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Paper Citation Record · LEDGER

Towards Robust Unsupervised Attention Prediction in Autonomous Driving

As of 17 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

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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.

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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

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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.

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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

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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.

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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

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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.

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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

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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.

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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

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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.

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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

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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.

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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

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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.

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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

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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.

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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

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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.

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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

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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.

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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

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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.

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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

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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:bb616ac6dc079b2df6e5621522ffdfe77992ba46776db8976557780d7e15fd4a

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

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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.

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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

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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.

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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

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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.

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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

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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.

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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

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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:e395b7040f8da14e2f392bd83d072c2139f672b1da42df5377bbce02e5fb4556

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

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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:ccc169996e52692f84ec9bcb996cee04beaad783daed171855fb4ac54f4bc531

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

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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=sha256:5b5e472e4d2ec2f9a67a55c24458bb787bc9fecf2e339c992864b40bd3b20b9e

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

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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:ce6575d79562f781eb95509fa48d5a6f310bf7dd7c22c2da6c83a1c7d1c721f4

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

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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:ef1bd2d3e41ee5fc24602f2edae8ba989a3ffce5380af8c72ceea6231b934149

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

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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.

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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

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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.

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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

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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=sha256:9edc61c1c5997069ab116a5c7698950b0c1d39d839207b76681a353557aac7d1

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

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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=sha256:080f2c96d92c3eb4d09641ac913ef7cb952d395f0c240750021603d0defc8c07

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

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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:f4bf7fea3cf8f1771eaeb36692ee4a7103c85b65c10666db6e1cfad60ea0046a

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

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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:ed30ff6bd5300900d0a859d5005500419b2d5fa6293d5629b196e4492f4176c3

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

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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=sha256:67a84cad62205ea9808386cf9ed41c7b230abacbd077ef1afe3138a2cc216dee

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

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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=sha256:040580fda1ec70a072d34b6c300ceb4ceb510d8337fb8a499c5d8eedb2455048

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

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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=sha256:1db3d693921d81b933d3682bb4376f26b29975b650595084f643e79095655a36

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

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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:f82abf98004c6d3f0c48db84e30a99f50d2a25f6c5c10dd99cd5b0c5616d3841

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

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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=sha256:7e710643b91c62c3ba331484a42dfe0ac1189f3b8e62a7e422f59b2d7694eb5e

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

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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:e6c9e9736758dc1b11564fa9f5d727d179ca6d06b97112efa7e1a0b86ec55c77

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=sha256:4408f99abb3849bca01a7bd832cf0c5557da2a7ee983102bfb30d91467a8887a

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=sha256:9c75e72dfd24ef8c0f2eb6c8ec100c3994b968ed6c21d0103cb9ed508c2e36a6

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=sha256:2395b8ea922bb2a9618d28643af6e992eb6e6f25ab8ee3fa542ea1fdd16c075f

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=sha256:45b616ed1f2d66baf83cc8b518a4869c235f3fd88440ea05ab3275d971a9e9b8

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=sha256:824547d4a25dd1f2692d18ed98bfc1f2008d9398483c9ba70586c35938c823d8

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=sha256:82288dd5b1ae8e0aaed7c05c5d20c653987ebc37089b786aa7244ecdad17f671

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:acd08e1489bf685a707eefe7016ea8e2ea0dc6be1205a6d72f61b93aa488c7cc

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=sha256:864fe0589895e138a8bf5917120fc5329e843eb78d2b42e8277ed688d910ee84

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=sha256:6fa8b9407c02f425cd5e37e1b5aba117636129a1751c6368e4f72bd173285811

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:c9100f8ab0e7d05c5a628f8d99d0b34bd11a0a692fcc59fc0fff2388874fb6c6

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:b8a944824e94475e09435794e9ffe55da30b98d217f0654b8761b238d253443e

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=sha256:4601ebf7482ea4c0e186c43f5635f3d811c07068554d37b0473af5e0ffa2be5d

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:ed7dd0cd26f709a20bd3c2db3a9c4b4e5b474b7f7b74af2af8d18c416f7eac08

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:f78c9911b71a74cba45d81aa30aabf19d121b392b558d69c1afc49501930a6be

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=sha256:723ae6cb53dc85ee6387e3ee77996fa1347f432b7e1d789dcc08e4cd14d8e5a0

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:e32fd27463d9134c5198781aee289deb714414feae5627a46afa305de60f2c80

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=sha256:83ec15ebd4fe3876eb1b92807b242581da22935743c43ebf0eeb88af90989d85

Pith citing papers

No inbound Pith citation observations are available.