Knowledge catalogue
arXiv:2605.06226v2 Announce Type: replace Abstract: Accurate and timely diagnosis is essential for effective treatment, particularly in the context of rare diseases. However, current diagnostic workfl
arXiv:2605.08757v1 Announce Type: new Abstract: We present a visuo-tactile data-collection system that generates temporally structured, contact-rich demonstrations for imitation learning. Conventional
arXiv:2605.08692v1 Announce Type: cross Abstract: Post-training weight-only quantization to 4 bits is widely used to reduce the memory and compute costs of large language model inference. Existing PTQ
arXiv:2605.09811v1 Announce Type: new Abstract: Multi-robot simultaneous localization and mapping (SLAM) is a fundamental task in multi-robot operations. Robots must have a common understanding of the
arXiv:2605.09678v1 Announce Type: new Abstract: While extremely powerful and versatile at various tasks, the thinking capabilities of large language models (LLMs) are often put under scrutiny as they
arXiv:2605.09755v1 Announce Type: cross Abstract: The power method is one of the most fundamental tools for extracting top principal components from data through low-rank matrix approximation. Yet, wh
arXiv:2605.09034v1 Announce Type: new Abstract: Zeroth-order (ZO) optimization has become increasingly popular and important in fine-tuning large language models (LLMs), especially on edge devices due
arXiv:2605.10575v1 Announce Type: cross Abstract: Safe fine-tuning defenses are often endorsed on the basis of a held-out gap reduction, but the same reduction can come from sampling noise, subject ar
arXiv:2605.06042v2 Announce Type: replace Abstract: Flapping-wing micro aerial vehicles offer quieter and safer operation than rotary-wing drones, yet achieving precise autonomous control of bird-scal
arXiv:2605.08887v1 Announce Type: new Abstract: Self-evolving agents present a promising path toward continual adaptation by distilling task interactions into reusable knowledge artifacts. In practice
arXiv:2602.06457v2 Announce Type: replace Abstract: Online bilevel optimization (OBO) has emerged as a powerful framework for many machine learning problems. Prior works have developed several algorit
arXiv:2603.01743v2 Announce Type: replace Abstract: Anticipating future actions in videos is challenging, as the observed frames provide only evidence of past activities, requiring the inference of la
arXiv:2510.18184v3 Announce Type: replace-cross Abstract: Large language models (LLMs) excel at generating fluent text, but their internal reasoning remains opaque and difficult to control. Sparse aut
arXiv:2605.10654v1 Announce Type: cross Abstract: We consider the active learning problem where the goal is to learn an unknown function with low prediction error under an unknown Boltzmann distributi
arXiv:2605.08429v1 Announce Type: cross Abstract: Post-deployment monitoring of healthcare AI requires statistically valid, label-efficient methods, but gold-standard labels from clinician chart revie
arXiv:2605.10162v1 Announce Type: new Abstract: Reducing the annotation cost of oriented object detection in remote sensing remains a major challenge. Recently, sparse annotation has gained attention
arXiv:2605.10315v1 Announce Type: cross Abstract: Generative tabular augmentation is appealing in data-scarce domains, yet the prevailing focus on distributional fidelity does not reliably translate i
arXiv:2605.10075v1 Announce Type: new Abstract: Large language models (LLMs) require reliable evaluation from pre-training to test-time scaling, making evaluation a recurring rather than one-off cost.
arXiv:2605.08567v1 Announce Type: new Abstract: Action-conditioned world models (ACWMs) have shown strong promise for video prediction and decision-making. However, existing benchmarks are largely res
arXiv:2605.08408v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) provide a flexible framework for solving forward and inverse problems governed by partial differential equation
arXiv:2605.10741v1 Announce Type: new Abstract: Fine-tuning large language models with LoRA requires choosing a rank r before training starts. Existing approaches either extract rank-1 components sequ
arXiv:2605.08734v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) reparameterizes a weight update as a product of two low-rank factors, but the Jacobian J_{G} of the generator mapping the f
arXiv:2605.09455v1 Announce Type: new Abstract: Remote sensing image fusion aims to create a high-resolution multi/hyper-spectral image from a high-resolution image with limited spectral information a
arXiv:2605.10044v1 Announce Type: cross Abstract: Action chunking emerged as a pivotal technique in imitation learning, enabling policies to predict cohesive action sequences rather than single action
arXiv:2605.10470v1 Announce Type: new Abstract: Super-resolution (SR) is a severely ill-posed problem with inherent ambiguity, as widely recognized in both empirical and theoretical studies. Although
arXiv:2605.09707v1 Announce Type: cross Abstract: Training neural networks to satisfy universal constraints over continuous domains poses unique challenges. Common examples include Lyapunov Neural Net
arXiv:2512.13919v2 Announce Type: replace Abstract: This work shows how adaptivity can enhance value realization of digital twins in civil engineering. We focus on adapting the state transition models
arXiv:2605.09623v1 Announce Type: cross Abstract: In recent years, the use of artificial intelligence on resource-constrained IoT devices has grown significantly. However, existing approaches to DNN p
arXiv:2510.04988v3 Announce Type: replace Abstract: The vast majority of modern deep learning models are trained with momentum-based first-order optimizers. The momentum term governs the optimizer's m
arXiv:2511.06216v4 Announce Type: replace Abstract: Graph contrastive learning (GCL) learns node and graph representations by contrasting multiple views of the same graph. Existing methods typically r
arXiv:2605.10239v1 Announce Type: new Abstract: This work explores a simple yet powerful lightweight adapter design for feed-forward 3D Gaussian Splatting (3DGS). Existing methods typically apply comp
arXiv:2410.13181v2 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) have been remarkable. Users face a choice between using cloud-based LLMs for generation quality
arXiv:2605.08130v1 Announce Type: new Abstract: We present a framework for the simultaneous symbolic recovery of a function and its antiderivative from data. The framework rests on three ideas. First,
arXiv:2605.08161v1 Announce Type: new Abstract: Tumor segmentation in whole-body PET/CT imaging is crucial for precise disease evaluation and treatment planning. However, it remains challenging due to
MatterSim is expanding what AI can do for materials science—from faster large-scale simulations to MatterSim-MT, a new multi-task model for simulating properties beyond potential energy surfaces alone
arXiv:2605.09902v1 Announce Type: new Abstract: Adversarial perturbations can mislead Multimodal Large Language Models (MLLMs) recognize a benign image as a specific target object, posing serious risk
arXiv:2605.09337v1 Announce Type: new Abstract: We propose FAR-SIGN (Fully Asynchronous Robust optimization via SIGNed directional projections) for adversary-resilient learning in parameter-server--wo
AfD bei 28%, inzwischen hat sich der Abstand zur Union (22%) auf 6 Punkte vergrößert. Gleichzeitig sinkt auch das Verständnis für die 'Brandmauer'. Deutschland will den Wandel - wir sind dafür bereit.
arXiv:2605.10566v1 Announce Type: cross Abstract: Probabilistic linear solvers (PLSs) return probability distributions that quantify uncertainty due to limited computation in the solution of linear sy
After seeing the new OpenAI and Thinking Machines voice APIs, I did finally order a Reachy. Way more excited to talk to this thing than a Google puck Reachy is mad, but RAM costs + tariffs are forcing
After studying 300 Leetcode Hards, solving every Jane Street puzzle from the Dwarkesh ads, and watching one Horace He lecture, he finally landed the $400k annualized Jane Street internship. Unfortunat
arXiv:2605.10555v1 Announce Type: new Abstract: As AI agents transition from research prototypes to enterprise production systems, the tool interfaces they consume remain rooted in human-oriented CRUD
arXiv:2602.04284v2 Announce Type: replace Abstract: Managing agent context (e.g., thought and observation) during multi-turn agent-environment interactions is an emerging strategy to improve agent eff
arXiv:2603.22868v2 Announce Type: replace-cross Abstract: Agentic computing systems, while immensely capable, raise serious security, privacy, and safety concerns. A key issue is that the full set of
arXiv:2605.10365v1 Announce Type: new Abstract: Autonomous agents have rapidly matured as task executors and seen widespread deployment via harnesses such as OpenClaw. Safety concerns have rightly dra
arXiv:2605.10380v1 Announce Type: new Abstract: LLM-based agents deliver state-of-the-art performance across tasks but incur high end-to-end latency on edge devices. We introduce Agent-X, a software-o
arXiv:2605.08647v1 Announce Type: cross Abstract: Multi-agent systems achieve state-of-the-art outcomes through peer collaboration. However, when an agent in the pipeline silently drops a constraint,
arXiv:2605.08715v1 Announce Type: cross Abstract: LLM-based multi-agent systems are increasingly deployed on long-horizon tasks, but a single decisive error is often accepted by downstream agents and
arXiv:2605.08956v1 Announce Type: new Abstract: A growing body of work pursues AI scientists capable of end-to-end autonomous scientific discovery. This position paper argues that although they alread
arXiv:2605.09186v1 Announce Type: new Abstract: Mixed-integer programming (MIP) research is both mathematically sophisticated and engineering-intensive: testing an algorithmic hypothesis within a bran
arXiv:2605.10384v1 Announce Type: new Abstract: Agentic artificial intelligence (AI) is a natural fit for Internet of Things (IoT) and edge systems, but edge deployments are often constrained to model
Agentic security operations startup Exaforce Inc. today announced that it has raised 125 million in new funding to scale up its AI-driven security operations platform and expand its real-time threat r
arXiv:2605.08704v1 Announce Type: new Abstract: Multi-agent reasoning has shown promise for improving the problem-solving ability of large language models by allowing multiple agents to explore divers
arXiv:2406.12708v3 Announce Type: replace Abstract: Peer review is fundamental to the integrity and advancement of scientific publication. Traditional methods of peer review analyses often rely on exp
arXiv:2605.10286v1 Announce Type: new Abstract: Building effective clinical decision support systems requires the synthesis of complex heterogeneous multimodal data. Such modalities include temporal e
arXiv:2605.08813v1 Announce Type: new Abstract: Large Language Model-based Multi-Agent Systems (MAS) have demonstrated remarkable capabilities in complex tasks. However, manually designing optimal com
arXiv:2605.08756v1 Announce Type: new Abstract: Automatic heuristic design (AHD) has emerged as a promising paradigm for solving NP-hard combinatorial optimization problems (COPs). Recent works show t
arXiv:2505.18184v2 Announce Type: replace-cross Abstract: The increase in cardiac and pulmonary diseases presents an alarming and pervasive health challenge on a global scale responsible for unexpecte
arXiv:2605.08480v1 Announce Type: new Abstract: Individuals with Alzheimer's disease (AD) and Alzheimer's disease-related dementia (ADRD) experience memory and thinking changes that impact their abili
Vercel's AI Gateway production index is a monitoring tool that tracks the performance and reliability of AI services and models in production environments. It likely provides metrics on latency, uptim