Knowledge catalogue
arXiv:2609.26402v1 Announce Type: new Abstract: The discovery of novel inorganic materials drives technological breakthroughs in critical fields such as computing and energy storage. Generative AI has
arXiv:2609.23407v1 Announce Type: cross Abstract: Humans can effortlessly localize the direction of a sound source and integrate it with visual cues for reasoning, yet this remains challenging for emb
arXiv:2609.26624v1 Announce Type: cross Abstract: Sparse Gaussian processes achieve O(N) inference by replacing the kernel with an appropriate expansion in a fixed basis {phi_j} on the input space. Gi
arXiv:2609.23774v1 Announce Type: new Abstract: Probabilistic inference is generally only tractable in low-treewidth graphical models, limiting its effective applicability in high-treewidth settings.
On stage with @MistralAI . 🔥 From building models to putting them into the hands of developers, a closer look at how Mistral is shaping the next generation of AI products. Straight from the #AIEParis
arXiv:2609.26280v1 Announce Type: new Abstract: In this chapter, we investigate how classical machine learning models respond to small, targeted modifications in their parameters. We compare and contr
arXiv:2609.25705v1 Announce Type: cross Abstract: Federated learning (FL) is intrinsically heterogeneous: honest clients may have different data-generating models. On top of that, adversarial clients
arXiv:2609.26388v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have made them widely used for code-related tasks. Identifier names are statistically informative in n
arXiv:2609.26334v1 Announce Type: new Abstract: The dimensional collapse of representations in self-supervised contrastive learning is an ever-present issue. One notable technique to prevent such a co
arXiv:2609.26097v1 Announce Type: new Abstract: Remote-sensing (RS) multimodal large language models (MLLMs) are trained and evaluated only in English, while text-only instruction data covers over 100
arXiv:2609.26435v1 Announce Type: new Abstract: Drifting provides a direct route to one-step generative models, but applying it directly to stochastic transition modeling requires multiple samples of
I have been using open-webui and open-terminal. Open-terminal is installed in a VM and gives the agent a ton of control of it's own system that I keep away from my normal network. I find this gives th
OpenAI: OpenAI releases MentalHealthBench, an open benchmark to evaluate AI responses in realistic mental health conversations, developed with 80+ licensed experts — An open benchmark developed with m
@openai: OpenAI says ChatGPT Voice can now be powered by GPT-6 Astra, Sol, and Luna, use plugins like email and calendar, and be used in ChatGPT Work on web and mobile — We heard you loud and clear. C
Zoe Kleinman / BBC: OpenAI says it will give its AI cyber defense system Daybreak and GPT-5.6 Sol to the Ukrainian government for free to help it protect civilian infrastructure — The tech giant OpenA
arXiv:2603.17043v2 Announce Type: replace Abstract: Physics-aware multimodal large language models (MLLMs) can localize and characterize two-dimensional (2D) material flakes from optical microscopy im
arXiv:2609.26707v1 Announce Type: cross Abstract: Offline reinforcement learning and off-policy evaluation evaluates dynamic treatment rules based on retrospectively collected data prior to deployment
arXiv:2609.25710v1 Announce Type: cross Abstract: The statistical accuracy of neural networks depends on both their approximation power and the complexity of the class fitted from data. While increasi
arXiv:2507.15836v2 Announce Type: replace Abstract: In this work we study black-box privacy auditing, where the goal is to lower bound the privacy parameter of a differentially private learning algori
arXiv:2609.26052v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have recently emerged as a promising alternative to conventional Auto-Regressive (AR) Large Language Models (LLM
arXiv:2609.22987v1 Announce Type: new Abstract: Automated operations research (OR) modeling requires LLMs to translate natural-language decision problems into correct mathematical programs. Existing m
Database security controls are moving closer to enterprise data as artificial intelligence creates new access paths around traditional application defenses. The aim is to enforce authorization regardl
Data-layer security is becoming more important as automated systems gain broader access to sensitive information and business processes. Controls designed for predictable applications may not be enoug
Out today: Nemotron 3 Diarization, so you can implement speaker detection in your voice applications. 🗣️✅ And it's available day-0 on transformers and @Dell Enterprise Hub! Enterprises can implement o
arXiv:2506.11585v3 Announce Type: replace Abstract: We introduce OV-MAP, a novel approach to open-world 3D mapping for mobile robots by integrating open-features into 3D maps to enhance object recogni
arXiv:2609.22353v1 Announce Type: new Abstract: Mobile river monitoring robots must interpret obstacles and water boundaries that geographic waypoints alone cannot describe. On resource constrained pl
arXiv:2609.26249v1 Announce Type: new Abstract: Diffusion language models (dLLMs), such as LLaDA and Dream, have become competitive with autoregressive (AR) LLMs in generation quality while supporting
arXiv:2609.26355v1 Announce Type: new Abstract: Reinforcement learning has become a central component of large language model (LLM) post-training, yet token-level credit lacks a generally accepted mat
arXiv:2609.25630v1 Announce Type: new Abstract: Real-world reinforcement learning (RL) systems still struggle with the demands of contact-rich industrial manipulation, including micrometer-level preci
arXiv:2609.22770v2 Announce Type: cross Abstract: We study a parameterized hybrid ranker that fuses a dense embedding list and a sparse lexical list. The method has a small, explicit parameter vector:
arXiv:2609.25375v1 Announce Type: new Abstract: Global point-cloud registration remains challenging when limited overlap, repetitive geometry, and sensor noise produce correspondence sets dominated by
arXiv:2609.26199v1 Announce Type: new Abstract: A large graph is often available only in part: a crawl stopped by its budget, a panel, a partial dump. When the sampled fraction s is known by design th
arXiv:2609.25832v1 Announce Type: new Abstract: Part segmentation is a fundamental problem in computer graphics and 3D vision. Recent works have expanded 3D part segmentation beyond fixed taxonomies,
arXiv:2609.24876v1 Announce Type: new Abstract: In multi-agent social settings, model reliability varies across relationships. Beyond inferring what others will do, an agent must calibrate how confide
arXiv:2609.25396v1 Announce Type: new Abstract: Parallel coding agents can produce patches that work alone but fail when merged. This happens when one agent changes an interface or rule that another a
arXiv:2609.26219v1 Announce Type: cross Abstract: Long-running LLM agent workflows often revise interior context spans while retaining long suffixes. Although suffix tokens remain unchanged, altered c
arXiv:2609.25046v1 Announce Type: new Abstract: Peer review plays a central role in scholarly publishing, yet verifying whether reviewer claims are supported by manuscript evidence remains a largely m
arXiv:2609.25381v1 Announce Type: cross Abstract: We propose penalized nonreversible Langevin algorithms for sampling from pi(x)propto e^{-f(x)}mathbf 1_{mathcal C}(x), where mathcal Csubsetmathbb R^d
I am proud to release these quants of Qwen 3.8 27B. They beat the excellent ISTA and Unsloth quants byte-for-byte on three corpora. Both KLD and top 1% were tested 3x. It took a week of continuous GPU
arXiv:2609.25438v1 Announce Type: new Abstract: Diverse pretraining has been shown to be an effective method for learning reusable, domain-aware representations that provide a starting point for fine-
arXiv:2609.26629v1 Announce Type: new Abstract: Procedural character generation aims to populate games, simulations, and other virtual worlds with diverse characters. Large language models (LLMs) offe
arXiv:2609.26795v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) can reconstruct a captured scene photorealistically, but the resulting representation does not by itself support physical i
arXiv:2609.23695v1 Announce Type: new Abstract: Recent advances in Physical AI have accelerated the use of foundation models in autonomous systems such as unmanned aerial vehicles (UAVs), which must p
arXiv:2609.25057v1 Announce Type: cross Abstract: Radar pulse de-interleaving is a foundational Electronic Support Measures (ESM) task that aims to separate chronologically interleaved pulse streams f
arXiv:2609.25653v1 Announce Type: new Abstract: Large-scale manipulation demonstrations are essential for learning robust visuomotor policies, yet real-world data collection is expensive and difficult
If like me you enjoyed classics like Baldur's Gate 2, this is a small fun experiment. For anyone interested: https://www.youtube.com/live/8FhPfRKTucw?si=PMIVdHbZ-31PNwZD Qwen 3.8 Flash Next has amazin
arXiv:2609.25388v1 Announce Type: cross Abstract: A classical question in statistics is which observable quantities to condition on when drawing inferences about unobservable targets. For conformal pr
arXiv:2609.23023v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) require coordinated choices over network representation, sampling, loss construction, and optimization, while e
arXiv:2609.24881v2 Announce Type: new Abstract: In high-stakes decision-making applications of large language models (LLMs), practitioners require not only accurate LLMs but also uncertainty estimates
arXiv:2609.25754v1 Announce Type: new Abstract: Humanoid motion tracking policies rely on dense frame-by-frame references, limiting their use as high-level motion controllers for planning and interact
arXiv:2609.25538v1 Announce Type: new Abstract: While single-view 3D reconstruction has seen significant progress, extrapolating complex 3D structures from inherently ambiguous 2D observations remains
arXiv:2609.26581v1 Announce Type: cross Abstract: We study Polyak-type step-size selection for extragradient methods for solving deterministic and stochastic monotone root-finding problems. We show th
arXiv:2410.14788v4 Announce Type: replace-cross Abstract: Neural operator (NO) architectures learn nonlinear maps between infinite-dimensional function spaces and are widely used to accelerate simulat
arXiv:2609.26474v1 Announce Type: cross Abstract: Scattered light is common in biomedical images, yet its removal remains challenging. The difficulty arises from three aspects: first, aligned scattere
arXiv:2609.25969v1 Announce Type: new Abstract: Legged robots under sparse waypoint guidance must avoid moving obstacles using partial, rapidly changing LiDAR observations. We present LOOP (Latent-rec
arXiv:2609.24453v1 Announce Type: new Abstract: Predicting postprandial glycemic response (PPGR) is fundamental to personalized nutrition and type 2 diabetes management, yet existing approaches typica
arXiv:2609.25430v1 Announce Type: new Abstract: Neural surrogates can substantially accelerate computer-aided engineering (CAE) workflows, but their use in design requires uncertainty estimates that r
arXiv:2609.26310v1 Announce Type: new Abstract: Graph neural networks have achieved strong performance in node classification by aggregating information from graph neighborhoods. However, a single agg
arXiv:2609.23860v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) commonly reuse visual encoders pretrained with CLIP, although the features of these ViTs are ultimately consume
arXiv:2606.18473v2 Announce Type: replace Abstract: Machine unlearning for large language models (LLMs) aims to remove specified knowledge while preserving the rest of the model's capabilities. Howeve