Diagnosing Personalization Failures in Mobile GUI Agents

No. 171 of 245 · arXiv · Zhixin Lin, Dongliang Xu, Jungang Li et al. · published 23 Oct 2026, 04:00 UTC · first published 22 Oct 2026 · 40 min read

AI & machine learning
Paper

3 judges. Scored by all three judges. Only the day’s top stories get the claim check. How far stories are checked

PrefDiag-Bench is a new benchmark for evaluating personalized mobile GUI agents, which must use user preferences to guide actions across changing app screens. It sorts preferences into five execution-oriented types and adds a stage-wise diagnostic framework with 1,664 probes, to identify where agents fail to apply preferences.

Read the original at arxiv.org. The judges saw only its text, with the site, the author and link domains removed; they are shown again after ranking.

Score

0.62total under rubric v2.0

Significance0.57
Reader interest0.63
Audience breadth0.47
Practical relevance0.62
Substantiated0.84
Technical depth0.77
New information0.90
Counts against: Promotional0.04
Counts against: Overclaim0.20

Each judge’s answer per question (0–1), their mean and spread, and what the question adds to the score (weight × mean).

Question	Judge 1	Judge 2	Judge 3	Mean	Spread	Weight	Contribution (weight times mean)
Significance	0.63	0.35	0.72	0.57	0.37	+0.25	+0.142
Reader interest	0.60	0.45	0.84	0.63	0.39	+0.20	+0.126
Audience breadth	0.52	0.35	0.55	0.47	0.20	+0.10	+0.047
Practical relevance	0.72	0.45	0.68	0.62	0.27	+0.15	+0.093
Substantiated	0.99	0.70	0.82	0.84	0.29	+0.10	+0.084
Technical depth	0.89	0.60	0.83	0.77	0.29	+0.10	+0.077
New information	0.92	0.80	0.98	0.90	0.18	+0.10	+0.090
Promotional	0.05	0.05	0.03	0.04	0.02	−0.15	−0.006
Overclaim	0.16	0.25	0.18	0.20	0.09	−0.15	−0.030
Sum of contributions							+0.622
Claim-check penalty							0.000
Total, as published							0.622

Spread is the highest minus the lowest judge answer. marks a spread above 0.40: the judges disagree, and the story is marked contested.

Also covered by

No other coverage was clustered with this story.

Elsewhere

Elsewhere: HN —

Recorded for context only, checked 24 Oct 2026, 08:54 UTC. It played no part in the ranking.

Panel for this edition

Four AI agents ranked this edition: three judges scored every story blind to its site and author, and a fourth compared the top stories’ claims with the sources they cite. Summaries are written by AI.

Model versions are pinned for every edition and listed in its JSON. This one was scored under rubric v2.0; How ranking works describes the current rubric, v2.2.