Pith. sign in

Paper Citation Record · LEDGER

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning

As of 11 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2608.06934.

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

pith.paper-citation-record.v1
2608.06934 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:06:13.804465Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

39 of 39 outbound references displayed

  • verified exact0
  • verified fuzzy33
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4239f637-aaff-4141-bfce-ea9db7449c95 · outbound

This paper cites Validation of Walk Score for estimating neighborhood walkability: An analysis of four US metropolitan areas,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Validation of Walk Score for estimating neighborhood walkability: An analysis of four US metropolitan areas,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.507966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.594698Z digest=sha256:a8c555f8eac754fd471c8a5cc4ec0efb52c398c78491726abb4e2fc0ec67bdb1

Observation 9fd30368-7b24-4467-b887-4651b2e58bda · outbound

This paper cites Social inequalities in neighborhood visual walkability: Using street view imagery and deep learning technologies to facilitate healthy city planning,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Social inequalities in neighborhood visual walkability: Using street view imagery and deep learning technologies to facilitate healthy city planning,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.489547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.602972Z digest=sha256:265f328e1acb88e50a1d8e0702aa057d1cba3061ad70ff9309334becd7f13cc7

Observation 0e226d1d-5c32-4f1d-89b7-abcacf5e795b · outbound

This paper cites How does pedestrian accessibility vary for different people? Development of a perceived user-specific accessibility measure for walking (PAW),.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning How does pedestrian accessibility vary for different people? Development of a perceived user-specific accessibility measure for walking (PAW),

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.470988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.610826Z digest=sha256:fe94956b06a09aa78dc67b07dd7451ab60efe410bbba26dab773b887ccf45aae

Observation dc158475-d66f-4def-9599-6a280169301d · outbound

This paper cites Understanding urban perception with visual data: A systematic review,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Understanding urban perception with visual data: A systematic review,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.453951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.618107Z digest=sha256:eba92352354162567b5745aaac4e613c3f7d8ab3efa08ae1700af254909080aa

Observation 9f0b25b5-1afb-4875-a28a-f9c2ad8cde93 · outbound

This paper cites Measuring visual walkability perception using panoramic street view images, virtual reality, and deep learning,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Measuring visual walkability perception using panoramic street view images, virtual reality, and deep learning,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.437274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.624946Z digest=sha256:dbf2ae5b28a3168a9bdd7467e65c21ba02ef91de6bb4a09f838b200262a16add

Observation d049e1b3-a541-4dcc-9965-1835055aa17e · outbound

This paper cites Global urban visual perception varies across demograph- ics and personalities,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Global urban visual perception varies across demograph- ics and personalities,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.419723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.630570Z digest=sha256:e4bf9373e04d84ee47bbfd12d0fd4acd061abe7a9926f25727ee258aa2fb0aa2

Observation 70cc77ab-2069-4dad-bb75-5c455092122d · outbound

This paper cites Geographic identity and perceptions of walkable space,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Geographic identity and perceptions of walkable space,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.403707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.636417Z digest=sha256:8e55b79ad9ffd5e5dd57288d55043e0312175a9b694f77c5dc47a0a35a9e6d88

Observation a5409875-d07b-4a80-b29a-d2440e8d2ac4 · outbound

This paper cites Translat- ing street view imagery to correct perspectives to enhance bikeability and walkability studies,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Translat- ing street view imagery to correct perspectives to enhance bikeability and walkability studies,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.386783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.641528Z digest=sha256:e7312bedeb08935fe87c1af492f61ad45c91d692fe3d9a1a19199e2c421ea31d

Observation 2a973ebc-38d3-45d9-b968-73c6d487489b · outbound

This paper cites Designing effective image-based surveys for urban visual perception,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Designing effective image-based surveys for urban visual perception,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.368206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.647643Z digest=sha256:3436bd3059230bcfd89a7b4741000e6b5b60520b54cebbcbdcd0bd5d043340d6

Observation 07c0d994-809c-4a88-ae65-2bd86c9440c1 · outbound

This paper cites Measuring the unmeasurable: Urban design qualities related to walkability,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Measuring the unmeasurable: Urban design qualities related to walkability,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.346106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.653106Z digest=sha256:60d115bb89446d0ca43d58b48154c37ed03ed4d98ade58845f6254705fe3f0e1

Observation 8ae98151-14e5-4511-9fbd-fe1105d599c9 · outbound

This paper cites Deep learning the city: Quantifying urban perception at a global scale,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Deep learning the city: Quantifying urban perception at a global scale,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.327643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.659116Z digest=sha256:b2e4c8312ece48b0e5cb13a9c95d4ee79bf45f859b06dac5c30e4cf33dafb970

Observation befe1a94-8f52-4860-84d7-691f0777a92d · outbound

This paper cites Practical multicriteria urban bicycle routing,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Practical multicriteria urban bicycle routing,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.307134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.664460Z digest=sha256:c130c5bddc9b96416826884ccbe98976424434c8b7f3766996b21b275e5b4f1c

Observation 215ed903-fac5-43fe-b894-6a9d541c790f · outbound

This paper cites Response quality checks,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Response quality checks,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.288994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.669235Z digest=sha256:46f3f512e8570a5b0274193a6bf844b7ccb3c35f56627c2964f22e632ef4ae8d

Observation fe0f4823-8e8f-4611-afa5-89bc7074ace3 · outbound

This paper cites Towards automatic assess- ment of perceived walkability,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Towards automatic assess- ment of perceived walkability,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.271276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.673777Z digest=sha256:f8b1a81a5bc7dc1855e1af61864417f378691f670e3c3734ce918a7df73e9865

Observation 4baebf89-a382-4183-bef0-21b6a1e6fa34 · outbound

This paper cites Per- sonalized image aesthetics assessment with rich attributes,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Per- sonalized image aesthetics assessment with rich attributes,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.254724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.678159Z digest=sha256:6c167c942180f9b2dc3da2d82f999789ef51a99038af19c5c5141b55e6c0d20c

Observation bfbf1bf5-bd3e-4df0-9a0e-060f3aff0f0f · outbound

This paper cites LANISTR: Multimodal Learning from Structured and Unstructured Data.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning LANISTR: Multimodal Learning from Structured and Unstructured Data

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T18:06:13.683298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:06:13.683298Z digest=sha256:9aef6916170baa8febb924865bd3188999593d01a15b7b4e85bd5e6f0b00ef75

Observation b2162784-83ee-46b9-9e35-13eba74892d6 · outbound

This paper cites MetaFormer baselines for vision,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning MetaFormer baselines for vision,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.238097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.688738Z digest=sha256:61ea164b090ffd11aff7515f42fc8a8208c6b727a5bfe36aec3d5134d37b4feb

Observation a2cd4c40-6190-468c-b004-c33252e1c784 · outbound

This paper cites Revisiting deep learning models for tabular data,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Revisiting deep learning models for tabular data,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.222660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.695578Z digest=sha256:366bcf075727a9a1bf64e828fb1972cd99f34fd7d5a115551ee9fa542951dc26

Observation 415a02f3-9f8f-447e-b234-232a77ff733a · outbound

This paper cites Rank consistent ordi- nal regression for neural networks with application to age estima- tion,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Rank consistent ordi- nal regression for neural networks with application to age estima- tion,

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-10T18:06:13.701795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:06:13.701795Z digest=sha256:02878532786a1b0ab5190ec76e6b73bafa6a18620deba66e49820655c6876095

Observation 035faf1d-f173-4ddf-8423-5c64c6e9cb8b · outbound

This paper cites LAPIS: A novel dataset for personalized image aesthetic assessment,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning LAPIS: A novel dataset for personalized image aesthetic assessment,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.203416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.706987Z digest=sha256:2c34a3e8fe9b60c8f35ccf219d61dce2c3efa9faa160bab4aab5570a868f7c1b

Observation 1142fbf8-f292-41f0-b7f5-0ceebcdd1d78 · outbound

This paper cites How rating scales influence responses’ reliability, extreme points, middle point and respondent’s preferences,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning How rating scales influence responses’ reliability, extreme points, middle point and respondent’s preferences,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.180411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.712672Z digest=sha256:b29505e5949d678ce69d7cce36d351bf21f14ff5d4d66aacb4e18771e8f63325

Observation aaf5f9ee-6f5d-4078-89b9-b61da00499f7 · outbound

This paper cites Measuring streetscape perceptions from driveways and side- walks to inform pedestrian-oriented street renewal in D ¨usseldorf,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Measuring streetscape perceptions from driveways and side- walks to inform pedestrian-oriented street renewal in D ¨usseldorf,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.162744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.717654Z digest=sha256:fe333447baec9d11673a65782002913ca7ea7af4b403ce9c8fb5e9085237488b

Observation 21d84596-18cd-4ae8-a670-159a501a9e44 · outbound

This paper cites Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-10T18:06:13.722238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:06:13.722238Z digest=sha256:1e633d90f50cd636828148ef3461854380944920eda94ab107fa96463ab980ae

Observation 17a3d4a1-975c-4977-b9a8-c73c29097ea8 · outbound

This paper cites A neural approach to automated essay scor- ing,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning A neural approach to automated essay scor- ing,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.145402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.727198Z digest=sha256:466820353f79fb0fff686415dcd9468f46b9cebf11d183d3c1910ffb53e1ba30

Observation 57b06dc8-2e9b-46b0-95db-29b859de168b · outbound

This paper cites Deep learning fundus image analysis for diabetic retinopathy and macular edema grading,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Deep learning fundus image analysis for diabetic retinopathy and macular edema grading,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.127190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.731743Z digest=sha256:6b7ea50c7405fb34cb64a60ae5ab3c8c24c655f22787fa229889fbb579329708

Observation 311bd260-48df-4ba5-8955-9afb3efde3b5 · outbound

This paper cites Random forests,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Random forests,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.110714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.736454Z digest=sha256:5cbe5c96f85ac63adf45ae93bea2431627e5c2ff5dff4cc23dbb5c3ca3273182

Observation c86fe6b2-e3ab-4f0c-ac11-dd03e2d81981 · outbound

This paper cites Which cycling environment appears safer? Learning cycling safety perceptions from pairwise image comparisons,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Which cycling environment appears safer? Learning cycling safety perceptions from pairwise image comparisons,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.092134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.741519Z digest=sha256:20b4573dee84c5b856a3a07da3d92e3a823ff4e89b795dc1bb4b2546eeeabda2

Observation c4598a92-e382-40e1-adb9-583beef7118b · outbound

This paper cites Personalized image aesthetics,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Personalized image aesthetics,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.073729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.747338Z digest=sha256:88a5c8284e976fe6f16c4066be36a7d83edd162708fc8c9dfaa868fa552d31ce

Observation 19309f3a-dcf8-4dd8-96f7-d867db615ae7 · outbound

This paper cites Street view imagery in urban analytics and GIS: A review,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Street view imagery in urban analytics and GIS: A review,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.056931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.752125Z digest=sha256:2c5d568d06bb24a8dcb2be0400d9e6f23a77fa3f67c39423cbfd1c9218dbe142

Observation 49ad0b46-44f9-462e-b413-75d8f2a6dad1 · outbound

This paper cites Deep residual learning for image recognition,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Deep residual learning for image recognition,

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-10T18:06:13.757651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:06:13.757651Z digest=sha256:274b02e867a709c53bfd71cdf230ba11b25bbe4d5b9d0271eb12cd09fe8b83a0

Observation ec6ab4e1-18fd-42e1-8e77-31854a929374 · outbound

This paper cites Swin Transformer: Hierarchical vision transformer using shifted windows,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Swin Transformer: Hierarchical vision transformer using shifted windows,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.027881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.762468Z digest=sha256:ab6dd3cf291db07af293c0e263ae153590ec6aadc7023c107b4784425a8af3a6

Observation 5994e267-6e4b-471e-a735-726360bbb941 · outbound

This paper cites A ConvNet for the 2020s,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning A ConvNet for the 2020s,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:14.010123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.767161Z digest=sha256:69be391f387b07ce91d0b3a9b1535395e98e32ca3327bb89fe4a2e3f1f72e862

Observation cbbe00f9-586e-48e1-adbb-abe5f3e7f52f · outbound

This paper cites Deep neural networks for rank- consistent ordinal regression based on conditional probabilities,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Deep neural networks for rank- consistent ordinal regression based on conditional probabilities,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:13.990711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.772185Z digest=sha256:72aee170cefeabfa783ef8cf1945ad3aa99975bcda9864e1d0a3fca694c5262e

Observation e40b6808-205b-4129-9c28-cd21b6525fed · outbound

This paper cites Attention is all you need,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Attention is all you need,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:13.974461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.778088Z digest=sha256:defa9a23bc2105eaaacced75d3da95aa9a58847eaa75fe20154dd7588a37bcc2

Observation 5aa75782-b97c-481b-b8f2-b92f0c6b7969 · outbound

This paper cites Crowd- sourced NeRF: Collecting data from production vehicles for 3D street view reconstruction,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Crowd- sourced NeRF: Collecting data from production vehicles for 3D street view reconstruction,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:13.959250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.783468Z digest=sha256:85e634497df0140bba019a4c89ee6e186ee3961ceed83b6c4a365fc0d141b280

Observation 4d35e7ac-7677-449c-8003-48034acb9bf7 · outbound

This paper cites Unrestricted Permutation forces Extrapolation: Variable Importance Requires at least One More Model, or There Is No Free Variable Importance.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Unrestricted Permutation forces Extrapolation: Variable Importance Requires at least One More Model, or There Is No Free Variable Importance

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-10T18:06:13.788718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:06:13.788718Z digest=sha256:59b99ed9aba325e2256fe0b8ea3e98578b3f2b223109202f91bbdf6befef325c

Observation ae7c83a4-6a79-48dd-822b-ae14d0b1635f · outbound

This paper cites Adaptive personalized travel information systems: A Bayesian method to learn users’ personal preferences in multimodal transport networks,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Adaptive personalized travel information systems: A Bayesian method to learn users’ personal preferences in multimodal transport networks,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:13.943011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.794150Z digest=sha256:58c09d9160effd6da410b308f7941dd07ad7162456f90e34bf2f0af92078e1e6

Observation 5b5635d0-1b38-4cce-94bf-ef7525081d82 · outbound

This paper cites Deep learning for intelligent transportation systems: A survey of emerging trends,.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Deep learning for intelligent transportation systems: A survey of emerging trends,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:06:13.926639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T18:06:13.799161Z digest=sha256:a0aba426bb1a8ed80d2749468d12a116a206ea6b42713e0d0d17bdc61ca99e83

Observation c7f7e653-e7e6-4502-9396-04eb255856ea · outbound

This paper cites AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T18:06:13.804465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:06:13.804465Z digest=sha256:4112fb802b725a41c369ae8037f28a70892fd417f209e7d07ed3c966873a0235

Pith citing papers

No inbound Pith citation observations are available.