Knowledge catalogue
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
arXiv:2610.14809v1 Announce Type: new Abstract: Influence functions provide an efficient alternative to retraining for assessing the effects of removing or reweighting training data. For groups, howev
arXiv:2610.16489v1 Announce Type: new Abstract: Reinforcement learning (RL) can substantially improve the reasoning capabilities of large language models, but an effective training run requires consid
arXiv:2610.16817v1 Announce Type: new Abstract: Progressive depth growth builds large networks by starting with shallow models and inserting layers during training. Recent advances in large language m
arXiv:2506.10946v3 Announce Type: replace Abstract: Unlearning large language models (LLMs) is important due to copyright and privacy concerns. A key challenge is unintended forgetting, where removing
arXiv:2610.15829v1 Announce Type: new Abstract: Hard-margin SVM training is the distance problem between two convex hulls, which the Triangle Algorithm (TA) solves with a certified duality gap. We pro
arXiv:2610.16654v1 Announce Type: new Abstract: Flow matching models are typically trained to transport a Gaussian source to the data distribution, with source and target samples paired independently.
arXiv:2610.15856v1 Announce Type: new Abstract: DiffusionNFT (NFT) fine-tunes diffusion models toward task-specific rewards, but optimizing these rewards does not guarantee fidelity to the full prompt
arXiv:2610.18125v1 Announce Type: new Abstract: Training-free diffusion-based compression methods repurpose the generative priors of a diffusion or a flow model to compress data without retraining the
arXiv:2610.17348v1 Announce Type: new Abstract: Modeling 3D hair strands is challenging due to complex hairstyle geometry, scarce high-quality training data, and incomplete or noisy input observations
arXiv:2607.18360v2 Announce Type: replace-cross Abstract: GPTZero found 53 NeurIPS 2025 accepted papers with hallucinated citations, and venues now screen submissions with automated reference checkers
arXiv:2610.18369v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have demonstrated promising capabilities for remote sensing reasoning, yet they frequently generate visually un
arXiv:2610.17948v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) have attracted increasing research attention due to their bidirectional attention and arbitrary order decoding.
arXiv:2610.15769v1 Announce Type: cross Abstract: Human demonstrations can capture task-relevant manipulation without using the target robot, but the recorded hand motions cannot directly serve as rob
arXiv:2610.15951v1 Announce Type: cross Abstract: Ransomware is a fast-escalating privacy threat causing significant financial and data losses worldwide. As attacks grow more sophisticated, traditiona
arXiv:2610.16261v1 Announce Type: cross Abstract: Mamba-based super-resolution models are efficient alternatives to Transformer-based restoration backbones, but their low-bit post-training quantizatio
arXiv:2610.15957v1 Announce Type: cross Abstract: Transformer models trained on symbolic music have become remarkably capable. However, it is yet unclear how they represent music structure, and whethe
Workplace artificial intelligence security startup Harmonic Security Inc. today announced it has raised 50 million in new funding to grow its platform for governing how employees use AI tools. The com
Duncan Riley / SiliconANGLE: Harmonic Security, which uses small language models to inspect employee interactions with AI tools, raised a 50M Series B, taking its total funding to 76M — Workplace arti
arXiv:2610.14224v1 Announce Type: cross Abstract: LLM agents' capabilities depend not only on their underlying models but also on their execution harnesses. Recursive self-improvement (RSI) offers a p
arXiv:2610.15431v1 Announce Type: new Abstract: Monocular depth estimation (MDE) has emerged as a cost-effective alternative to hardware-dependent 3D sensing modalities, yet predicting precise metric
arXiv:2610.15401v1 Announce Type: new Abstract: VLMs provide promising solutions to embodied reward design. Most current methods that train VLMs as reward regressors not only require extensive annotat
arXiv:2610.17370v1 Announce Type: new Abstract: Scientific discovery with language models requires finding the best valid solution within a finite computational budget. We study how feedback from this
I've been using ChatGPT Voice for years, particularly during my commute to work. Until recently, I've almost exclusively used Standard Voice Mode, but a recent issue has made it practically unusable.
arXiv:2610.17368v1 Announce Type: cross Abstract: Generative recommendation models have shown promising results by representing items as semantic IDs and generating these IDs autoregressively. We intr