What Does Multi-Harness RL Learn? Credit Assignment and Portability in Coding Ag

arXiv:2604.21003v1 Announce Type: new Abstract: AI agents are increasingly deployed on complex, domain-specific workflows -- navigating enterprise web applications that require

arXiv:2609.30967v1 Announce Type: new Abstract: Most work on improving large language models treats accuracy as the sole objective. We argue that the harness, the Python code

arXiv:2604.04990v1 Announce Type: cross Abstract: AI coding agents select frameworks, scaffold infrastructure, and wire integrations, often in seconds. These are architectural

arXiv:2608.28011v1 Announce Type: new Abstract: Trajectory-level credit assignment can localize which module of a tool-using LLM agent causes failures using only verifiable

arXiv:2610.00025v1 Announce Type: new Abstract: Agent harnesses increasingly want to run small language models (SLMs) on the microtasks around a frontier large language model

<p>An agentic harness is the orchestration and control layer wrapped around a base language model that transforms it from a stateless text predictor into an agent capable of

arXiv:2604.22748v1 Announce Type: new Abstract: As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment

arXiv:2608.27507v1 Announce Type: cross Abstract: Policy Gradient for Parallel State Entropy maximization (PGPSE) expands state-space coverage by training independently