Knowledge catalogue
arXiv:2605.17678v1 Announce Type: cross Abstract: In this paper, we derive rates of convergence in the high-dimensional central limit theorem for Polyak--Ruppert averaged iterates generated by entropy
arXiv:2605.18262v1 Announce Type: new Abstract: Accurate pedestrian trajectory prediction is crucial for autonomous systems operating in complex environments, such as modular buses and delivery robots
arXiv:2601.23154v2 Announce Type: replace-cross Abstract: Pain management in intensive care usually involves complex trade-offs, since both inadequate and excessive treatment can compromise patient sa
arXiv:2605.18370v1 Announce Type: cross Abstract: We study sample quantiles of distributions indexed by estimated parameters, with a on Value-at-Risk related to linear projections of financial returns
arXiv:2512.12572v2 Announce Type: replace Abstract: Data attribution aims to explain model predictions by estimating how they would change if certain training points were removed, and is used in a wid
arXiv:2601.21531v2 Announce Type: replace-cross Abstract: Visual token compression is widely used to accelerate large vision-language models (LVLMs) by pruning or merging visual tokens, yet its advers
arXiv:2602.16712v2 Announce Type: replace Abstract: Dexterous manipulation policies today largely assume fixed hand designs, severely restricting their generalization to new embodiments with varied ki
arXiv:2605.17907v1 Announce Type: cross Abstract: By sharing intermediate features, collaborative perception extends each agent's sensing beyond standalone limits, but real-world feature modality hete
arXiv:2605.17811v1 Announce Type: cross Abstract: Can a shared-weight recurrent Transformer develop distinct internal roles without being partitioned into separate modules? We study this in Asymmetric
One of the loudest applauses in the entire Google keynote: Nishtha put on the new Gentle Monster + Gemini glasses, tapped the side to summon Gemini, and ALL in one prompt said “take a photo and put a
'One thing that we've been seeing recently is that inference benchmarks don't really match production workloads that well.' - @realDanFu, VP of Kernels When you're running dozens of concurrent coding
One trend that I think you might start to see at big companies is insourcing via hiring: why pay so many outside vendors (legal, marketing, software vendors) when you can hire in-house and harness AI
arXiv:2602.20706v2 Announce Type: replace Abstract: This paper introduces online algorithms with unreliable guidance (OAG), a model for ML-augmented online decision-making that cleanly separates the p
arXiv:2605.17705v1 Announce Type: cross Abstract: Panel data, in which multiple units are repeatedly observed over time, arise throughout science and engineering. Quantifying predictive uncertainty in
arXiv:2603.03538v3 Announce Type: replace Abstract: Large Language Models (LLMs) with chain-of-thought generation have demonstrated great potential for solving complex reasoning and planning tasks. Ho
arXiv:2306.12282v2 Announce Type: replace-cross Abstract: Decision-makers often have access to machine-learned predictions about future demand that can help guide online resource allocation decisions.
arXiv:2512.04331v2 Announce Type: replace Abstract: The surge in face forgeries has increasingly undermined confidence in the authenticity of online content. As generation algorithms rapidly evolve, n
open sourcing Marlin-2B 🐟 a tiny VLM to extract structured information from videos Marlin is finetuned for two questions devs want to ask in their videos: what is happening, and when? Best open model
OpenAI: OpenAI introduces Guaranteed Capacity, a new offering that lets customers guarantee access to OpenAI's compute through one- to three-year commitments — Guarantee long-term access to OpenAI com
New York Times: OpenAI's win against Elon Musk leaves it free to continue its IPO plans, but it still faces many issues, like rising competition and dozens of other lawsuits — A jury's rejection of El
arXiv:2605.06088v2 Announce Type: replace Abstract: Understanding open-vocabulary 3D scenes with Gaussian-based representations remains challenging due to fragmented and spatially inconsistent semanti
arXiv:2605.17172v1 Announce Type: cross Abstract: Personal AI stacks, like OpenClaw and Hermes Agent, are becoming central to daily work, yet they route nearly every query (often over sensitive local
arXiv:2508.16438v4 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) and dense retrievers have driven significant progress in retrieval-augmented generation (RAG).
arXiv:2605.17283v1 Announce Type: cross Abstract: Recent progress in formal theorem proving has benefited from large-scale proof generation and verifier-aware training, but agentic proving is rarely i
arXiv:2307.12405v2 Announce Type: replace Abstract: We propose a machine learning approach to the optimal control of multiclass fluid queueing networks (MFQNETs) that provides explicit and insightful
arXiv:2605.17800v1 Announce Type: cross Abstract: Rearranging densely packed tabletop objects is challenging when parallel-gripper picks are infeasible without sufficient clearance around an object. T
arXiv:2605.18349v1 Announce Type: cross Abstract: Occupancy estimation and crowd counting are critical tasks in designing smart and efficient public transport vehicles. Given that public transport loa
arXiv:2605.17197v1 Announce Type: cross Abstract: Post-disaster damage assessment requires rapid and accurate semantic segmentation of 3D point clouds to identify critical infrastructure such as damag
arXiv:2605.16363v1 Announce Type: new Abstract: Smartphone scams are increasingly prevalent and typically manifest as multi-stage, cross-application processes with gradually emerging intent. Effective
arXiv:2605.16395v1 Announce Type: cross Abstract: We present OrbiSim, a novel robotic simulation paradigm that redefines world models as a fully differentiable physics engine for embodied intelligence
arXiv:2509.02351v3 Announce Type: replace-cross Abstract: Labeled data is a fundamental component in training supervised deep learning models for computer vision tasks. However, the labeling process,
arXiv:2601.01155v3 Announce Type: replace Abstract: Existing methods for multi-agent navigation typically assume fully known environments, offering limited support for partially known scenarios with o
arXiv:2605.16341v1 Announce Type: new Abstract: Low-rank gradient compression reduces communication in distributed training by representing updates with rank-r factors. Dion is a recent method that ap
arXiv:2605.16421v1 Announce Type: cross Abstract: We present a new algorithm for deciding formula entailment in orthologic (a sound approximation of classical logic) that avoids the costly preprocessi
arXiv:2605.17757v1 Announce Type: cross Abstract: INT2 KV-cache quantization is attractive for long-context LLM serving, but it remains difficult to make both accurate and deployable. Simple rotations
arXiv:2506.16042v2 Announce Type: replace Abstract: Generative AI is being leveraged to solve a variety of computer-use tasks involving desktop applications. State-of-the-art systems have focused sole
🚨Our paper is out in PNAS: we found classic human persuasion techniques worked on AIs in a 'parahuman' way, making them agree to objectionable requests (upping compliance from 35% to 51%) It worked on
arXiv:2605.16391v1 Announce Type: cross Abstract: Inertial measurement units (IMUs) are fundamental sensing components in multi-source integrated navigation systems, and their performance directly det
arXiv:2605.18583v1 Announce Type: cross Abstract: Coding agents now run autonomously with shell, file, and network privileges. When a user issues a benign request, the agent sometimes does more than a
arXiv:2603.14371v2 Announce Type: replace-cross Abstract: Embodied AI agents increasingly require parallel execution of multiple tasks, such as manipulation, conversation, and memory construction, fro
arXiv:2605.16925v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has recently emerged as a powerful explicit representation enabling fast, high-fidelity rendering, making it a promising fo
arXiv:2605.18587v1 Announce Type: cross Abstract: Single-cell trajectory inference from destructive time-course snapshots is fundamentally ill-posed: neither cross-time cell correspondences nor contin
arXiv:2605.17877v1 Announce Type: new Abstract: A significant hurdle for current LLMs is the execution of complex, multi-stage tasks. Group Relative Policy Optimization (GRPO) has been emerging as a l
arXiv:2605.18191v1 Announce Type: new Abstract: Current reinforcement learning(RL) methods are broadly applicable and powerful in verifiable settings where scalar rewards can be provided. However, in
arXiv:2605.16881v1 Announce Type: new Abstract: Digital humanities projects increasingly rely on machine translation and large language models to widen access to classical, religious, and otherwise un
arXiv:2605.17916v1 Announce Type: new Abstract: Generating a consistent whole-house VR tour from a floorplan and style reference requires both photorealistic panoramas and cross-view spatial coherence
arXiv:2605.17028v1 Announce Type: cross Abstract: Large language models (LLMs) hallucinate with confidence: their outputs can be fluent, authoritative, and simply wrong. In medical, legal, and scienti
arXiv:2605.17108v1 Announce Type: new Abstract: Transformers have become the dominant architecture for sequence modeling by using self-attention to enable expressive and highly parallel processing. Ho
arXiv:2601.09495v3 Announce Type: replace Abstract: With the emergence of massively parallel processing units, parallelization has become a desirable property for new sequence models. The ability to p
arXiv:2602.18227v2 Announce Type: replace Abstract: Accurate AC power flow (AC-PF) prediction under domain shift is critical when models trained on medium-voltage (MV) grids are deployed on high-volta
arXiv:2605.18080v1 Announce Type: cross Abstract: We present a novel parameterized 4-qubit Eisert-Wilkens-Lewenstein (EWL) quantum game circuit for recommender systems in quadruple helix innovation ec
arXiv:2509.22849v2 Announce Type: replace-cross Abstract: Neural networks with ReLU activations are a widely used model in machine learning. It is thus important to have a profound understanding of th
arXiv:2605.17860v1 Announce Type: cross Abstract: While modern Automatic Speech Recognition (ASR) systems achieve high accuracy on benchmark corpora, their performance often degrades when there is rea
arXiv:2511.18801v3 Announce Type: replace Abstract: Existing autoregressive (AR) methods for generating artist-designed meshes struggle to balance global structural consistency with high-fidelity loca
arXiv:2605.18038v1 Announce Type: new Abstract: Salmon re-identification in commercial net-pens is challenging due to large populations, which impose strict accuracy requirements and make large-scale
arXiv:2605.17719v1 Announce Type: new Abstract: CNN- and Transformer-based architectures have achieved strong performance in medical image segmentation, but CNNs are limited in modeling long-range dep
arXiv:2605.16266v1 Announce Type: cross Abstract: We introduce Patchwork, a new general-purpose shape representation capable of modeling 2D and 3D geometry with a small number of parameters. Patchwork
arXiv:2503.20981v2 Announce Type: replace-cross Abstract: Investigating the public experience of urgent care facilities is essential for promoting community healthcare development. Traditional survey
arXiv:2605.16452v1 Announce Type: cross Abstract: Accurate peak detection across diverse cardiac physiological signals, including the Electrocardiogram (ECG), Photoplethysmogram (PPG), Ballistocardiog
arXiv:2605.16858v1 Announce Type: cross Abstract: Autonomous Vehicles (AVs) must make reliable decisions in dense urban environments where pedestrian behavior is variable, sometimes abnormal, and ofte