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arXiv:2410.13735v3 Announce Type: replace Abstract: Conformal prediction provides model-agnostic uncertainty quantification with guaranteed coverage, but conventional methods often yield overly conser

arXiv:2610.17174v1 Announce Type: cross Abstract: Achieving complex, long-horizon robot behavior remains challenging because successful execution depends on skills grounded in a robot's physical affor

arXiv:2610.16992v1 Announce Type: new Abstract: Bayesian optimisation (BO) is a powerful framework for sample-efficient optimisation of expensive black-box functions, but its application to high-dimen

arXiv:2610.15110v1 Announce Type: cross Abstract: Cancer detection using AI methods and image databases faces several challenges, including limited and imbalanced image datasets, long algorithm traini

arXiv:2610.15565v1 Announce Type: new Abstract: Recent multimodal large language models achieve promising results on visual reasoning tasks, approaching human-level performance on existing STEM benchm

arXiv:2610.15280v1 Announce Type: new Abstract: Depth estimation and Gaussian reconstruction share a need for multi-scale feature processing, yet use different prediction interfaces and training objec

arXiv:2610.14293v1 Announce Type: new Abstract: Video diffusion models increasingly serve as priors for 4D generation, but the generated videos often lack geometric consistency. Recent approaches addr

arXiv:2610.18587v1 Announce Type: cross Abstract: Multimodal Emotion Recognition (MER) aims to understand human emotions by integrating information from multiple modalities such as speech and text. Ps

arXiv:2610.18634v1 Announce Type: new Abstract: Recent studies investigate the weight geometry through its spectral structure, which characterizes how the weights transform different input directions.

arXiv:2610.16170v1 Announce Type: new Abstract: Vision-language models (VLMs) can answer many geometric and physical reasoning questions correctly, yet still behave inconsistently in interaction, for

arXiv:2610.17742v1 Announce Type: cross Abstract: Dimensionality reduction can preserve the average performance of text embeddings even when a substantial fraction of their dimensions is removed. Aggr

arXiv:2610.15735v1 Announce Type: new Abstract: This paper presents a geometry-aware predictive control framework for bipedal obstacle crossing across walking and running regimes. The proposed approac

arXiv:2610.16122v1 Announce Type: new Abstract: 3D instance segmentation requires representations that are both geometrically structured and semantically discriminative. Pure 3D encoders model spatial

arXiv:2601.07632v5 Announce Type: replace Abstract: Discrete motion tokenization has recently enabled Large Language Models (LLMs) to serve as versatile backbones for motion understanding and motion-l

arXiv:2610.17845v1 Announce Type: new Abstract: Functional near-infrared spectroscopy (fNIRS) provides portable and spatially localized measurements of cortical hemodynamics, but differences in channe

arXiv:2610.18694v1 Announce Type: new Abstract: Vision-language models (VLMs) struggle with metric and multi-view relationships that remain implicit in RGB observations. Geometry foundation models rec

arXiv:2610.14852v1 Announce Type: new Abstract: Reinforcement learning (RL) is promising for spatial text-to-image generation, but existing work largely focuses on policy optimization, assuming accura

arXiv:2610.14541v1 Announce Type: new Abstract: Emerging strong Vision-Language Models (VLMs) have advanced navigation foundation models. However, these models still have unsatisfactory performance on

arXiv:2610.16455v1 Announce Type: new Abstract: 3D scene graph generation requires understanding both object semantics and metric spatial relations. However, existing open-vocabulary methods often str

arXiv:2610.17794v1 Announce Type: new Abstract: Contextual forecasting seeks to improve time series forecasting by incorporating forward-looking information, such as planned events, external condition

arXiv:2603.25072v2 Announce Type: replace Abstract: Video Large Language Models (VLMs) have achieved remarkable success in video understanding, but the significant computational cost from processing d

arXiv:2610.15064v1 Announce Type: new Abstract: The world has seen several threats that include resource depletion, food security, poverty and inequality, difficulties associated with urbanization, mi

arXiv:2610.14655v1 Announce Type: new Abstract: Pose Graph Optimization (PGO) is a classical and widely applied problem in state estimation for robotics, playing a fundamental role in localization, ma

arXiv:2610.17927v1 Announce Type: new Abstract: Autonomous navigation in real-world environments often requires long-horizon operation under partial observability and evolving goals. Existing mapless

arXiv:2610.17117v1 Announce Type: cross Abstract: Existing interpretability tools do not test whether a representation keeps the same content when only the phrasing changes. We treat each paraphrase p

arXiv:2610.15522v1 Announce Type: cross Abstract: Camera-based occupancy prediction provides geometric and semantic scene understanding for robot perception and has been adopted in autonomous vehicle

Foo Yun Chee / Reuters: Google DeepMind and Google Cloud plan to provide up to 200 European scientific researchers with access to their frontier AI models and $3M in compute credits — Google DeepMind

Google DeepMind and the Singapore Government have launched a partnership to deploy an artificial‑intelligence tool designed to help citizens identify and avoid scams. Announced in May 2026, the initia

arXiv:2610.16861v1 Announce Type: new Abstract: This paper presents GpFlash, a Gaussian process library that is focused on fast training and posterior evaluations, minimal memory usage, and scalabilit

Every local setup I tried for Qwen-Image 2.1 meant a Python env, a node graph and an evening of picking quantization, offloading and resolution for my card. Kokon is a free, open-source desktop app th

arXiv:2610.17321v1 Announce Type: cross Abstract: As demand for LLM inference grows and consumer GPUs grow more capable, edge deployment is becoming increasingly attractive. WebGPU is compelling in th

arXiv:2602.03945v2 Announce Type: replace Abstract: Simple row-wise predictors that score each row independently remain competitive with far more expressive architectures on tabular benchmarks, which

arXiv:2610.17062v1 Announce Type: new Abstract: We propose a mitigation to reward hacking in reinforcement learning. Our setup involves a misspecified reward function that gives rise to unintended beh

arXiv:2610.18471v1 Announce Type: new Abstract: Weight-space learning treats the weights of neural networks as data, processed by other models called metanetworks. A key challenge is that different we

arXiv:2505.02712v4 Announce Type: replace Abstract: Cellular reprogramming, the artificial transformation of one cell type into another, has been attracting increasing research attention due to its th

arXiv:2610.16272v1 Announce Type: new Abstract: Feed-forward reconstruction recovers camera poses and dense geometry from image sets whose views are assumed to come from a single scene. In practice, u

arXiv:2408.16717v4 Announce Type: replace Abstract: Due to the ongoing electrification of transportation systems, energy-based routing problems such as the Electric Vehicle Routing Problem (EVRP) are

arXiv:2405.03411v5 Announce Type: replace Abstract: Informed sampling techniques accelerate the convergence of sampling-based motion planners by biasing sampling toward regions of the state space that

arXiv:2610.18774v1 Announce Type: new Abstract: A robot needs a world model that predicts how its actions will change the scene and a policy that chooses those actions. Models are usually built and ev

arXiv:2607.08798v2 Announce Type: replace-cross Abstract: Adaptive volumetric finite element meshing traditionally requires iterative PDE solvers or heavily supervised, data-driven surrogates trained

arXiv:2610.18637v1 Announce Type: cross Abstract: A robot's world model must remember objects that leave the camera's view. FloWM, a learned world model, keeps them in a spatial grid of features that

🔮 Grok Bot email accounts and traffic will be larger than Gmail and 1000x more productive. Efficient Grok Bot email will liberate us from spam with high signal and low noise Claude Shannon would be pr

Elon Musk’s artificial intelligence company SpaceXSI, formerly xAI, today released Grok Voice 3.0, a new version of the speech-to-speech model behind its Voice Agent API. SpaceXSI is pitching the mode

Grok Voice 3.0 in Grok Bot is 🔥 SpaceXSI just launched Grok Voice 3.0, its new speech-to-speech model, which is currently beating GPT Live 1 and Gemini 3.8 Flash Live on all major benchmarks. I tried

Application observability startup groundcover Inc. today gave outside artificial intelligence coding agents such as Anthropic PBC’s Claude and OpenAI Group PBC’s Codex a way to hand production investi

arXiv:2610.15808v1 Announce Type: cross Abstract: Data flow underlies deep learning (DL) framework execution, including automatic differentiation and operator-fusion optimization. Bugs involving data