Quality follows upgrading
Ever a pioneer, ever a student — learning through our mistakes and failures
Academic
arXiv:2604.05339v1 Announce Type: new Abstract: As LLMs become increasingly integrated into human society, evaluating their orientations on human values from social science has drawn growing …
arXiv:2604.05374v1 Announce Type: new Abstract: Linear matrix inequalities (LMIs) have played a central role in certifying stability, robustness, and forward invariance of dynamical systems. Despite …
arXiv:2604.05842v1 Announce Type: new Abstract: Mixture of linear regression is well studied in statistics and machine learning, where the data points are generated probabilistically using …
arXiv:2604.05564v1 Announce Type: new Abstract: We describe THIVLVC, a two-stage system for the EvaLatin 2026 Dependency Parsing task. Given a Latin sentence, we retrieve structurally …
arXiv:2604.05414v1 Announce Type: new Abstract: Recent work has shown that removing orthogonalization during training and applying it only at inference improves rotation estimation in deep …
arXiv:2604.05018v1 Announce Type: new Abstract: Synthesizing unstructured research materials into manuscripts is an essential yet under-explored challenge in AI-driven scientific discovery. Existing autonomous writers are …
arXiv:2604.05522v1 Announce Type: new Abstract: Omni Large Language Models (Omni-LLMs) have demonstrated impressive capabilities in holistic multi-modal perception, yet they consistently falter in complex scenarios …
arXiv:2604.05142v1 Announce Type: new Abstract: As artificial intelligence systems (AIs) become increasingly produced by recursive self-improvement, a form of evolution may emerge, in which the …
arXiv:2604.05072v1 Announce Type: new Abstract: Recent large language models have shifted SVG generation from differentiable rendering optimization to autoregressive program synthesis. However, existing approaches still …
arXiv:2604.05229v1 Announce Type: new Abstract: Agentic AI systems plan, use tools, maintain state, and produce multi-step trajectories with external effects. Those properties create a governance …
arXiv:2604.05267v1 Announce Type: new Abstract: In the era of Large Language Models (LLMs), the Mixture of Experts (MoE) architecture has emerged as an effective approach …
arXiv:2604.04998v1 Announce Type: new Abstract: This paper proposes a novel framework for enhancing the prediction accuracy and lead time of El Ni\~no events, crucial for …