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Beijing

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2

RESEARCH · 1 SOURCE · arXiv cs.AI

Empirical evaluation of joint upper‑bound coverage for route choice (arXiv:2610.06995v1)

This arXiv preprint evaluates whether improving joint upper‑bound coverage of path travel‑time forecasts helps downstream route decisions. Using offline proxy tasks built from Beijing and Chengdu road speed data (150 OD pairs, three candidate paths, 14 test days), the authors compare raw 90th‑percentile path time bounds to jointly calibrated upper bounds: joint calibration raises joint coverage substantially (e.g., from 83.19% to 92.26% in one Beijing task) but nevertheless increases lateness and mean travel time in the frozen tasks; separately, a predictor with 14.91% lower speed MAE reduced lateness modestly under a different decision rule. The paper stresses that joint coverage is not a reliable surrogate for route utility in these offline experiments and does not claim online or causal benefits.

5.0

STARTUPS · 1 SOURCE · The Decoder

Manus 2.0 launches platform to run phone-based agents, edit video, and host multiplayer games

Manus 2.0 turns the company’s agent into a broader platform: users can now edit video and develop/host multiplayer games in a desktop app (Manus Studio), run personal agents reachable by their own phone numbers, and remotely direct approved files and apps on their machines via a "Computer Use" feature. A tested Cascade agent configuration used 23.2% fewer tokens and cost 32% less to run than the prior system; a separate Cue app (in free early access by invite) gives each agent an email address, wallet, and cloud computer. The release is available now.

6.0