arXiv:2605.01231v1 Announce Type: new
Abstract: Recent progress in time-series forecasting has led to rapidly increasing architectural complexity, yet many reported State-of-the-Art gains are statistically fragile or misattributed. We argue that progr…
arXiv:2605.01240v1 Announce Type: cross
Abstract: Self-supervised pretraining is promising for large-scale neuroimaging, yet the impact of region-aware masking and hybrid sequence modeling remains underexplored. In this work, we introduce Rhamba, a re…
arXiv:2602.00217v2 Announce Type: replace
Abstract: Large language models (LLMs) achieve remarkable performance through ever-increasing parameter counts, but scaling incurs steep computational costs. To better understand LLM scaling, we study represen…
arXiv:2602.11083v2 Announce Type: replace
Abstract: Remote change detection in LLMs is a difficult problem. Existing methods are either too expensive for deployment at scale, or require initial white-box access to model weights or grey-box access to l…
arXiv:2502.06719v3 Announce Type: replace-cross
Abstract: In this paper, we establish the non-asymptotic validity of the multiplier bootstrap procedure for constructing the confidence sets using the Stochastic Gradient Descent (SGD) algorithm. Under a…
arXiv:2509.09723v3 Announce Type: replace-cross
Abstract: Psychological measurement is critical to many disciplines. Despite advances in measurement, building nomological networks, theoretical maps of how concepts and measures relate to establish vali…
arXiv:2605.01358v1 Announce Type: new
Abstract: Unsupervised Environment Design (UED) offers a promising paradigm for improving reinforcement learning generalization by adaptively shaping training environments, but it requires reliable environment eva…
arXiv:2511.21678v2 Announce Type: replace
Abstract: MLLMs exhibit strong reasoning on isolated queries, yet they operate de novo — solving each problem independently and often repeating the same mistakes. Existing memory-augmented agents mainly store…
arXiv:2605.01574v1 Announce Type: new
Abstract: Vehicle Routing Problem (VRP) is one of the most complex NP-hard combinatorial optimization problem in transportation and logistics that requires a dynamic solution approach. In this paper we present a n…
arXiv:2605.01616v1 Announce Type: cross
Abstract: Human behavior is difficult to observe continuously at scale, yet it leaves measurable traces in everyday device use. We test whether encrypted smartphone network traffic — a ubiquitous, always-on, pa…