Knowledge catalogue
arXiv:2509.21671v2 Announce Type: replace Abstract: High-resolution neural datasets enable foundation models for the next generation of brain-computer interfaces and neurological treatments. The commu
arXiv:2605.08188v1 Announce Type: cross Abstract: Human attention is the gateway to conscious perception, memory and decision-making. However, its role in modern transformer models remains largely une
arXiv:2605.10804v1 Announce Type: new Abstract: Campus well-being underpins academic success, yet many universities lack effective methods for monitoring satisfaction and detecting mental health risks
NEW paper from Google DeepMind. (bookmark it) AI Co-Mathematician is an agentic research workbench for mathematicians, and it just hit 48% on FrontierMath Tier 4, a new high score among AI systems eva
Microservices testing company Signadot Inc. today launched /signadot-validate, a new skill that lets coding agents such as Anthropic PBC’s Claude Code, OpenAI Group PBC’s Codex and Cursor validate the
arXiv:2505.20001v5 Announce Type: replace Abstract: Multi-modal object Re-IDentification (ReID) aims to obtain complete identity features across heterogeneous modalities. However, most existing method
arXiv:2605.09387v1 Announce Type: new Abstract: While Large Language Models (LLMs) have catalyzed progress in embodied intelligence, a fundamental gap between their inherent probabilistic uncertainty
arXiv:2605.08452v1 Announce Type: new Abstract: The ability to derive precise spatial and physical insights is a cornerstone of vision-language models (VLMs), yet their poor performances in related sp
arXiv:2602.04549v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) revolutionized novel view rendering. Instead of inferring from dense spatial points, as implicit representations do, 3D
arXiv:2510.20797v2 Announce Type: replace-cross Abstract: Context compression reduces Transformer inference costs by replacing lengthy inputs with shorter pre-computed representations. It carries sign
Vercel has made Node.js 26.x available for use in Vercel Sandboxes, enabling developers to test and run applications with the latest Node.js runtime version. This update allows users to leverage new f
arXiv:2605.09328v1 Announce Type: new Abstract: Pre-trained text-to-image (T2I) diffusion models have shown strong potential for real-world image super-resolution (Real-ISR), owing to their noise-star
arXiv:2605.08144v1 Announce Type: cross Abstract: Diffusion models have achieved remarkable success across a wide range of generative tasks, yet their training paradigm largely treats injected noise a
arXiv:2605.08221v1 Announce Type: cross Abstract: This paper presents NoisyCoconut, a novel inference-time method that enhances large language model (LLM) reliability by manipulating internal represen
arXiv:2605.08306v1 Announce Type: cross Abstract: Body composition assessment (BCA) provides detailed information about the distribution of different tissue types in the body, enabling more precise ch
arXiv:2605.08913v1 Announce Type: cross Abstract: Autoregressive inference is typically assumed to scale predictably with decoding length, and key-value (KV) caching is widely regarded as a universall
arXiv:2605.08999v1 Announce Type: new Abstract: In machine learning, a critical class of decision-related problems concerns preventing predicted undesirable outcomes, referred to as the extit{avoiding
arXiv:2605.09058v1 Announce Type: cross Abstract: We introduce Nonlinear GENERIC Informed Neural Networks (N-GINNs), a deep learning framework for discovering evolution equations of systems governed b
Emma Roth / The Verge: Nonprofit RSL Media announces the Human Consent Standard, an AI licensing framework for use of people's work or likeness, backed by George Clooney and others — This new standard
arXiv:2605.10823v1 Announce Type: new Abstract: Reversible instance normalization (RevIN) and its successors (Dish-TS, SAN, FAN) have become the de facto plug-in for time-series forecasting, yet the m
arXiv:2605.08193v1 Announce Type: cross Abstract: Normalization Equivariance (NE), equivariance to global contrast and brightness transforms, improves robustness to distribution shift in image-to-imag
arXiv:2605.10379v1 Announce Type: new Abstract: Large language models (LLMs) have become capable mathematical problem-solvers, often producing correct proofs for challenging problems. However, correct
arXiv:2605.09490v1 Announce Type: new Abstract: Reasoning LLMs produce thousands of chain-of-thought tokens whose KV cache must reside in scarce GPU HBM. The dominant response -- permanently evicting
arXiv:2605.08778v1 Announce Type: new Abstract: Deploying LLMs in multi-turn dialogues facilitates jailbreak attacks that distribute harmful intent across seemingly benign turns. Recent training-based
arXiv:2605.10676v1 Announce Type: new Abstract: During MLLM decoding, attention often abnormally concentrates on irrelevant image tokens. While existing research dismisses this as invalid noise and fo
not every day @scaling01 and I agree. but he’s right. and most people won’t notice it happening, per the work of @informor. hot take: unrestricted LLMs are as dangerous as weapons of mass destruction
arXiv:2605.10061v1 Announce Type: cross Abstract: Futrell and Mahowald (2025) frame the success of neural language models (LMs) as supporting gradient, usage-based linguistic theories. I argue that LM
Gary Marcus references a conversation with someone named Haider, noting that despite Haider's typically optimistic outlook, he has shared documented evidence of expressing concerns about a particular
arXiv:2510.03895v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models represent a pivotal advance in embodied intelligence, yet they confront critical barriers to real-world de
Nous Portal is one easy subscription that gives you access to 300+ models, exclusive discounts, and bundles your tokens and paid tools together for hassle-free setup and simple billing. http://portal.
arXiv:2605.09950v1 Announce Type: cross Abstract: Most feature selection algorithms, especially wrapper methods, run inefficiently on CPU based platforms because of their high computational complexity
arXiv:2602.06382v2 Announce Type: replace Abstract: Achieving robust vision-based humanoid locomotion remains challenging due to two fundamental issues: the sim-to-real gap introduces significant perc
Announced today at SAP Sapphire — where NVIDIA founder and CEO Jensen Huang joined SAP CEO Christian Klein’s keynote by video — SAP and NVIDIA’s expanded collaboration helps enterprises run specialize
CNBC: Nvidia says that Jensen Huang is joining President Trump on his China trip; source: the president asked Huang to join after seeing media coverage of his absence — BEIJING — Nvidia CEO Jensen Hua
arXiv:2605.10155v1 Announce Type: new Abstract: Legal information in India remains largely inaccessible due to the complexity of legal language and the sheer volume of legal documentation involved in
arXiv:2605.09160v1 Announce Type: new Abstract: Learned representations are often invariant to rotational transformations, leaving individual dimensions non-identifiable and interchangeable. We study
arXiv:2605.10707v1 Announce Type: new Abstract: Object-centric view planning is a core component of active geometric 3D reconstruction in robotics, yet existing evaluations often conflate object compl
arXiv:2512.24552v2 Announce Type: replace Abstract: This paper proposes a novel second-order optimization algorithm based on the Optimal Control Principle (OCP), applicable to large-scale optimization
arXiv:2605.09055v1 Announce Type: cross Abstract: Recent agentic-robotics systems, from Code-asPolicies to modern vision-language-action (VLA) foundation models, presuppose that drivers, SDKs, or ROS-
arXiv:2605.09433v1 Announce Type: new Abstract: Existing preference datasets for text-to-image models typically store only the final winner/loser images. This representation is insufficient for rectif
arXiv:2605.08762v1 Announce Type: cross Abstract: Current omni-modal benchmarks mainly evaluate models under settings where multiple modalities are provided simultaneously, while the ability to start
arXiv:2605.09996v1 Announce Type: new Abstract: While multimodal large language models have advanced across text, image, and audio, personalization research has remained primarily vision-language, wit
arXiv:2605.08758v1 Announce Type: cross Abstract: Driven by the rapid expansion of e-commerce and small-batch production, the size of the intralogistics load unit of finished goods, semi-finished good
arXiv:2605.09200v1 Announce Type: new Abstract: We study adversarial noisy bandits given a known function class F. In each round, the adversary selects a function f in F, the learner chooses an arm, a
arXiv:2605.08368v1 Announce Type: new Abstract: Debates about large language model post-training often treat supervised fine-tuning (SFT) as imitation and reinforcement learning (RL) as discovery. But
arXiv:2605.10722v1 Announce Type: new Abstract: Molecular Graph Neural Networks (GNNs) are increasingly common in drug discovery, particularly for Quantitative Structure-Activity Relationship (QSAR) s
arXiv:2605.08400v1 Announce Type: cross Abstract: Dynamics of interacting systems in engineering, society, and nature often evolve over latent networks that govern which entities can interact. We stud
arXiv:2605.10818v1 Announce Type: new Abstract: Periodic signals are critical for representing physical and perceptual phenomena. Scalar, real angular measures, e.g., radians and degrees, result in di
arXiv:2605.09725v1 Announce Type: new Abstract: On-policy distillation (OPD), which supervises a student on its own sampled trajectories, has emerged as a data-efficient post-training method for impro
arXiv:2509.15816v5 Announce Type: replace Abstract: The Muon optimizer has demonstrated remarkable empirical success in handling matrix-structured parameters for training neural networks. However, a s
arXiv:2512.18248v3 Announce Type: replace Abstract: The low-rank adaptation (LoRA) algorithm for fine-tuning large models has grown popular in recent years due to its remarkable performance and low co
arXiv:2605.09606v1 Announce Type: cross Abstract: Recent advances in image-to-3D models have significantly improved the fidelity and accessibility of 3D content creation. Such a powerful reconstructio
arXiv:2605.10775v1 Announce Type: cross Abstract: A surprising phenomenon in the training of neural networks is the ability of gradient descent to find global minimizers of the training loss despite i
arXiv:2601.21619v2 Announce Type: replace-cross Abstract: Parallel thinking improves LLM reasoning through multi-path sampling and aggregation. In standard evaluations, due to a lack of sample-specifi
arXiv:2605.09757v1 Announce Type: new Abstract: Providing non-conservative uncertainty quantification for function estimates derived from noisy observations remains a fundamental challenge in statisti
arXiv:2605.09235v1 Announce Type: cross Abstract: One-step generative modeling has emerged as a leading approach to amortize the inference cost of diffusion and flow-matching models. Among distillatio
SpaceX fueled its new Starship V3 megarocket for the first time, setting a new record as the world's tallest rocket at approximately 408 feet (124.4 meters), surpassing the V2 by 4 feet. The successfu
arXiv:2605.09727v1 Announce Type: cross Abstract: A central challenge in reinforcement learning (RL) is to learn models that generalize beyond the tasks on which they are trained, a goal traditionally
Red Hat Enterprise Linux, the platform underpinning much of enterprise IT, has spent 20 years as the quiet foundation of enterprise computing. Now, as AI moves into production at scale, it’s becoming
arXiv:2605.10179v1 Announce Type: cross Abstract: Neural Flows efficiently model irregular multivariate time series by directly learning ODE solution trajectories with neural networks, bypassing step-