id
related bits
0
processing priority
3
site type
0 (generic, awaiting analysis)
review version
11
html import
20 (imported)
first seen date
2024-11-25 10:56:05
expired found date
-
created at
2024-11-25 10:56:05
updated at
2026-01-28 13:47:30
length
22
crc
64268
tld
86
nm parts
0
nm random digits
0
nm rare letters
0
is subdomain of id
87719371 (github.io)
previous id
0
replaced with id
0
related id
-
dns primary id
0
dns alternative id
0
lifecycle status
0 (unclassified, or currently active)
deleted subdomains
0
page imported products
0
page imported random
0
page imported parking
0
count skipped due to recent timeouts on the same server IP
0
count content received but rejected due to 11-799
0
count dns errors
0
count cert errors
0
count timeouts
0
count http 429
0
count http 404
0
count http 403
0
count http 5xx
0
next operation date
-
server bits
—
server ip
-
mp import status
20
mp rejected date
-
mp saved date
-
mp size orig
18251
mp size raw text
4977
mp inner links count
4
mp inner links status
20 (imported)
title
CORR workshop
description
site name
author
updated
2026-01-26 18:05:33
raw text
CVPR Workshop on Causal and Object-Centric Representations for Robotics About Call for Papers Schedule Papers Causal and Object-Centric Representations for Robotics June 17, CVPR 2024 Workshop (Arch 210) & Posters #225 - 239 Current approaches in computer vision and machine learning primarily rely on identifying statistical correlations within massive datasets. This reliance limits their efficacy in areas that necessitate generalization through higher-order cognition, such as domain generalization and planning. A foundational approach to overcome these limitations involves incorporating principles of causality into the processing of large datasets. Similar to classic AI methodologies, causal inference usually assumes that the causal variables of interest are provided externally. However, real-world data, often encapsulated in high-dimensional, low-level observations (e.g., RGB pixels in a video), generally lacks organization into meaningful causal units. Causal Repre...
redirect type
0 (-)
block type
0 (no issues)
detected language
1 (English)
category id
AI [en] (229)
index version
2025123101
spam phrases
0
text nonlatin
0
text cyrillic
0
text characters
4060
text words
636
text unique words
348
text lines
80
text sentences
25
text paragraphs
11
text words per sentence
25
text matched phrases
3
text matched dictionaries
2
links self subdomains
0
links other subdomains
links other domains
4 - tri.global, egavves.com, roozbehm.info, francescolocatello.com
links spam adult
0
links spam random
0
links spam expired
0
links ext activities
2
links ext ecommerce
0
links ext finance
0
links ext crypto
0
links ext booking
0
links ext news
0
links ext leaks
0
links ext ugc
9
links ext klim
0
links ext generic
0
dol status
0
dol updated
2026-01-26 18:05:33
rss path
rss status
1 (priority 1 already searched, no matches found)
rss found date
-
rss size orig
0
rss items
0
rss spam phrases
0
rss detected language
0 (awaiting analysis)
inbefore feed id
-
inbefore status
0 (new)
sitemap path
sitemap status
1 (priority 1 already searched, no matches found)
sitemap review version
1
sitemap urls count
0
sitemap urls adult
0
sitemap filtered products
0
sitemap filtered videos
0
sitemap found date
-
sitemap process date
-
sitemap first import date
-
sitemap last import date
-