BestHub
Sign in
Tagged articles

Evolutionary Search

8 articles · Page 1 of 1
PaperAgent
PaperAgent
Aug 7, 2026 · Artificial Intelligence

OpenMLE: Tsinghua’s Self‑Evolving MLE System Pushes 35B Model Past GPT‑5.5

The article introduces OpenMLE, an open‑source full‑stack system for recursive self‑improvement (RSI) research, showing how a 35B Frontis‑MA1 model improves its Medal Average from 39.39% to 71.21% on MLE‑Bench Lite, surpasses GPT‑5.5+Codex, and details the mechanism hierarchy, task‑curation gym, trainable evolution operators, and experimental evidence that training and search gains combine additively.

Evolutionary SearchFrontis-MA1MLE-Bench Lite
0 likes · 19 min read
OpenMLE: Tsinghua’s Self‑Evolving MLE System Pushes 35B Model Past GPT‑5.5
TonyBai
TonyBai
Jul 10, 2026 · Artificial Intelligence

The New AI Stack: Models, Harnesses, Loops, and Self‑Evolving Agents

The article argues that AI product performance hinges not on ever smarter foundation models but on the surrounding harness framework—covering loops, file‑system memory, sub‑agents, context engineering, and self‑optimizing code—and provides concrete patterns, pitfalls, and a four‑week roadmap for developers.

AIAgentic SystemsEvolutionary Search
0 likes · 26 min read
The New AI Stack: Models, Harnesses, Loops, and Self‑Evolving Agents
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Jul 8, 2026 · Artificial Intelligence

How Harness Engineering Enables Recursive Self‑Improvement in AI

The article surveys recent research on harness engineering—software layers that orchestrate large language models—and examines how these layers can drive recursive self‑improvement, outlining design patterns, optimization techniques, evolutionary search, and the remaining technical challenges.

AIAgentic SystemsEvolutionary Search
0 likes · 38 min read
How Harness Engineering Enables Recursive Self‑Improvement in AI
AI Engineering
AI Engineering
Jul 8, 2026 · Artificial Intelligence

How AI Can Achieve Recursive Self‑Improvement: Lilian Weng Says Build a Robust Harness First

The article examines recursive self‑improvement in AI, arguing that a well‑designed harness—responsible for workflow orchestration, context management, and tool integration—is as crucial as model intelligence, and outlines design patterns, meta‑engineering approaches, evolutionary search methods, and the remaining challenges for truly autonomous AI systems.

AI self‑improvementAgent designEvolutionary Search
0 likes · 17 min read
How AI Can Achieve Recursive Self‑Improvement: Lilian Weng Says Build a Robust Harness First
Machine Heart
Machine Heart
Jul 7, 2026 · Artificial Intelligence

How Harness Engineering Drives Recursive Self‑Improvement in AI

The article surveys recent research on Harness engineering—systems that orchestrate model reasoning, tool use, context management, and evaluation—and examines whether recursive self‑improvement (RSI) will first emerge in model weights or in the surrounding Harness, while outlining design patterns, optimization strategies, and open challenges.

AIAgentic SystemsEvolutionary Search
0 likes · 37 min read
How Harness Engineering Drives Recursive Self‑Improvement in AI
Kuaishou Large Model
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 Searchdiffusion modelsimage generation
0 likes · 8 min read
How EvoSearch Boosts Image & Video Generation with Test‑Time Evolutionary Search
Kuaishou Tech
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 Searchdiffusion models
0 likes · 8 min read
How EvoSearch Supercharges Image and Video Generation with Test‑Time Evolutionary Search