Z digest=sha256:02b9c2d14ce66d748437d35b019bd2a8e76acbda90494ec076d7f16291eadad6

Observation 23770d2a-6d36-46ff-9c15-ffc441eae5eb · outbound

This paper cites Multi-task dense prediction via mixture of low-rank experts, 2024.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Multi-task dense prediction via mixture of low-rank experts, 2024

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:08.436998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:07.094199Z digest=sha256:cb9a6be717d1be68d0180e2be5363c0191a4e949c2f5c8c2e047d55356edd043

Observation d81fce45-f2ba-45bf-a8e2-00d733cd16dd · outbound

This paper cites Invpt: Inverted pyramid multi-task transformer for dense scene understanding.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Invpt: Inverted pyramid multi-task transformer for dense scene understanding

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:08.344744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:07.130814Z digest=sha256:dd5d16e268f957ef8bb6c9a06d90eed3fb5cd9d716c62913124cc2f071a0bc35

Observation 3a1786be-0114-4e44-952f-5e704064e305 · outbound

This paper cites Taskprompter: Spatial-channel multi-task prompting for dense scene understanding.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Taskprompter: Spatial-channel multi-task prompting for dense scene understanding

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:08.227199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:07.160870Z digest=sha256:784ad97c05e248f8e50cea2937f43f6d3d7b60e72c33499fb14d2c888fb26ff0

Observation 539b0df1-ad6e-483f-a8d9-a27069b0cac4 · outbound

This paper cites Gradient surgery for multi-task learning, 2020.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Gradient surgery for multi-task learning, 2020

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:08.141058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:07.204746Z digest=sha256:abf24ff01eda2557ebc92357ef9aa121aa6cff655b3506d9faf8198ae7b71f6d

Observation a29f99ca-11d3-4891-aecd-337042b37f27 · outbound

This paper cites A survey on multi-task learn- ing.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization A survey on multi-task learn- ing

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:08.086816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:07.235898Z digest=sha256:9573296cb0dba5d8a76e8566c7729a4c396fce25a60823f424e16bf720075207

Observation 7ea28770-1cb1-4505-a7b0-e2bc3b889861 · outbound

This paper cites Pattern-affinitive propagation across depth, surface normal and semantic segmentation, 2019.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Pattern-affinitive propagation across depth, surface normal and semantic segmentation, 2019

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:08.042229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:07.254767Z digest=sha256:cfb78638808e4aca16d9b5ceb9a0082329fc5f8a7e12214f5be1b2edd1a70de1

Observation f2fecd18-cfd5-4dbd-99f4-a52a9ab84ff0 · outbound

This paper cites Semantic under- standing of scenes through the ade20k dataset, 2018.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Semantic under- standing of scenes through the ade20k dataset, 2018

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:07.995999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:07.274742Z digest=sha256:bf5971875869778e8c1d753fda124f74c1da2092f52cc1e839584d76d32e5b64

Observation e93976f2-df70-48ad-89f0-047b8f45a994 · outbound

This paper cites an unresolved cited work.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-11T22:47:07.943241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:07.294227Z digest=sha256:7f5e4cc13a7bb516f3565d7bf716b8a59a12a1592f8e68919c784cc4f0f495c0

Observation c4c2aa2c-5a95-4328-89a9-e05a89a8bf76 · outbound

This paper cites Vlprompt: Vision-language prompting for panoptic scene graph gener- ation, 2024.

Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization Vlprompt: Vision-language prompting for panoptic scene graph gener- ation, 2024

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:47:07.889128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T22:47:07.326630Z digest=sha256:32dec854be498dd73d90e4509b232e423e255aee5874875a4dfde08853244028

Pith citing papers

No inbound Pith citation observations are available.