Pith. sign in

Paper Citation Record · LEDGER

Towards Robust Unsupervised Attention Prediction in Autonomous Driving

As of 18 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2501.15045.

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

pith.paper-citation-record.v1
2501.15045 v2

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:48:06.943935Z

measured 51 of 51 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

51 of 51 outbound references displayed

  • verified exact0
  • verified fuzzy50
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d816fbee-16af-4531-8104-19d21e037bf7 · outbound

This paper cites Medirl: Predicting the visual attention of drivers via maximum entropy deep inverse reinforcement learning.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Medirl: Predicting the visual attention of drivers via maximum entropy deep inverse reinforcement learning

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.627735Z

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=2026-08-10T14:48:06.741058Z digest=sha256:a3b1bfc72eca86c53086acfe9379189f27fbc299d59a3d65185743f269a5387a

Observation 6dfe6467-b3ac-41cc-97bb-cbba08fb480d · outbound

This paper cites ” looking at the right stuff”-guided semantic-gaze for autonomous driving.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving ” looking at the right stuff”-guided semantic-gaze for autonomous driving

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.616391Z

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=2026-08-10T14:48:06.745947Z digest=sha256:f75d3d538deb6b407af9c44e34b1e120ef231456caf1ca0acf3ea38f4d8f3524

Observation 00b06bac-d386-4844-87a0-3c5fd4b58407 · outbound

This paper cites Ex- plainable object-induced action decision for autonomous vehicles.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Ex- plainable object-induced action decision for autonomous vehicles

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.604257Z

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=2026-08-10T14:48:06.749901Z digest=sha256:9850c1c54a507ce40829fa29224914ff4e77bc3e6b8383410696cc58b483ea6a

Observation 5807d3aa-f648-4aa9-a380-9895fe6b5b97 · outbound

This paper cites Stc-gan: Spatio-temporally coupled generative adversarial networks for predictive scene parsing.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Stc-gan: Spatio-temporally coupled generative adversarial networks for predictive scene parsing

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.592972Z

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=2026-08-10T14:48:06.754816Z digest=sha256:70906be7496a0dc6d48a6129a0292e42756cb204a7b970cc71640a35d5e7505f

Observation 960529d4-869b-414a-afd7-2111f6bfb285 · outbound

This paper cites Ke- gan: Knowledge embedded generative adversarial net- works for semi-supervised scene parsing.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Ke- gan: Knowledge embedded generative adversarial net- works for semi-supervised scene parsing

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.580959Z

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=2026-08-10T14:48:06.758872Z digest=sha256:66b01c6e4476a248ef4f9674e0efe17c033a180223e832ca19dfe1338901332a

Observation 050e8f17-bb74-4bc6-82f2-a9b1c35a8fd2 · outbound

This paper cites What uncertainties do we need in bayesian deep learning for computer vision? Adv.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving What uncertainties do we need in bayesian deep learning for computer vision? Adv

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.569317Z

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=2026-08-10T14:48:06.762760Z digest=sha256:d28fb03b60841b4408a13393dbda37961df29c0d87626f1673a5b587ae2f580c

Observation 8539dd06-7cea-442f-bfa7-7b7b441337ef · outbound

This paper cites Predicting the driver’s focus of attention: the dr (eye) ve project.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Predicting the driver’s focus of attention: the dr (eye) ve project

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.558572Z

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=2026-08-10T14:48:06.767137Z digest=sha256:1886abf582076e1717dbf93b2e6a83249b7c5cb155a03911fdf7220c9953270c

Observation 85fca595-6dbc-4484-bbdb-724c940f9813 · outbound

This paper cites Predicting driver attention in critical situations.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Predicting driver attention in critical situations

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.546908Z

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=2026-08-10T14:48:06.770843Z digest=sha256:75964c6c9db35361fca5daac25d1638a472b0a7225ea4ab9369058864e5abbc0

Observation 492cfc0a-d5e2-4984-8266-778909dc5d4c · outbound

This paper cites Dr (eye) ve: a dataset for attention-based tasks with applications to autonomous and assisted driving.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Dr (eye) ve: a dataset for attention-based tasks with applications to autonomous and assisted driving

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.535805Z

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=2026-08-10T14:48:06.774690Z digest=sha256:2076af35d143a9b4d6276456c5429551e6feb46e2ec93b4e64935c827b85427f

Observation 2d686d4a-0b2b-4d42-861f-829e6fbb3f83 · outbound

This paper cites Dada: Driver attention prediction in driving accident scenarios.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Dada: Driver attention prediction in driving accident scenarios

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.524778Z

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=2026-08-10T14:48:06.778406Z digest=sha256:1eed9ed2bcc3f765df64d1c60329be9f150638c58565a36cf402cd1cee9451cb

Observation 3d864d5d-04c0-4dde-80a3-210fcebbdcb5 · outbound

This paper cites Advisable learning for self-driving vehicles by internalizing observation-to-action rules.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Advisable learning for self-driving vehicles by internalizing observation-to-action rules

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.512831Z

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=2026-08-10T14:48:06.781913Z digest=sha256:09f2a4959153d210c623090bf2aa5037a98ca4daf5c33e834b5f1c818e3f01d9

Observation 7e560456-5234-468a-ad63-0e55a0f41f60 · outbound

This paper cites Deep learning-based robust positioning for all-weather autonomous driving.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Deep learning-based robust positioning for all-weather autonomous driving

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.499597Z

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=2026-08-10T14:48:06.785342Z digest=sha256:3c2bb3084696c5d48cc03b10ba2766ce7d967782927e788c042856def46cf20c

Observation 00f27f50-99a6-44c3-8077-f4b9eb016a72 · outbound

This paper cites Benchmarking neural network robustness to common corruptions and perturbations.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Benchmarking neural network robustness to common corruptions and perturbations

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.486727Z

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=2026-08-10T14:48:06.789402Z digest=sha256:a529a94470fe0f9a7ee4bbb64b4f1fdc79b551afeda8237bd906e90abb9f2fa0

Observation 37508d65-8223-4ca7-86d1-e5b7b80981de · outbound

This paper cites When human pose estimation meets robustness: Adversarial algorithms and benchmarks.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving When human pose estimation meets robustness: Adversarial algorithms and benchmarks

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.473540Z

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=2026-08-10T14:48:06.793878Z digest=sha256:ea64963665c548179bcb48381ad8b1905c86a7a4a5772f20dc82015f4d6e322e

Observation b2556238-85cb-49b5-a0a4-e583ac07f861 · outbound

This paper cites Contrastive adaptation network for unsu- pervised domain adaptation.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Contrastive adaptation network for unsu- pervised domain adaptation

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.461583Z

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=2026-08-10T14:48:06.798091Z digest=sha256:48daff58d4e3d994376a4473f81960dfea1dfdcfe34d52e41b70196ffa1ba3d4

Observation f10d2748-9f5d-4958-a311-ea439bf380fe · outbound

This paper cites Mask r-cnn.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Mask r-cnn

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.449243Z

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=2026-08-10T14:48:06.802048Z digest=sha256:19ce7427b1b5f8f1d13ee4aefa56c4e51ccb4d2617e73b2959af6f121b2af604

Observation e458d587-ac7c-4d2d-bc50-36b083c7d535 · outbound

This paper cites Microsoft coco: Common objects in context.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Microsoft coco: Common objects in context

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.436909Z

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=2026-08-10T14:48:06.805650Z digest=sha256:e80b25a5672dacda7a54660f3bc1eeb4adf910347c792850bf697f6cca526101

Observation 3860eeb4-aa82-4b03-84c1-f692fba48dc0 · outbound

This paper cites Unpaired image-to-image translation using cycle- consistent adversarial networks.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Unpaired image-to-image translation using cycle- consistent adversarial networks

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.423300Z

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=2026-08-10T14:48:06.809119Z digest=sha256:cf9249f4d9535fd742f2133976511108691ffb3001c7138762d5db722871916b

Observation 341ae095-9508-4778-805a-dfa5dbd19d9e · outbound

This paper cites Unsupervised self-driving attention prediction via uncertainty mining and knowledge embedding.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Unsupervised self-driving attention prediction via uncertainty mining and knowledge embedding

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.410656Z

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=2026-08-10T14:48:06.812917Z digest=sha256:2127aa7160b6069dbd52ba7c80d38ecf7dd50eaf2f8830b582c75c4213049ddb

Observation 1b2ece43-9d71-4f02-85fb-45a96f44dc29 · outbound

This paper cites Fblnet: Feed- back loop network for driver attention prediction.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Fblnet: Feed- back loop network for driver attention prediction

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.397039Z

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=2026-08-10T14:48:06.816367Z digest=sha256:639746e1e8fab4bed5d2be6700672d4e6cab0f06849758dfce509b5265ca6c7b

Observation 4d045153-5b36-4942-bf8d-9f555612f5dc · outbound

This paper cites Tased-net: Temporally- aggregating spatial encoder-decoder network for video saliency detection.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Tased-net: Temporally- aggregating spatial encoder-decoder network for video saliency detection

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.383429Z

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=2026-08-10T14:48:06.821404Z digest=sha256:bd29cf4b83c25ae20044206421e8aa2e06d481fdcae1195fc967fb4231f3283a

Observation 97c1e015-cc1a-48b1-a86c-d954421cb8e0 · outbound

This paper cites Unified image and video saliency modeling.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Unified image and video saliency modeling

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.369776Z

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=2026-08-10T14:48:06.825291Z digest=sha256:1b9e6eabdf814d55a83a5eb0eece2077343bf9cdf407f2b53a2e0595d4d38c48

Observation 9b36f971-c31b-44bf-8c2d-22b911a26ba4 · outbound

This paper cites Deep cropping via attention box prediction and aesthetics assessment.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Deep cropping via attention box prediction and aesthetics assessment

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.358500Z

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=2026-08-10T14:48:06.829131Z digest=sha256:07ff3f0cc213b14ba49c66d5027f6b9f95d1c0891acf5bb4c9bb9a8e321a7d49

Observation fd8f2424-4491-4efd-a67b-ce375e7bb798 · outbound

This paper cites Attentive relational networks for mapping images to scene graphs.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Attentive relational networks for mapping images to scene graphs

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.346524Z

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=2026-08-10T14:48:06.832658Z digest=sha256:8b452261007cf7903f61129cae7bc1f83f7bbdb1ace01e9511ce6cbdf6c7376f

Observation ad1cf0da-8a93-44c7-bd79-6b732a18ebe0 · outbound

This paper cites Semantics-aware spatial-temporal binaries for cross- modal video retrieval.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Semantics-aware spatial-temporal binaries for cross- modal video retrieval

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.331967Z

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=2026-08-10T14:48:06.836245Z digest=sha256:f7650a3df9b7ebf5302d934799b46911b4b15e3eaa3420214cb34c504c11e93d

Observation caae6000-0c42-4877-9098-826a722b6285 · outbound

This paper cites stagnet: An attentive semantic rnn for group activity recognition.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving stagnet: An attentive semantic rnn for group activity recognition

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.313905Z

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=2026-08-10T14:48:06.840783Z digest=sha256:a1bbdc474bb624aaaac29d7623d8a3355ff8b2f93a47c6e5e9433e710341b7d4

Observation d72995e2-a476-4f51-be18-f4eeb6901a2b · outbound

This paper cites Bbs-net: Rgb-d salient object detection with a bifurcated backbone strategy network.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Bbs-net: Rgb-d salient object detection with a bifurcated backbone strategy network

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.301048Z

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=2026-08-10T14:48:06.844551Z digest=sha256:af8761161bfe18be9b743fafe90443db0dfe5051b1ff66c175d90a462aa9cca4

Observation 22f16601-2889-45b1-85b7-9c89151774a3 · outbound

This paper cites Pyramid grafting network for one-stage high resolution saliency detection.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Pyramid grafting network for one-stage high resolution saliency detection

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.288278Z

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=2026-08-10T14:48:06.848383Z digest=sha256:dcfa0f6e47c17be75cf64985eb6bdf81251497b4d1035ab55be071a15fbd6bdb

Observation 91a538f9-64f9-426d-8653-529972b39495 · outbound

This paper cites Robust perception and precise segmentation for scribble-supervised rgb-d saliency detection.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Robust perception and precise segmentation for scribble-supervised rgb-d saliency detection

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.275380Z

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=2026-08-10T14:48:06.853128Z digest=sha256:fa1446435cb63d6b7e1f1c6a626db50454c3b47bcea77a01a790ec3d9dc473fd

Observation db93df99-880b-4132-94c4-7349f5e95624 · outbound

This paper cites Salicon: Saliency in context.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Salicon: Saliency in context

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.262467Z

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=2026-08-10T14:48:06.856899Z digest=sha256:997e44149738da65af3dc2c9887cd2e5fef1f215cf37688d10d001a66814117c

Observation 27595c2f-7ed5-4aeb-9cd0-0385a21bff05 · outbound

This paper cites Revisiting video saliency: A large- scale benchmark and a new model.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Revisiting video saliency: A large- scale benchmark and a new model

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.249999Z

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=2026-08-10T14:48:06.860518Z digest=sha256:34b27e36c427408b009d1e9c6a2e6c066dd25ad41b75b9f2ebf03890e533e2a2

Observation 1055c2c6-b5a6-4779-9cc1-d874eed0c039 · outbound

This paper cites A deep multi-level network for saliency prediction.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving A deep multi-level network for saliency prediction

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.235091Z

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=2026-08-10T14:48:06.865235Z digest=sha256:fe3f68008c44c6a96d9ca60e85b86ab970d2f23e73e2c5bde994d2dc5eba5f14

Observation 3b42e499-059f-453e-9661-bd02080fb216 · outbound

This paper cites Predicting human eye fixations via an lstm-based saliency attentive model.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Predicting human eye fixations via an lstm-based saliency attentive model

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.221964Z

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=2026-08-10T14:48:06.869286Z digest=sha256:cd3b757e4994a0a0601b65801e7dca64bf1cea764bd5d66f4682c90f3e007cc1

Observation 9e43cfe6-3516-4427-95a6-d2e6dd604d8f · outbound

This paper cites Mobilevit: Light-weight, general-purpose, and mobile-friendly vision transformer.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Mobilevit: Light-weight, general-purpose, and mobile-friendly vision transformer

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.209342Z

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=2026-08-10T14:48:06.873543Z digest=sha256:f20b4695955789e9b26895e56a6d2f6e781d50b186773168503e5b8d9f17019a

Observation fafee16d-69b9-4651-a129-cb1842df478a · outbound

This paper cites Laplace redux-effortless bayesian deep learning.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Laplace redux-effortless bayesian deep learning

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.193551Z

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=2026-08-10T14:48:06.877444Z digest=sha256:f9ef42840a9ec30b4af4f6c6746f78dea50562ca45d0a49185915d67812f598f

Observation 3ad56b3f-7dac-4e6d-878f-eb693fae6b41 · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Dropout as a bayesian approximation: Representing model uncertainty in deep learning

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.180422Z

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=2026-08-10T14:48:06.881111Z digest=sha256:494900e6cf1ac2e2c2ae47e29428bb5446ca834f975d2852b949b17a9813bbaf

Observation dbc738ac-7cdf-4c47-b553-a3c0a070a3c0 · outbound

This paper cites Multi- task learning using uncertainty to weigh losses for scene geometry and semantics.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Multi- task learning using uncertainty to weigh losses for scene geometry and semantics

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.167502Z

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=2026-08-10T14:48:06.884788Z digest=sha256:05320d6c58f51a5eb9148351df7fd59c77e16e390d154181e4a809d18624f43f

Observation 3bd577b7-c0e0-491d-ae47-2339bd42bbeb · outbound

This paper cites Transmix: Attend to mix for vision transformers.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Transmix: Attend to mix for vision transformers

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.154783Z

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=2026-08-10T14:48:06.889491Z digest=sha256:06d231ae306b3c4ecf801b4da87fdf2168854ec18f1ef2632355ea46c8643bc0

Observation b4a9054b-f4cd-498b-84f5-c943cbe88ca0 · outbound

This paper cites mixup: Beyond empirical risk mini- mization.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving mixup: Beyond empirical risk mini- mization

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.141234Z

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=2026-08-10T14:48:06.893485Z digest=sha256:92122905e88dc80508896d2d1b818452eb64c7d67840de53e2d4ffff9fb645d3

Observation 2d2b38ad-0c5c-4277-bae3-0ea0570542a5 · outbound

This paper cites Using mixup as a regularizer can surprisingly improve accuracy & out-of-distribution ro- bustness.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Using mixup as a regularizer can surprisingly improve accuracy & out-of-distribution ro- bustness

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.126501Z

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=2026-08-10T14:48:06.897226Z digest=sha256:5a0d9b1ba863123fa0a662beb22400d1cc039685d21d976f32b60d226a225295

Observation 3b70bde4-1a3c-405c-a6b2-dcdbdaa15c0b · outbound

This paper cites Pyramid scene parsing network.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Pyramid scene parsing network

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.112205Z

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=2026-08-10T14:48:06.900885Z digest=sha256:85cbc3ab61ee239069aef6cf4278934d00085e063500c0f3d619006531c68f71

Observation cd21f9fa-b6ee-4647-8e62-aa2c2fd570e3 · outbound

This paper cites A unified framework for u-net design and analysis.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving A unified framework for u-net design and analysis

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.099502Z

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=2026-08-10T14:48:06.904443Z digest=sha256:b8b521c5717b10af288037517bb37c381cdf914a8ec8229b05aa3d44418eec8e

Observation a5ceabe3-6712-4dcb-a427-a91775744e15 · outbound

This paper cites Non-local neural networks.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Non-local neural networks

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.086314Z

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=2026-08-10T14:48:06.909298Z digest=sha256:28bb1fad09040914366b76d22f157708f2033cb0d20ee68ae3dcc89061c8586e

Observation d5a7fe7c-c950-4ddc-8171-967ab5d36446 · outbound

This paper cites Multi-source uncertainty mining for deep unsupervised saliency detection.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Multi-source uncertainty mining for deep unsupervised saliency detection

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.074314Z

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=2026-08-10T14:48:06.913215Z digest=sha256:0dd5cfe9957c71d7868c2eab55b15135dafb482f75be104fdb560dd03de9c1ff

Observation fe7d5656-4fe4-4b5b-ab06-f855612b79f2 · outbound

This paper cites Deep residual learning for image recognition.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Deep residual learning for image recognition

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.060537Z

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=2026-08-10T14:48:06.918204Z digest=sha256:79fa6fb7dfbbb08e5cd3b3fedf7334467de86435f065494650a8c3021644328d

Observation 5054ae3c-8ffb-4912-bc8d-595408e6acbd · outbound

This paper cites Gated2depth: Real-time dense lidar from gated images.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Gated2depth: Real-time dense lidar from gated images

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.047157Z

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=2026-08-10T14:48:06.922158Z digest=sha256:4d319071254cb4f3702c4e3db566b5068ef14f4654b0642db64049fbd8843eb0

Observation 8736d69a-3f32-44ba-838d-f009b5b8ab8d · outbound

This paper cites DSOR: A Scalable Statistical Filter for Removing Falling Snow from LiDAR Point Clouds in Severe Winter Weather.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving DSOR: A Scalable Statistical Filter for Removing Falling Snow from LiDAR Point Clouds in Severe Winter Weather

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T14:48:06.927100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:48:06.927100Z digest=sha256:793cbcc5eb0920646034d382cbe722555f1413a799f4e447285ec53ab9e55151

Observation dba5820b-964a-4fb2-afa0-7c17b9067207 · outbound

This paper cites Picanet: Learning pixel-wise contextual attention for saliency de- tection.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Picanet: Learning pixel-wise contextual attention for saliency de- tection

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.033506Z

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=2026-08-10T14:48:06.931792Z digest=sha256:30252bf3da073e99cc227bc1c72c4cbbc904b648635a97c51059a0dc7aac6753

Observation 5d44e608-797c-46e6-939b-91bb0f92de38 · outbound

This paper cites What do different evaluation metrics tell us about saliency models? IEEE T rans.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving What do different evaluation metrics tell us about saliency models? IEEE T rans

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.019387Z

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=2026-08-10T14:48:06.935699Z digest=sha256:7f90b55df63050598fd938ef227ab7a8fb68e8be7d2987e6cdf6b7e84fc503cc

Observation 99be0395-8b2c-47fb-b199-f5f8fb4ed385 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Pytorch: An imperative style, high-performance deep learning library

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:07.006427Z

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=2026-08-10T14:48:06.939779Z digest=sha256:f3de5ca35ceec31f38db331d132fbc95e76aeca8a81efad3d3273b7f78b6d2de

Observation 1e5f8693-2692-4edf-829d-d63536dfb6ec · outbound

This paper cites Distill- ing the knowledge in a neural network.

Towards Robust Unsupervised Attention Prediction in Autonomous Driving Distill- ing the knowledge in a neural network

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:48:06.992586Z

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=2026-08-10T14:48:06.943935Z digest=sha256:40597878c462cf2922b5b4c7107252b036d6b50c0ed9b52250727fb25eeb01ec

Pith citing papers

No inbound Pith citation observations are available.