Knowledge catalogue
arXiv:2610.02717v1 Announce Type: new Abstract: A key challenge in bringing embodied intelligence into the real world is transferring capabilities from simulation to reality and enabling agents to con
arXiv:2610.02708v1 Announce Type: new Abstract: Wet-lab experimentation serves as the gold standard for hypothesis verification in scientific discovery; yet it is inherently labor-intensive, costly, a
arXiv:2506.05937v3 Announce Type: replace-cross Abstract: Reliability of deep learning models is critical for deployment in high-stakes applications, where out-of-distribution or adversarial inputs ma
arXiv:2610.02808v1 Announce Type: new Abstract: Adaptive multi-verifier systems are commonly compared through endpoint quality-cost gaps, even when the verifier catalog, availability, accounting, info
arXiv:2606.17011v2 Announce Type: replace-cross Abstract: Human interventions provide crucial corrective signals for post-training Vision-Language-Action (VLA) models. However, enabling seamless human
arXiv:2602.15013v2 Announce Type: replace Abstract: Text style transfer (TST) is naturally a supervised task - rewrite a sentence in a target style while preserving its meaning - yet the parallel corp
arXiv:2610.02469v1 Announce Type: new Abstract: Robotic manipulators operating over long durations often experience uneven joint degradation, which causes the weakest actuator to fail prematurely, lea
arXiv:2610.02242v1 Announce Type: cross Abstract: Chemical reaction-condition optimization -- choosing the catalyst, ligand, solvent, reagent, temperature, time, and atmosphere that jointly maximize y
arXiv:2610.03013v1 Announce Type: new Abstract: Category-level object pose estimation predicts the rotation, translation, and metric size of unseen instances within known categories. Many accurate RGB
arXiv:2610.03303v1 Announce Type: new Abstract: Uncertainty quantification (UQ) for random partial differential equations (PDEs) is ubiquitous in computational science and engineering. However, classi
arXiv:2610.03106v1 Announce Type: cross Abstract: The subseasonal-to-seasonal (S2S) timescale, roughly from two weeks to two months ahead, is a critical forecast window for sectors such as agriculture
arXiv:2610.03132v1 Announce Type: cross Abstract: Generative planners based on diffusion/flow matching can learn to synthesize long-horizon trajectories from demonstrations. However, real-world deploy
arXiv:2610.02981v1 Announce Type: new Abstract: Source-Free Domain Adaptation (SFDA) aims to adapt a source-pretrained model to an unlabeled target domain without access to the original source domain.
Ben Berkowitz / Axios: Sam Altman says he's “very uncomfortable” with attributing religious force to AI, calling it “a real safety issue”, as Anthropic engages with religious leaders — OpenAI CEO Sam
OpenAI Group PBC Chief Executive Sam Altman insists that the security risks of artificial intelligence need to be taken seriously. But unlike his counterpart Dario Amodei of Anthropic PBC, he believes
Sam Altman thinks that the benefits of AI will be so great that 'the world should accept some bad things happening' along the way. The OpenAI CEO pointed to hacks, scams, and 'other bad things' as cos
arXiv:2610.03165v1 Announce Type: new Abstract: Several variance-reduced versions of REINFORCE based on importance sampling achieve an improved O(epsilon^{-3}) sample complexity to find an epsilon-sta
arXiv:2610.02804v1 Announce Type: new Abstract: Vision-language-action (VLA) models often require costly real-world demonstrations to adapt to contact-rich manipulation tasks, particularly when genera
arXiv:2610.03372v1 Announce Type: new Abstract: Training long-horizon agents to solve complex tasks requires effective supervision over extended interaction sequences. However, sparse terminal rewards
arXiv:2604.05088v2 Announce Type: replace-cross Abstract: We propose ScalarFedLQR, a communication-efficient federated algorithm for model-free learning of a common policy in linear quadratic regulato
arXiv:2610.02611v1 Announce Type: cross Abstract: Fine-resolution precipitation estimates support flood risk assessment and water management, but coarse satellite products cannot resolve rainfall with
arXiv:2610.02826v1 Announce Type: new Abstract: Successful trajectories on difficult tasks provide valuable supervision for model improvement, but specialized harnesses introduce interventions that ma
arXiv:2610.02874v1 Announce Type: new Abstract: Scalable driving simulators typically execute vehicle commands using prescribed behavioral or kinematic rules, overlooking the physics of tire-road inte
arXiv:2511.21739v2 Announce Type: replace-cross Abstract: We present the first large-scale analysis of AI foundation model usage in science -- not just citations or keywords. We find that adoption has
arXiv:2610.02322v1 Announce Type: new Abstract: Real-world scenes are compositional: bricks, blades of grass, pebbles, and tree leaves recur across human-built and natural environments. Existing neura
arXiv:2610.02343v1 Announce Type: new Abstract: Geometric understanding supports endoscopic navigation and robotic assistance, but learning reliable endoscopic geometry faces two challenges: scarce ge
arXiv:2610.02466v1 Announce Type: cross Abstract: We present sparse dictionary differentiable predictive control (SD-DPC), a framework for learning sparse, interpretable feedback policies for nonlinea
arXiv:2610.03313v1 Announce Type: cross Abstract: Existing machine learning weather forecasting models typically generate forecasts through autoregressive rollouts at a fixed temporal resolution. Whil
arXiv:2610.03073v1 Announce Type: cross Abstract: Security workflows need models that turn complex observations and explicit policies into decisions. System One models introduced by Jev return typed p
arXiv:2610.03089v1 Announce Type: cross Abstract: Modern Computer Use Agents (CUAs) directly interact with graphical user interfaces and execute third-party web tools, exposing them to indirect prompt
arXiv:2610.02361v1 Announce Type: cross Abstract: Large language model (LLM)-driven evolutionary search is a powerful paradigm for automated program and algorithm discovery, yet existing systems are l
arXiv:2610.02876v1 Announce Type: new Abstract: A multimodal large language model that correctly reports a spatial fact does not necessarily use that fact in subsequent reasoning. To study this distin
arXiv:2610.02610v1 Announce Type: new Abstract: The research presented here focuses on modeling machine-learning performance. The thesis introduces Seer, a system that generates empirical observations
arXiv:2610.03249v1 Announce Type: cross Abstract: Deploying a pretrained controller exposes it to conditions that are absent from its training data. Sensor drift, outright sensor failure and accumulat
arXiv:2610.02710v1 Announce Type: cross Abstract: Terminal agents are increasingly deployed beyond software engineering in science and other specialized domains. Constructing training environments req
arXiv:2610.02994v1 Announce Type: cross Abstract: LLM agents often fail mid-task due to invalid tool calls, repeated actions, or poorly grounded reasoning, and learning from these failures is a path t
arXiv:2610.03268v1 Announce Type: new Abstract: Touche 2026 extends causality extraction to counter-causal claims: news sentences whose surface form appears causal but whose meaning denies the causati
arXiv:2610.02456v1 Announce Type: cross Abstract: AI coding agents are untrusted system components, yet they require autonomy on the developer machines they run on. This contradiction is a security pr
arXiv:2610.03689v1 Announce Type: new Abstract: We examine the transfer of a pretrained SigLIP2 image encoder to seven class fire risk classification from aerial imagery. We introduce a reproducible p
arXiv:2610.03019v1 Announce Type: new Abstract: Hybrid statistical-neural pipelines often assume that a successful statistical first stage leaves a cleaner and more learnable residual target. We exami
arXiv:2610.02702v1 Announce Type: new Abstract: Multi-agent debate is increasingly used to reach consensus among LLM agents, yet agents often yield to a unanimous majority. When an agent changes its a
arXiv:2610.02784v1 Announce Type: new Abstract: Tactile sensing provides essential contact information for robotic manipulation, yet incorporating it into pretrained vision-language-action (VLA) model
arXiv:2610.03679v1 Announce Type: new Abstract: The dynamics of cells, organisms, and fluids are often modeled as probability distributions evolving over time. Reconstructing and extrapolating this ev
arXiv:2610.02304v1 Announce Type: cross Abstract: Existing Simulink benchmarks mainly evaluate whether generated models compile, execute, or resemble a reference model. These criteria do not establish
arXiv:2610.03475v1 Announce Type: cross Abstract: Many reinforcement-learning (RL) problems are non-stationary yet structured and can be decomposed into phases, each with its own transition probabilit
arXiv:2610.03482v1 Announce Type: new Abstract: Hallucination detection is particularly important for medical language models, but repeated-sampling approaches are expensive and existing uncertainty-h
arXiv:2610.02788v1 Announce Type: new Abstract: Transferring robotic skills from simulation to reality requires task knowledge that remains usable across differences in perception, dynamics, and embod
GitHub (llama.cpp fork) : https://github.com/sky-is-green/prism-ml-llama.cpp (Prebuilt binaries there to try instantly) Draft model : https://huggingface.co/SkyIsNotGreen/Scion-35B-A3B-mtp-drafter sub
arXiv:2610.02953v1 Announce Type: new Abstract: Long-context LLM serving is increasingly bottlenecked by KV-cache memory, especially in resource-constrained scenarios. Among existing KV-cache compress
arXiv:2610.02324v1 Announce Type: cross Abstract: Foundation multimodal large language models are designed to support a broad spectrum of capabilities across diverse domains. Multi-teacher on-policy d
arXiv:2610.03082v1 Announce Type: new Abstract: Bridges contribute significantly to transportation connectivity and urban development. Therefore, reliable bridge monitoring is crucial for protecting p
So let me get this straight, now we have to call every piece of AI SI, even • ELIZA, 1965 which was just keyword matching and certainly not super or intelligent • Deep Blue, which could play chess but
So much reporting on the Claude or OpenAI usage of the same handful of technology companies with competing products & huge cloud infrastructure of their own. There are many, many more firms out there
arXiv:2610.02386v1 Announce Type: cross Abstract: We present a comprehensive overview of the challenges and opportunities in social bot detection in the context of the rise of sophisticated AI-based c
arXiv:2610.02360v1 Announce Type: new Abstract: Vision-language-action (VLA) policies enable diverse robotic manipulation but can fail during execution without recognizing their own errors. Human obse
arXiv:2610.03029v1 Announce Type: new Abstract: Gene set analysis is a cornerstone of functional genomics, yet it remains labor-intensive and heavily dependent on manual curation and expert biological
Our production recommender at Yandex Music has 15+ candidate generators feeding pre-ranking and ranking models with hundreds of features. LLMs showed that one end-to-end model can take over work that
arXiv:2610.02338v1 Announce Type: cross Abstract: A growing body of work suggests that tactile sensing gives robot policies contact information that complements vision in dexterous manipulation. Howev
arXiv:2610.03195v1 Announce Type: new Abstract: As LLM agents decide on users' behalf which product to buy, which hotel to book, or which paper to cite, a preference for items from certain sources (th
Marina Temkin / TechCrunch: Sources: AI inference-chip startup Etched is in early talks to raise funding at a 40B-50B valuation, up from 21B in August — Although it's only been a couple of months sinc