All entries

Monica Hunter-Hart / Forbes: Havoc, which offers autonomous boats and software to control thousands of vessels at once, raised a 100M Series A led by Cobalt and Boardman Bay — Interest in drone boats

arXiv:2605.08456v1 Announce Type: cross Abstract: The realtime analysis and secure transmission of electrocardiogram ECG signals are critical for accurate diagnosis and safeguarding patient privacy in

arXiv:2509.23668v3 Announce Type: replace Abstract: Time series forecasting occurs in a range of financial applications providing essential decision-making support to investors, regulatory institution

arXiv:2605.10201v1 Announce Type: cross Abstract: Generalizable manipulation involving cross-type object interactions is a critical yet challenging capability in robotics. To reliably accomplish such

arXiv:2605.10717v1 Announce Type: cross Abstract: Multi-agent trajectory modeling traditionally focuses on forecasting, often neglecting more general tasks like trajectory completion, which is essenti

arXiv:2605.10536v1 Announce Type: cross Abstract: Rare semantic innovations in high-dimensional, mission-critical domains are often obscured by dense background contexts, a challenge we define as exti

arXiv:2605.09502v1 Announce Type: cross Abstract: Chain-of-thought (CoT) prompting assumes that generated reasoning reflects a model's internal computation. We show this assumption is wrong in a speci

arXiv:2602.01442v3 Announce Type: replace-cross Abstract: Gradient-based attribution is the workhorse of mechanistic interpretability, yet whether it reliably tracks causal importance at the component

arXiv:2605.09972v1 Announce Type: cross Abstract: End-to-end autonomous driving has witnessed rapid progress, yet existing benchmarks are increasingly saturated, with state-of-the-art models achieving

arXiv:2605.09308v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) excel at relational reasoning but face two persistent challenges: the lack of interpretable attribution for heterogeneous

arXiv:2605.10624v1 Announce Type: new Abstract: Model Predictive Control (MPC) is widely used to operate safety-critical infrastructure by predicting future trajectories and optimizing control actions

arXiv:2605.10621v1 Announce Type: new Abstract: Reachability analysis of neural networks, which seeks to compute or bound the set of outputs attainable over a given input domain, is central to certify

arXiv:2605.08292v1 Announce Type: cross Abstract: Sparse Mixture-of-Experts (MoE) models scale capacity by routing each token to a small subset of experts. However, their routers exhibit a fundamental

arXiv:2605.08232v1 Announce Type: new Abstract: High-fidelity experimental characterization of turbulent premixed flames remains limited by the cost and complexity of advanced diagnostics, particularl

arXiv:2605.08330v1 Announce Type: new Abstract: We present a hierarchical language-driven framework for robotic task and motion planning to improve natural, intuitive human-robot interaction in servic

arXiv:2410.14927v2 Announce Type: replace-cross Abstract: Automated equity trading requires converting noisy market and news signals into executable portfolio decisions under risk, turnover, and trans

arXiv:2512.21815v2 Announce Type: replace Abstract: Vision-language models (VLMs) achieve remarkable performance but remain vulnerable to adversarial attacks. Entropy, as a measure of model uncertaint

arXiv:2605.09465v1 Announce Type: new Abstract: High-precision heavy-duty grading is a common step in earthworks, traditionally carried out manually by skilled operators. Removing a significant amount

arXiv:2509.21484v3 Announce Type: replace Abstract: We study online convex optimisation with ell_q-Lipschitz losses, ell_p-regularised FTRL, and randomised two-point finite-difference gradient estimat

arXiv:2605.08864v1 Announce Type: new Abstract: We study online estimation in latent-variable models by recasting the problem as tracking a moving empirical equilibrium. Standard online EM and stochas

arXiv:2605.10546v1 Announce Type: new Abstract: Pixel-based deep reinforcement learning agents are typically trained on heavily downsampled visual observations, a convention inherited from early bench

Highlights: 👉 600+ voices across MiniMax, Cartesia, Deepgram, Rime, and more 👉 Search by prompt or audio sample 👉 Filter by 15+ attributes, including pitch, accent, language, age, emotion, and speakin

arXiv:2605.08665v1 Announce Type: new Abstract: Large reasoning models achieve high accuracy through extended chain-of-thought but generate 5--8 more tokens than necessary, applying verbose reasoning

arXiv:2602.09524v3 Announce Type: replace Abstract: Unsupervised industrial anomaly detection (UAD) is essential for modern manufacturing inspection, where defect samples are scarce and reliable detec

arXiv:2404.18923v5 Announce Type: replace Abstract: We introduce Holmes, a new benchmark designed to assess language models (LMs) linguistic competence - their unconscious understanding of linguistic

arXiv:2605.09348v1 Announce Type: cross Abstract: Large Language Models (LLMs) provide flexible natural language processing capabilities, while knowledge graphs (KGs) offer explicit and structured kno

Full-stack observability startup Hound Technology Inc., which does business as Honeycomb, introduced a number of new platform updates aimed at investigating artificial intelligence agent activity in p

arXiv:2605.08143v1 Announce Type: cross Abstract: Large language models encode vast factual knowledge that inevitably becomes outdated or incorrect after deployment, yet retraining is costly prohibiti

In this post, we demonstrate how Amazon FinTech teams are using Amazon Bedrock and other AWS services to build a scalable AI application to transform how regulatory inquiries are handled. Each team us

This article discusses how Chief Financial Officers at consulting firms can use Databricks' data and AI platform to improve operational margins and profitability. It likely covers strategies for lever

This OpenAI Academy article explores how finance teams leverage Codex, OpenAI's code generation model, to automate financial analysis, reporting, and data processing tasks. It likely covers practical

The modern web is extremely visual. People are busy and easily-distracted, and smart companies know they have just seconds to attract would-be customers with compelling images, videos, animations, and

arXiv:2504.10766v2 Announce Type: replace-cross Abstract: As the post-training of large language models (LLMs) advances from instruction-following to complex reasoning tasks, understanding how differe

arXiv:2605.09314v1 Announce Type: new Abstract: Language models can be persuaded to abandon factual knowledge. This vulnerability is central to AI safety, but its internal mechanism remains poorly und

arXiv:2605.10347v1 Announce Type: new Abstract: Recent advances in vision-language models have enabled mobile GUI agents to perceive visual interfaces and execute user instructions, but reliable predi

arXiv:2605.08348v1 Announce Type: new Abstract: The circuits framework in mechanistic interpretability aims to identify causally important sparse subgraphs of model components, typically evaluated by

arXiv:2605.09243v1 Announce Type: new Abstract: If a person can solve a task, can measuring their brain make it easier to train a model to solve that task too? Recent NeuroAI work suggests that supple

NVIDIA engineers and researchers utilize OpenAI's Codex, a large language model trained on code, to accelerate software development and improve productivity across their engineering workflows. The art

This article examines how open-source AI model ecosystems create compounding effects through community contributions, fine-tuning, and iterative improvements that accelerate innovation and accessibili

Sapu is an early-stage biopharmaceutical company developing treatments for hard-to-treat cancers. From its San Diego facility, the team is pioneering a nanomedicine pipeline that takes existing FDA-ap

arXiv:2605.10199v1 Announce Type: new Abstract: Full-duplex spoken dialogue requires a model to keep listening while generating its own spoken response. This is challenging for large language models (

This article explains how to implement and deploy GPU workloads in a truly serverless architecture, likely covering Modal's approach to abstracting away infrastructure management while providing GPU c

How to Convert Your ComfyUI Workflow into an APP Mode Workflow App Mode is a new way to view and run any ComfyUI workflow. When you enter App Mode, the node graph disappears and is replaced by a clean

arXiv:2605.08817v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) recently thrives in large language model (LLM) reasoning tasks. However, the reward sparsity and t

Hewlett Packard Enterprise Co. today is expanding its hybrid cloud and data platform portfolio with new private cloud, storage and cyber resilience offerings designed to simplify infrastructure modern

arXiv:2504.02373v3 Announce Type: replace-cross Abstract: In practical applications, low-light images are often compressed for efficient storage and transmission. Most existing methods disregard compr