applications

arXiv:2609.31881v1 Announce Type: new Abstract: Dynamic text-attributed graphs (DTAGs), where nodes, edges, and textual attributes evolve over time, are crucial in applications such as social networks

arXiv:2609.33937v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) and Generalized Category Discovery (GCD) are traditionally treated as disjoint problems: the former adapts models to domain s

arXiv:2609.32384v1 Announce Type: new Abstract: Real-world time series are inherently non-stationary, with trends, periodic patterns, and uncertainty evolving over time. While the Fourier domain offer

arXiv:2609.34156v1 Announce Type: new Abstract: Prediction-powered inference (PPI) and its power-tuned extension (PPI++) improve confidence intervals by combining a small gold-standard labeled sample

arXiv:2609.34232v1 Announce Type: new Abstract: Images and videos have long helped people understand what happened and how a work came into being. Generative systems complicate that role. Realistic me

arXiv:2609.33257v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to forecast real-world events, but access to the strongest individual forecaster may be costly or oth

Using the biggest model for every task can work in a demo. In production, cost, latency, and task-specific quality can tell a different story. At ODSC AI West 2026, Rob Ferguson, VP of Technology and

arXiv:2609.33603v1 Announce Type: new Abstract: Reliable optical chemical structure recognition (OCSR) is essential for building high-quality chemical data from scientific literature, yet even small r

arXiv:2609.31697v1 Announce Type: new Abstract: Low-light conditions can significantly degrade the ability of vision-language models (VLMs) to accurately describe human actions in videos. In this work

arXiv:2609.34199v1 Announce Type: new Abstract: Humanoid loco-manipulation demands coordinated body and hand behavior, while conventional robot pre-training data provide limited coverage of such whole

arXiv:2609.34981v1 Announce Type: new Abstract: World action models (WAMs) predict the future alongside actions during training. Due to the heavy computation cost of video denoising, whether the futur

arXiv:2609.32898v1 Announce Type: new Abstract: Pretrained tabular foundation models process every dataset at a fixed depth, with inference costs growing with dataset size. To address this, we present

arXiv:2609.35416v1 Announce Type: new Abstract: Continuous video counting requires distinguishing new observations from new objects or completed events. We introduce StaMina (State Maintenance), which

arXiv:2411.04707v4 Announce Type: replace Abstract: Deep neural networks achieve strong performance on complex tasks but are often regarded as 'black boxes,' which limits their adoption in domains whe

arXiv:2609.31166v1 Announce Type: cross Abstract: Recommender systems have traditionally been developed for platforms. However, this has given rise to many phenomena that may be advantageous for platf

arXiv:2609.31197v1 Announce Type: new Abstract: Machine learning for scientific discovery is almost systematically data bound. Producing relevant high quality data, under budget constraints, is amongs

AppDirect Inc., the cloud-based business commerce platform and marketplace provider, today announced it acquired Soul Machines Ltd., an artificial intelligence human-like avatar experience provider, t

arXiv:2609.31157v1 Announce Type: new Abstract: Multi-dimensional time series, inherently tensorial, are common in practice. Despite great progress in time series anomaly detection, most existing meth

arXiv:2609.31165v1 Announce Type: cross Abstract: Speech-breath segmentation is a fundamental preprocessing step in respiratory audio analysis, enabling applications such as respiratory acoustic bioma

arXiv:2609.31339v1 Announce Type: cross Abstract: Reconstructing environments where parts of the scene change between captured image sets poses a challenge for 3D scene reconstruction. We present Chro

arXiv:2609.31381v1 Announce Type: new Abstract: Context projection replaces older tool observations with compact, addressable excerpts, reducing repeated input while potentially adding evidence-retrie

“connect[ing] AI to the internet … safely with current technology is not a realistic goal...” Regardless of how well you think OpenAI security did their job, the thing people should take from this is

arXiv:2609.30360v1 Announce Type: cross Abstract: Inspired by the problem of identifying the best model from a collection of large language models (LLMs) with heterogeneous querying costs, we formulat

arXiv:2607.11347v2 Announce Type: replace Abstract: Neural networks increasingly inform consequential decisions, making their reliability increasingly important. Yet their internal mechanisms provide

arXiv:2609.30935v1 Announce Type: cross Abstract: Continual fine-tuning is essential for large language models (LLMs) to dynamically adapt to real-world environments, yet it inevitably suffers from ca

arXiv:2609.30880v1 Announce Type: new Abstract: Time series foundation models (TSFMs) are pretrained on series from diverse domains, where demand series make up only a small fraction. Demand data has

Florida has sought a temporary injunction against OpenAI, arguing that large‑language model development without third‑party approved safety guardrails poses an existential threat and preys on vulnerab

Deploy two generative media models from one AWS vLLM-Omni Deep Learning Container on Amazon SageMaker AI. Generate an image with FLUX.2-klein through real-time inference, then animate it into video wi

arXiv:2512.18640v3 Announce Type: replace-cross Abstract: Event cameras offer a high temporal resolution over traditional frame-based cameras, which makes them suitable for motion and structure estima

arXiv:2609.30543v1 Announce Type: new Abstract: As robots transition from structured factory settings into homes, they are required to interact with an ever-increasing variety of objects. Many tasks r

arXiv:2609.30571v1 Announce Type: new Abstract: Language models are often evaluated on curated benchmarks that underrepresent the complexity of enterprise deployments. We introduce HARDEN, a constrain

“I dislike the passive vibe from OpenAI and the other companies that the breakneck pace of progress is simply happening to them, rather than an active choice they are deliberately making.” Good essay.

Reuters: IPO filing: Anthropic's seven co-founders will initially have 50.1% of the total voting power through a new “Founder LLC” aimed at serving the common good — Anthropic has long positioned itse

Echo Wang / Reuters: IPO prospectus: Anthropic reports a net loss of 42B in 2025, with operating losses of 8B+; revenue grew 12x to ~$4.6B, ~25% of which came from two customers — Anthropic is making

Meta Platforms Inc. is launching a new business unit that will provide artificial intelligence services to enterprises. The Meta Enterprise Platform, as it’s called, will be led by longtime technology

arXiv:2609.30795v1 Announce Type: new Abstract: Existing human motion diffusion methods provide strong motion generation quality, and recent style transfer models can inject target style cues, but fin

arXiv:2609.30770v1 Announce Type: cross Abstract: General-purpose robot models increasingly rely on large and diverse datasets. For embodied 3D navigation, however, existing data sources face a fundam

Not bad Grok 4.7 xHigh ranks #1 in Artificial Analysis Cyber Index It's a powerful frontier model performing at the highest level in enterprise cyber defense Outperforming Fable 5.1 Max, Opus 5.5, Ast

As artificial intelligence matures, the security guardrails — and the computer system itself — are changing. This week, the conversation centered around agents going rogue. Better guardrails are neede

arXiv:2609.30988v1 Announce Type: new Abstract: Real-world image super-resolution (SR) requires recovering perceptually realistic high-resolution images from complex low-resolution observations while

arXiv:2609.31025v1 Announce Type: cross Abstract: Precise, high-speed control remains challenging for robots with complex actuation dynamics. Learning directly on hardware is further constrained by th

arXiv:2510.05191v3 Announce Type: replace-cross Abstract: Conditional generation and disentangled representation learning are central to controlled generation across audio, vision, and multimodal doma

arXiv:2609.30547v1 Announce Type: new Abstract: Audience sizing is a critical component of digital marketing. It enables precise resource allocation, campaign planning, and performance optimization. T

arXiv:2609.31337v1 Announce Type: new Abstract: Building a robotic manipulation system requires connecting perception, planning, and control through carefully designed representations and interfaces.

arXiv:2609.31498v1 Announce Type: cross Abstract: Search is one of the most important features in e-commerce, directly driving customer engagement and business growth. A good product search system mus

arXiv:2609.30517v1 Announce Type: cross Abstract: Recent progress in speech-driven 3D facial animation has improved vertex-level reconstruction quality, but speech-consistent visible articulation rema