Search: “papers”

arXiv:2606.06887v1 Announce Type: new Abstract: This paper introduces ARAPDiffusion, a latent diffusion model to learn the underlying continuous shape space of a deformation shape collection. The key

arXiv:2606.05967v2 Announce Type: replace-cross Abstract: In this paper, we study the finite-time behavior of the TD(0) temporal-difference method with linear function approximation (LFA). We consider

arXiv:2606.06786v1 Announce Type: new Abstract: This paper presents a forward-looking vision for integrating the emerging multi-modal multi-task federated foundation models (M3T FedFMs) into vehicular

arXiv:2606.06790v1 Announce Type: cross Abstract: This paper presents ERNEST, a four-wheeled planetary rover concept equipped with a two-degree-of-freedom Active Gimbal Suspension that combines yaw an

arXiv:2508.17821v3 Announce Type: replace-cross Abstract: This paper investigates the limitations of the normalization in attention mechanisms. We begin with a theoretical framework that enables the i

arXiv:2606.06838v1 Announce Type: cross Abstract: Automatic decompilers produce functionally correct but often unreadable C code. This paper addresses one stage of the reverse engineering workflow: im

arXiv:2606.06996v1 Announce Type: new Abstract: This paper studies runtime safety for autonomous driving when high-level driving commands become faulty or unreliable. Unlike conventional runtime-safet

arXiv:2411.09734v3 Announce Type: replace Abstract: In this paper, we propose a continuous-time formulation for the AdaGrad, RMSProp, and Adam optimization algorithms by modeling them as first-order i

arXiv:2606.07117v1 Announce Type: cross Abstract: This paper presents Native3D, the first end-to-end 3D scene generation framework that completely bypasses 2D intermediate representations. Traditional

arXiv:2606.07449v1 Announce Type: cross Abstract: This paper addresses orbital stabilization of a circular motion primitive for a dynamic extension of the Dubins car model within a transverse-lineariz

arXiv:2606.06686v1 Announce Type: new Abstract: This paper presents a simple framework that settles the complexity of Multi-Agent Path Finding (MAPF) on trees across standard objectives--distance, mak

arXiv:2606.07476v1 Announce Type: cross Abstract: This paper investigates multi-degrees of freedom (DoF) joint kinematics estimation under partially observed surface electromyography (sEMG), where onl

arXiv:2606.07404v1 Announce Type: new Abstract: This paper reports on training a hundred-billion-parameter sparse mixture of experts on a single eight-GPU node, end to end. LightningLM 0.1V is a recur

arXiv:2606.07436v1 Announce Type: new Abstract: This paper explores agentic 3D spatial understanding, i.e., MLLM agents performing 3D reasoning through tool use. Existing methods often misuse tools an

arXiv:2406.00636v2 Announce Type: replace Abstract: In this paper, we address the challenging problem of long-term 3D human motion generation. Specifically, we aim to generate a long sequence of smoot

arXiv:2507.01548v3 Announce Type: replace-cross Abstract: This paper explores how older migrants in urban China can record stories that everyday language and design often miss. We ran two co-creation

arXiv:2606.06854v1 Announce Type: new Abstract: This paper uses geometry to explain how a machine learning model can be stolen using an already existing well-known method. The author has shown the exa

tl;dr: we aren’t close to RSI, regardless of the hints IPO-bound Anthropic tried to drop last week. This paper tests whether today’s AI agents can build better AI agents without human design help. i.e

arXiv:2603.21510v3 Announce Type: replace-cross Abstract: This paper addresses the fusion of a pair of spatially unregistered hyperspectral image (HSI) and multispectral image (MSI) covering roughly o

arXiv:2606.06893v1 Announce Type: new Abstract: Large language model agents increasingly rely on Skills to encode procedural knowledge, yet high-quality Skills remain costly to hand-write. This paper

Refreshing What happens when AIs become smarter than us? Why would they keep humans around if given the choice? Our new paper argues that only trying to control AIs is a limited strategy, and that a s

arXiv:2503.01734v3 Announce Type: replace-cross Abstract: Attacks on machine learning models have been extensively studied through stateless optimization. In this paper, we demonstrate how a reinforce

https://x.com/hendrycks/status/2052422910133104670?s=20 What happens when AIs become smarter than us? Why would they keep humans around if given the choice? Our new paper argues that only trying to co

arXiv:2606.05770v1 Announce Type: cross Abstract: AI is changing how software engineers work, but it often comes with hidden burdens and costs. In this paper, we characterize two such often-overlooked

arXiv:2606.06303v1 Announce Type: cross Abstract: Controllable generation with discrete diffusion models is often hindered by high computational overhead or the need for retraining. In this paper, we

arXiv:2606.05167v1 Announce Type: cross Abstract: Realism is a central yet seemingly under-theorized concept in Agent-Based Modelling. This paper presents a Systematic Literature Review, aiming to ide

arXiv:2606.06486v1 Announce Type: cross Abstract: In this paper, we study regret minimization in repeated games with adaptive opponents who can respond based on histories of play. The standard metric

Take that, @geoffreyhinton. “If LLMS have human-like attributes, then so does Age of Empires II”. Also, score another point for @Pontifex! This is an insane paper and I love it https://arxiv.org/abs/2

arXiv:2606.06061v1 Announce Type: new Abstract: This paper presents a distributed conversational framework for human-robot collaborative manipulation that integrates local language and vision-language

This post from Swyx discusses the high volume of CFP (Call for Papers) submissions received, exceeding 2000 responses compared to previous years, and apologizes for delays in responding to submitters

Check out the NVIDIA blog! This week at #CVPR2026, NVIDIA Research is presenting three papers across physical ai that offer groundbreaking solutions for training at scale across diverse applications:

arXiv:2606.05494v1 Announce Type: new Abstract: Automatic text summarization has become increasingly important due to the rapid growth of digital textual information. This paper presents a Multi-Model

arXiv:2606.05359v1 Announce Type: new Abstract: In this paper, we propose RePHO, a method to reconstruct physically plausible human-object interactions (HOI) from monocular videos. While existing kine

arXiv:2606.05848v1 Announce Type: new Abstract: In this paper, we present a robotic ultrasound acquisition system that integrates stereo vision, touch-based feedback, and expert-informed strategies to

arXiv:2606.04828v1 Announce Type: new Abstract: This paper presents a French corpus annotated for multiword expressions (MWEs) with adverbial function. This corpus is designed for investigation on inf

arXiv:2508.14623v2 Announce Type: replace-cross Abstract: This paper examines the implications of using the Scale-Invariant Signal-to-Distortion Ratio (SI-SDR) as both evaluation and training objectiv

arXiv:2606.04518v1 Announce Type: new Abstract: This paper proposes a cooperative target circumnavigation framework for multiple unmanned surface vehicles (USVs) operating without external localizatio

arXiv:2606.04670v1 Announce Type: cross Abstract: This paper presents a method of multivariate scattered data interpolation and approximation that produces optimal Lipschitz-continuous approximation,

arXiv:2606.04345v1 Announce Type: cross Abstract: This paper presents HYolo, an intelligent IoT-based object detection framework that integrates hypergraph learning into the YOLO architecture. Traditi

arXiv:2606.05045v1 Announce Type: cross Abstract: We present in this paper a framework for the identification of control-affine reduced-order models (ROMs). The proposed method utilizes autoencoders (

arXiv:2601.21868v2 Announce Type: replace-cross Abstract: Understanding the stability and long-time behavior of generative models is a fundamental problem in modern machine learning. This paper provid

arXiv:2606.04871v1 Announce Type: new Abstract: The selection of an appropriate 3D representation is a fundamental design decision that dictates the efficiency, quality, and capabilities of modern com

See also: https://x.com/emollick/status/1799046218917822682?s=20 Alignment, of a sort: this paper conducts what they call a “moral Turing Test,” asking people to compare GPT-4o to humans on ethical qu

arXiv:2606.04157v1 Announce Type: new Abstract: Haptic guidance in teleoperation enhances operator performance through force feedback. This paper presents guidelines to select the most appropriate mod

arXiv:2603.02697v2 Announce Type: replace-cross Abstract: This paper presents ShareVerse, a video generation framework enabling multi-agent shared world modeling, addressing the gap in existing works

arXiv:2606.04073v1 Announce Type: cross Abstract: This paper proposes a two-stage pseudo anomaly-guided anomaly detection method (extbf{T}wo-stage extbf{P}seudo extbf{A}nomaly-guided extbf{A}nomaly ex