Research Feed Page 47
Search source-linked summaries of recent AI and machine-learning papers by topic, by date, or by whether they include code or a diagram.
Research results
The paper uses the Lyapunov characteristic exponent as a reward signal to teach reinforcement learning agents how to stabilize an inverted pendulum with vertical motion.
The researchers introduced Cluster-based Sequential Feature Selection (CSFS), a wrapper method that reduces the computational cost of feature selection in renewable energy prediction pipelines.
VideoRAE replaces pixel-focused autoencoders with a system that maps video foundation model features into more efficient and semantically aware latent representations.
The researchers developed a security framework to protect the lifecycle of reusable LLM agent skills from creation through execution.
The researchers developed a method to assign rewards to intermediate steps in agent interactions to improve performance on long-horizon tasks.
The paper introduces RELAI-VCL, a regression-aware optimizer that prevents agent performance from dropping when learning new tasks.
This paper proposes a new method for penetration testing AI-enabled systems that focuses on violating operational objectives through AI-governed behavior rather than just compromising resources.
The paper introduces Lighthouse RL, a reinforcement learning method that uses strategic reset points to improve sample efficiency in analog circuit sizing.
The paper identifies how architecture choices like normalization placement and width expansion prevent gradient rank collapse in deep Transformer models at initialization.
The paper examines how developers integrate agentic coding tools into their workflows by analyzing pull request patterns across 2,361 GitHub repositories.
The authors implement a domain routing system that dispatches page images to specialized OCR models, enabling accurate text extraction across varied historical Manchu writing styles.
The paper introduces COLLEAGUE.SKILL, an end-to-end workflow that distills heterogeneous traces of person-grounded knowledge into inspectable, correctable, and agent-usable skills.
GrepSeek replaces traditional vector-based search indices with an agent that interacts directly with raw corpus files using shell commands.
The paper introduces a method called Trust Region Behavior Blending to stabilize on-policy distillation by controlling how teachers supervise student models during early training.