id
processing priority
3
site type
5 (wiki-type site, growing by topic rather than chronologically)
review version
11
html import
20 (imported)
first seen date
2024-08-06 23:58:07
expired found date
-
created at
2024-08-06 23:58:06
updated at
2024-08-09 12:57:55
length
17
crc
64571
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
18690
mp size raw text
8533
mp inner links count
0
mp inner links status
1 (no links)
title
description
Self-RAG: Learning to Retrieve, Generate and Critique through Self-Reflection.
image
site name
author
updated
2026-01-06 19:08:10
raw text
Self-RAG: Learning to Retrieve, Generate and Critique through Self-Reflection Self-RAG: Learning to Retrieve, Generate and Critique through Self-Reflections Akari Asai 1 Zeqiu Wu 1 Yizhong Wang 1 , Avirup Sil 2 , Hannaneh Hajishirzi 1,3 , 1 University of Washington, 2 IBM AI Research, 3 Allen Institute for AI arXiv Code Model (7B) Model (13B) Data HF Space Self-RAG learns to retrieve, generate and critique to enhance LM's output quality and factuality, outperforming ChatGPT and retrieval-augmented LLama2 Chat on six tasks. Summary The issue: Factual inaccuracies of versatile LLMs Despite their remarkable capabilities, large language models (LLMs) often produce responses containing factual inaccuracies due to their sole reliance on the parametric knowledge they encapsulate. They often generate hallucinations, especially in long-tail, their knowledge gets obsolete, and lacks attribution. Is Retrieval-Augmented Generation a sil...
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
6641
text words
1137
text unique words
455
text lines
130
text sentences
47
text paragraphs
23
text words per sentence
24
text matched phrases
3
text matched dictionaries
2
links self subdomains
0
links other subdomains
1 - research.ibm.com
links other domains
0
links spam adult
0
links spam random
0
links spam expired
0
links ext activities
3
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
2026-01-06 19:08:10
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
2
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
-