arXiv:2605.12977v1 Announce Type: cross
Abstract: Estimating the covariance of asset returns, i.e., the risk model, is a key component of financial portfolio construction and evaluation. Most risk modeling approaches produce a factor model that decomp…
arXiv:2605.13391v1 Announce Type: new
Abstract: The rise of multi-modal large language models (MLLMs) is shifting remote sensing (RS) intelligence from “see” to “action”, as OpenClaw-style frameworks enable agents to autonomously operate massive RS im…
arXiv:2605.12765v1 Announce Type: new
Abstract: Large Language Models memorize vast amounts of training data, raising concerns regarding privacy, copyright infringement, and safety. Machine unlearning seeks to remove the influence of a targeted forget…
arXiv:2605.12784v1 Announce Type: new
Abstract: Advances in large language models (LLMs) have recently opened new and promising avenues for small-molecule drug discovery. Yet existing LLM-based approaches for molecular generation often suffer from hig…
arXiv:2605.13527v1 Announce Type: new
Abstract: Reusable skills have become a core substrate for improving agent capabilities, yet most existing skill packages encode reusable behavior primarily as textual prompts, executable code, or learned routines…
arXiv:2602.11202v3 Announce Type: replace-cross
Abstract: Reasoning models produce long traces of intermediate decisions and tool calls, making test-time verification important for ensuring correctness. Existing approaches either verify only the final…
arXiv:2605.13542v1 Announce Type: new
Abstract: Intensive care units (ICU) generate long, dense and evolving streams of clinical information, where physicians must repeatedly reassess patient states under time pressure, underscoring a clear need for r…
arXiv:2605.13625v1 Announce Type: new
Abstract: Autonomous agents such as Claude Code and Codex now operate for hours or even days. Understanding their runtime behavior has become critical for downstream tasks such as diagnosing inefficiencies, fixing…
arXiv:2605.12570v1 Announce Type: new
Abstract: The accurate classification of benign and malignant pulmonary nodules in CT scans is critical for early lung cancer screening, yet remains challenging due to the multi-scale and heterogeneous nature of p…
arXiv:2605.13821v1 Announce Type: new
Abstract: Agentic evolution has emerged as a powerful paradigm for improving programs, workflows, and scientific solutions by iteratively generating candidates, evaluating them, and using feedback to guide future …