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Self-Improving Autonomous Agents: A Survey of Adaptive Systems and Frameworks
Self-improving autonomous agents are moving from research prototypes to deployed systems. The primary goal is controllable evolution, or adaptation, from experience with minimal or even no human input. This survey frames modern self-improving agents as ad
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arxiv.org6h agoWaterMoE: A Low-Overhead Watermarking Method for Mixture-of-Experts LLMs
Large language models (LLMs) have achieved remarkable success but raise growing concerns about content provenance and misuse, motivating the need for reliable watermarking techniques. However, these techniques have rarely been adopted in practice mainly f
Shared by @arxiv-daily-bot.bsky.social ↗arxiv.org6h agoOracle Agent Memory: A Database-Native Memory Substrate for Long-Horizon AI Agents
Agent memory is a systems problem for long-horizon agents. Practical deployments require retention of task state across extended conversations, recovery of user-specific facts and preferences across sessions, and accumulation of procedural knowledge from
Shared by @arxiv-daily-bot.bsky.social ↗arxiv.org6h agoApproximation Algorithms for Hierarchical Clustering into Trees and Bounded Diameter Graphs
Consider the following variation on the Hierarchical Clustering problem: Usually, while building a hierarchical clustering, one recursively partitions the data until each cluster becomes a singleton. We relax the halting condition of the recursive process
Shared by @arxiv-daily-bot.bsky.social ↗arxiv.org6h agoImproved Deterministic Algorithm for Approximate Minimum Spanning Trees in Doubling Metrics
The minimum spanning tree (MST) problem is one of the most basic optimization problems on metric spaces and graphs. We study the problem of computing a $(1+ε)$-approximation to the MST of an $n$-point metric space $(X, \mathbf{d})$ of doubling dimension $
Shared by @arxiv-daily-bot.bsky.social ↗arxiv.org6h agoPrivacy-Preserving Recommendation Framework Balances Personalization with Regulatory Compliance
Personalized recommendation systems are central to modern e-commerce and retail platforms, but they typically rely on centralized storage of detailed user interaction data, creating significant privacy and regulatory challenges. With increasing requiremen
Shared by @arxiv-daily-bot.bsky.social ↗arxiv.org6h agoXiaomi MiMo Team Details Full-Pipeline Inference Optimization for Hybrid SWA + MoE Multimodal LLM Serving
We present a full-pipeline inference optimization for the MiMo-V2.5 model family, which combines Hybrid Sliding Window Attention (Hybrid SWA), sparse Mixture-of-Experts (MoE), and multimodal encoders. While Hybrid SWA can ideally reduce both attention com
Shared by @teortaxesTex ↗arxiv.org19h ago