All Articles
1 min read
ResearchOctober 20, 2026

Not Every User Says It All: Training Tool-Using Agents Beyond Ideal Simulated Users

arXiv:2610.24294v1 Announce Type: new Abstract: Tool-using agents are trained and evaluated almost exclusively with strong simulated users who state every detail clearly, yet real users are often weaker. We construct weak users by masking sentences of a simulated user's replies,…

Han Bao, Zheyuan Zhang, Kaiwen Shi, Yanfang Ye·arXiv — cs.AI
Original Source
Key Takeaways
  • 01.arXiv:2610.24294v1 Announce Type: new Abstract: Tool-using agents are trained and evaluated almost exclusively with strong simulated users who state every detail clearly, yet real users are often weaker
  • 02.We construct weak users by masking sentences of a simulated user's replies,…

This material is provided as an extended analytical summary.

Read full article at source
Aggregated within AI Qazaqstan national intelligence stream with author attribution.

Related Intelligence

All stories →
Research1 мин

How Sullivan & Cromwell builds legal tools with Codex | OpenAI

At Sullivan & Cromwell LLP, John Savva uses Codex to build tools around the firm’s legal expertise. Agreement Analyzer brings together a draft agreement, selected precedents, and playbooks reflecting the firm’s and client’s positions. It identifies potential issues and returns a…

YouTube — OpenAI Official
Research1 мин

Hebbia on Astra: Better research, better presentations | OpenAI

“We see Astra actually show over double digit gains over any other model we've tested on two fronts.” Hebbia’s Kavita Anand names the two: selecting the right sources and generating PowerPoint presentations. For a banker or investor working through a data room with thousands of…

YouTube — OpenAI Official