Ensemble Complexity in Photovoltaic Forecasting
arXiv:2609.15049v1 Announce Type: cross Abstract: An ensemble can improve photovoltaic forecasts while adding components that contribute little or increase computation. We assess these effects through
Knowledge catalogue
arXiv:2609.15049v1 Announce Type: cross Abstract: An ensemble can improve photovoltaic forecasts while adding components that contribute little or increase computation. We assess these effects through
arXiv:2609.15077v1 Announce Type: new Abstract: Molecular design is typically approached as a problem of finding molecules which can adopt a single bioactive conformation. In reality, molecules occupy
arXiv:2609.14187v1 Announce Type: cross Abstract: Memory-efficient feature representations are increasingly important in machine learning settings where storage, transmission cost, bandwidth, or priva
arXiv:2609.13925v1 Announce Type: cross Abstract: This work studies the stability and convergence of augmented primal-dual dynamics when constraint values are estimated from samples. Unbiased constrai
arXiv:2609.15089v1 Announce Type: new Abstract: Empathetic response generation in spoken dialogue systems requires both accurate emotion perception and appropriate emotion regulation. Grounded in psyc
arXiv:2609.13295v1 Announce Type: cross Abstract: Diffusion learning leverages the statistical mechanism of diffusion processes for learning, reasoning, and inferring complex distributions from data.
arXiv:2512.08661v2 Announce Type: replace Abstract: This paper addresses the problem of trajectory planning for information gathering with a dynamic and resolution-varying sensor footprint. Ergodic pl
arXiv:2609.14619v1 Announce Type: new Abstract: LiDAR--4-D radar fusion combines accurate spatial geometry with motion and reflectivity cues from radar, offering a promising solution for 3-D object de
arXiv:2609.15392v1 Announce Type: cross Abstract: Recent progress in image and 3D scene generation has enabled increasingly realistic static environments, yet most methods remain confined to such stat
arXiv:1304.3111v2 Announce Type: replace Abstract: In this paper, we describe a representation for spatial information, called the stochastic map, and associated procedures for building it, reading in
arXiv:2609.12839v2 Announce Type: replace-cross Abstract: The proliferation of highly capable open-weight Small Language Models (SLMs) democratizes access to advanced cybersecurity capabilities, posin
arXiv:2609.14654v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) are typically evaluated using held-out classification accuracy, an approach that presupposes predictions are based
arXiv:2607.15080v2 Announce Type: replace Abstract: This article explores the application of covariate balance diagnostics for detecting the presence of hidden confounding/model miss-specification in
arXiv:2609.13192v1 Announce Type: new Abstract: This study compares traditional machine learning models and Large Language Model (LLM)-generated rule-based systems for heart disease prediction using t
arXiv:2609.15315v1 Announce Type: new Abstract: Safe reinforcement learning (RL) is commonly formalized as a Constrained Markov Decision Process (CMDP), in which an agent maximizes expected reward whi
arXiv:2609.13250v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) cannot process every frame of a long video because of limitations in visual-token and computational budgets.
arXiv:2609.14569v1 Announce Type: cross Abstract: Constraining reaction rate coefficients is a central challenge in the development of explicit atmospheric chemical mechanisms, particularly for autoxi
Runtime security startup Eve Security Inc. wants to help stop dangerous artificial intelligence agents in their tracks after raising 4.5 million in funding today. The round, which was led by Run Ventu
arXiv:2609.13854v1 Announce Type: new Abstract: Facial emotion recognition (FER) in real-world environments remains challenging due to unconstrained imaging conditions, including multiple faces, occlu
arXiv:2609.15772v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) have shown promise for sparse, event-driven computation through stateful processing that is naturally compatible with l
arXiv:2501.13707v3 Announce Type: replace-cross Abstract: The event-based Vision-Language Model (VLM) recently has made good progress for practical vision tasks. However, most of these works just util
arXiv:2609.15779v1 Announce Type: new Abstract: Data agents aim to fulfill natural-language instructions over heterogeneous data, including tables, files, and databases. However, data agents face a ch
arXiv:2609.14935v1 Announce Type: new Abstract: Multi-robot Control Barrier Function (CBF) safety filters can become infeasible, but a failed quadratic program (QP) does not indicate why the conflict
arXiv:2609.14127v1 Announce Type: cross Abstract: We derive exact local responses for attention interventions, allowing candidate edits to be scored from a cached baseline and one backward pass. The s
arXiv:2601.16427v3 Announce Type: replace-cross Abstract: We study exact community recovery in sparse directed stochastic block models using neighborhood smoothing of connection-probability profiles.
arXiv:2505.07163v2 Announce Type: replace-cross Abstract: Ising solvers have a finite spin budget. Quadratization uses auxiliary spins to replace higher-order interactions by pairwise ones. We show th
Exactly. More here: https://www.engineering.columbia.edu/about/news/columbia-experts-urge-calm-amid-ai-panic As the first publicly disclosed agent cyberattack victim, we've had a front-row seat to thi
Agentic security operations startup Exaforce Inc. today launched Exaforce AI Security, capabilities that let security teams see the artificial intelligence agents running across their environments and
arXiv:2609.13816v1 Announce Type: cross Abstract: JavaScript powers approximately 98.8% of all websites, making vulnerabilities in its code a significant security risk, yet existing detection approach
arXiv:2609.14666v1 Announce Type: cross Abstract: Turn-taking is a fundamental component of spoken interaction, and while humans naturally rely on both verbal and non-verbal signals, dialogue systems
arXiv:2609.13927v1 Announce Type: new Abstract: Biological organisms minimize free energy by balancing two competing demands on their internal world model: it must be accurate enough to predict sensor
arXiv:2608.14714v1 Announce Type: cross Abstract: Track seeding strongly affects both the quality and computational cost of charged-particle reconstruction, yet its many configuration parameters are c
arXiv:2509.11252v3 Announce Type: replace-cross Abstract: LLMs have become the mainstream approaches to code generation. Existing LLMs mainly employ autoregressive generation, i.e. generating code tok
arXiv:2609.13289v1 Announce Type: new Abstract: Achieving high-speed locomotion in quadrupedal robots remains highly challenging, as actuators operate near their physical limits and exhibit pronounced
arXiv:2609.14913v1 Announce Type: new Abstract: Repository-level repair requires not only correct patches but also inspectable records that explain how issue requirements are translated into code chan
arXiv:2609.14758v1 Announce Type: cross Abstract: Tool-augmented language models are evaluated on whether they reach the right answer, not on whether they report honestly when a tool fails to supply o
arXiv:2609.15209v1 Announce Type: cross Abstract: Automatic prompt optimization (APO) improves language-model programs by revising prompts from task feedback, yet it typically holds its training data
arXiv:2609.13634v1 Announce Type: cross Abstract: Do AI assistants help believers reason about moral dilemmas consistently with their faith? We present FaithfulBench, the first benchmark to score AI c
arXiv:2609.14539v1 Announce Type: new Abstract: This work proposes a model-based fault detection and diagnosis framework for underwater vehicles subject to actuator faults that explicitly accounts for
arXiv:2609.13315v1 Announce Type: cross Abstract: We investigate whether a Chern-Simons (CS) context reservoir is a viable computational substrate and whether evolving its gauge connection provides a
arXiv:2609.15625v1 Announce Type: cross Abstract: Driven by the escalating demand for privacy-preserving computing, Federated Learning (FL) has witnessed remarkable progress, becoming a cornerstone te
arXiv:2609.13661v1 Announce Type: new Abstract: Knowledge graph question answering usually assumes that one system can reach the whole graph. In practice, facts are often held by organizations that sh
arXiv:2609.13733v1 Announce Type: new Abstract: Stable and reliable 4D spatial understanding is fundamental for autonomous driving systems. While feedforward reconstruction networks can estimate camer
arXiv:2409.17685v3 Announce Type: replace Abstract: Hypomimia has drawn growing interest as a digital marker for screening Parkinson's disease (PD). However, developing reliable facial-expression-base
arXiv:2609.13262v1 Announce Type: new Abstract: 3D Gaussian Splatting achieves photorealistic reconstruction within training view distribution, yet it degrades on out-of-distribution novel views, exhi
arXiv:2609.13920v1 Announce Type: cross Abstract: Persistent Gaussian perturbations have been shown to prevent asymptotic oversmoothing in recurrent Graph Neural Networks (GNNs) by ensuring a positive
arXiv:2609.13580v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities across a wide range of natural language processing tasks. However, conventional fine-
arXiv:2609.14674v1 Announce Type: new Abstract: Assigning reduced coordinates to states near an attracting limit cycle requires the correct invariant-fibre geometry. The classical first-order phase-is
arXiv:2609.15631v1 Announce Type: new Abstract: Learning a motion prior requires a reward that guides a policy from its current behavior toward demonstrated motion. Adversarial Motion Priors (AMP) pro
arXiv:2609.13640v1 Announce Type: new Abstract: Encoder-based time series foundation models (TSFMs) typically rely on deep stacks of independently parameterized Transformer layers, where only the fina
arXiv:2609.14451v1 Announce Type: cross Abstract: Modern semi-supervised learning (SSL) couples pseudo-label generation and classifier training, using the classifier's own confidence to select the pse
One thing I love about both Qwen 3.8 27B and Flash Next is the effort it puts in to make a good product. It is the opposite of a lazy model and 'good enough' is never what aims to accomplish. It goes
arXiv:2609.13779v1 Announce Type: new Abstract: Force-controlled loco-manipulation requires a whole-body policy to coordinate locomotion and arm motion while regulating end-effector interaction forces
arXiv:2609.13737v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly deployed, the generation of harmful content has become a critical safety concern. Existing safeguards o
arXiv:2609.14384v1 Announce Type: new Abstract: What must a neural system be capable of to implement language? Current research annotates stimuli with linguistic variables and tests which electrodes,
arXiv:2609.14896v1 Announce Type: cross Abstract: A notable byproduct of LLM alignment training is mode collapse: the progressive loss of output diversity that narrows a model's expressivity at infere
arXiv:2609.13265v1 Announce Type: cross Abstract: Near-infrared (NIR) imaging does not consistently outperform standard color cameras for daytime agricultural traversability once spatial data leakage
arXiv:2609.15015v1 Announce Type: new Abstract: Synthetic perturbations appear to offer inexpensive calibration data for LLM evaluators in biomedical ML, where expert review is scarce. Yet a planted m
arXiv:2609.13519v1 Announce Type: new Abstract: Molecular design is most effective when generation mirrors the edits chemists actually make: extending a scaffold, replacing a substituent, or decoratin
arXiv:2609.13269v1 Announce Type: new Abstract: Gesture recognition on video is normally posed as classification: label each frame, then act on the label. That is adequate for control, where a command