AgenticSciML: Collaborative Multi‑Agent System for Emergent Discovery in Scientific Machine Learning

AgenticSciML introduces a collaborative multi‑agent framework that autonomously designs SciML models—such as PINNs and neural operators—by iteratively debating, retrieving knowledge, and evolving solutions, achieving up to 11,000× error reduction on benchmark PDE problems.

AgenticSciMLAutoMLEmergent Discovery

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AgenticSciML: Collaborative Multi‑Agent System for Emergent Discovery in Scientific Machine Learning

Kuaishou Large Model

Jul 3, 2025 · Artificial Intelligence

How EvoSearch Boosts Image & Video Generation with Test‑Time Evolutionary Search

The EvoSearch method introduced by HKUST and Kuaishou’s KuaLing team leverages test‑time scaling to dramatically improve diffusion‑based image and video generation without training, using evolutionary search along the denoising trajectory, achieving state‑of‑the‑art results on SD2.1, Flux‑1‑dev and other models.

Evolutionary SearchTest-Time ScalingVideo Generation

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How EvoSearch Boosts Image & Video Generation with Test‑Time Evolutionary Search

Kuaishou Tech

Jul 2, 2025 · Artificial Intelligence

How EvoSearch Supercharges Image and Video Generation with Test‑Time Evolutionary Search

EvoSearch, a test‑time evolutionary search method, dramatically improves image and video generation by increasing inference compute without extra training, outperforming existing scaling techniques on diffusion and flow models while maintaining robustness and diversity across multiple benchmarks.

AI researchEvolutionary SearchTest-Time Scaling

0 likes · 8 min read