3 papers
cs.AI2026
Evo-Harness: Context-to-Harness Skill Compilation for Self-Evolving Agents
Tianxin Wei, Zhan Shi, Minhua Lin +14
Learning from experience is critical for developing capable, self-improving large language model (LLM) agents. Existing methods typically extract knowledge from accumulated traject…
cs.LG2026
Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams
Zewen Liu, Zhan Shi, Yisi Sang +7
Auto-harness systems such as A-Evolve, GEPA, and Meta-Harness improve LLM agents by optimizing prompts, skills, tools, memories, and supporting infrastructure from execution feedba…
q-bio.BM2025
General Protein Pretraining or Domain-Specific Designs? Benchmarking Protein Modeling on Realistic Applications
Shuo Yan, Yuliang Yan, Bin Ma +6
Recently, extensive deep learning architectures and pretraining strategies have been explored to support downstream protein applications. Additionally, domain-specific models incor…