Main

related bits

0

processing priority

3

site type

0 (generic, awaiting analysis)

review version

11

html import

20 (imported)

Events

first seen date

2025-04-07 00:06:32

expired found date

-

created at

2025-04-07 00:06:32

updated at

2025-04-07 00:06:32

Domain name statistics

length

20

crc

1981

tld

86

nm parts

0

nm random digits

0

nm rare letters

0

Connections

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)

Subdomains and pages

deleted subdomains

0

page imported products

0

page imported random

0

page imported parking

0

Error counters

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

server bits

server ip

-

Mainpage statistics

mp import status

20

mp rejected date

-

mp saved date

-

mp size orig

34298

mp size raw text

9566

mp inner links count

0

mp inner links status

1 (no links)

Open Graph

title

description

offline-RL-SEEM

image

site name

author

updated

2026-02-07 16:22:39

raw text

offline-RL-SEEM SEEM: Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL Yang Yue * , Rui Lu * , Bingyi Kang * , Shiji Song , Gao Huang + , &nbsp&nbsp * Equal Contribution &nbsp&nbsp + Corresponding author &#x25B6 1 Department of Automation, BNRist, Tsinghua University 2 Bytedance Inc. arXiv Code Slide Poster The Self-Excite Eigenvalue Measure (SEEM) offers a new theoretical framework and metric to understand, predict, and better resolve Q-value divergence in offline RL. SEEM can reliably predict upcoming divergence through the largest eigenvalue of a kernel matrix and accurately characterize the growth order of diverging Q-values. Finally, SEEM resolves divergence from a novel perspective, namely regularizing the neural network’s generalization behavior. Abstract The divergence of the Q-value estimation has been a prominent issue offline reinforcement learning (offline...

Text analysis

redirect type

0 (-)

block type

0 (no issues)

detected language

1 (English)

category id

AI [en] (229)

index version

2025123101

spam phrases

0

Text statistics

text nonlatin

0

text cyrillic

0

text characters

7120

text words

1349

text unique words

520

text lines

86

text sentences

62

text paragraphs

16

text words per sentence

21

text matched phrases

1

text matched dictionaries

2

RSS

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

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

-