MemU-Bench: Benchmarking GUI Agents on Long-Horizon User Interactions
arXiv cs.AIen
arXiv:2611.00191v1 Announce Type: new Abstract: Existing Graphical User Interface (GUI) benchmarks predominantly rely on precise and stateless user instructions. In everyday usage, however, instructions are often \emph{vague and history-dependent}: users omit the exact details of their past operations because they no longer remember them, leaving the agent to recover the missing context from long and noisy interaction histories. To bridge this evaluation gap, we introduce \textbf{MemU-Bench}, a mobile benchmark of \textbf{118 vague tasks} grounded in 29 long-horizon user trajectories, where agents must distill raw interaction streams into memory and retrieve the missing context on demand, wi
This is a short summary published by AI Global Wire. The full article is owned and hosted by arXiv cs.AI — open it there to read it in full.
Read the full story at arXiv cs.AI- Forskning
- Agenter
- Företag
Related AI news
- South Korea urged to link chip fab support to local suppliersDIGITIMES · November 3, 2026
- Thunder Tiger flexes unmanned surface vessel capabilities alongside US companiesDIGITIMES · November 3, 2026
- heise+ | Vom Testanalysten zum Agententeam: Qualitätssicherung mit klaren Leitplankenheise online – KI · November 3, 2026
- OpenAI partners with Cathedral to test its security defenses and revamps its Security Bug Bounty program, including quadrupling rewards for critical findings (OpenAI)Techmeme · November 3, 2026
- Cities Worldwide Build and Scale AI Services With NVIDIA Physical and Agentic AINVIDIA Blog · November 3, 2026
- Apple's US$5 trillion dilemma: iPhone Duo and AI raise stakes for next growth chapterDIGITIMES · November 3, 2026