Search: “models”

arXiv:2605.18916v1 Announce Type: cross Abstract: We investigate Counterfactual Video Foley Generation, which aims to adopt a sound-source identity that contradicts the visual evidence while remaining

arXiv:2605.19887v1 Announce Type: cross Abstract: Current Physical AI (PAI) relies heavily on closed-loop visual-servoing pipelines, whose perception and planning stages may become computationally int

deepagents v0.6 ships w/ support for code interpreters! these are the perfect happy medium between pure tool execution and heavyweight sandboxes they give your agent an environment where it can... → k

arXiv:2605.19294v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies are typically deployed with asynchronous inference: the robot executes a previously predicted action chunk while

arXiv:2605.19557v1 Announce Type: cross Abstract: We study post-hoc Learning to Defer (L2D) through the lens of ideal distributions: divergence-regularized reweightings of the data distribution under

arXiv:2506.12218v2 Announce Type: replace-cross Abstract: Directed acyclic graphs (DAGs) are central to science and engineering applications including causal inference, scheduling, and neural architec

arXiv:2605.18881v1 Announce Type: new Abstract: In dynamic flow fields, various animals exhibit remarkable odor search capabilities despite relying on stochastic detections. Interestingly, there exist

arXiv:2605.19842v1 Announce Type: new Abstract: We propose a scalable tensorization framework for neural network compression based on slice-wise feature distillation. Unlike conventional tensor decomp

arXiv:2605.19279v1 Announce Type: new Abstract: Visual image reconstruction from functional Magnetic Resonance Imaging (fMRI) is a fundamental task in brain decoding, providing a crucial pathway for u

arXiv:2601.18993v2 Announce Type: replace-cross Abstract: Camera redirection aims to replay a dynamic scene from a single monocular video under a user-specified camera trajectory. However, large-angle

arXiv:2511.16062v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) excel on homophilous graphs but often fail under heterophily due to self-reinforcing and phase-inconsistent signals. We

arXiv:2605.19050v1 Announce Type: new Abstract: Generating stable molecular conformations typically forces a tradeoff between the physical realism of energy-based relaxation and the sampling efficienc

arXiv:2605.19889v1 Announce Type: cross Abstract: 3D Lookup Tables (3D LUTs) are widely used for color mapping, but their grid-based representation requires discretizing the RGB space, leading to a ca

arXiv:2605.20138v1 Announce Type: new Abstract: This article presents a Hamilton--Jacobi (HJ) reachability framework for a two--satellite collision avoidance problem operating in the same circular orb

arXiv:2605.19902v1 Announce Type: new Abstract: Predicting protein-ligand binding affinity remains intractable for multi-domain proteins, where inter-domain dynamics govern molecular recognition. Exis

arXiv:2605.18932v1 Announce Type: cross Abstract: In this work, we propose HypergraphFormer, a novel and efficient approach to floor plan generation based on learning hypergraph representations with a

arXiv:2605.20159v1 Announce Type: new Abstract: Non-destructive testing of aerospace SiC/SiC composites via X-ray computed tomography (XCT) relies on expert visual assessment, with current workflows o

Lambda Labs announced a partnership with Hudson River Trading (HRT), a quantitative trading firm, to provide computational infrastructure and GPU resources for HRT's quantitative research and developm

arXiv:2605.19113v1 Announce Type: cross Abstract: Many clinical risk scores are deployed as additive rules with nonnegative integer points assigned to relevant binary predictive features. These intege

arXiv:2605.18846v1 Announce Type: cross Abstract: Classical communication systems fail not only through random noise but also when transmitter and receiver use incompatible operational codebooks. Vari

This guide provides instructions for setting up local AI capabilities on a 2019 Mac Pro running Ubuntu 24.04, covering the installation and configuration of ROCm 7.2.3 GPU drivers, PyTorch 2.10 for ma

arXiv:2605.19594v1 Announce Type: new Abstract: Navigating to instance-level targets in complex environments is a challenging problem. Many existing zero-shot methods achieve strong performance by mod

arXiv:2403.07183v4 Announce Type: replace-cross Abstract: We present an approach for estimating the fraction of text in a large corpus which is likely to be substantially modified or produced by a lar

arXiv:2605.18823v1 Announce Type: new Abstract: Digital twins (DTs) for urban transportation systems have gained increasing attention; however, their systematic evaluation in safety-critical scenarios

arXiv:2605.20098v1 Announce Type: new Abstract: Claim verification is an important problem in high-stakes settings, including health and finance. When information underpinning claims is incomplete or

arXiv:2605.19584v1 Announce Type: new Abstract: We study an online market-making problem in which a learner sequentially posts bid and ask prices for a single asset while interacting with traders hold

arXiv:2605.20105v1 Announce Type: new Abstract: Learning to generalise from limited data is a fundamental challenge for both artificial and biological systems. A common strategy is to extract reusable

arXiv:2605.19032v1 Announce Type: new Abstract: Photos of faces uploaded online are vulnerable to malicious actors who can scrape facial images from online sources and intrude on personal privacy via

arXiv:2605.20185v1 Announce Type: cross Abstract: Existing Gaussian avatar methods typically parameterize geometry on a body-template surface, which entangles the avatar's representation space with th

arXiv:2605.19782v1 Announce Type: new Abstract: LLM discovery and optimization systems are increasingly applied across domains, implementing a common propose-evaluate-revise loop. Such optimization or

arXiv:2605.18864v1 Announce Type: cross Abstract: Recent studies observe that reinforcement learning with verifiable rewards (RLVR) reliably improves pass@1 on reasoning tasks, yet often fails to yiel

arXiv:2605.19378v1 Announce Type: new Abstract: This paper systematically diagnoses the training failure modes of Token-Choice sparse Mixture-of-Experts (MoE) on video Diffusion Transformers. Starting

arXiv:2605.19856v1 Announce Type: cross Abstract: Training very deep neural networks requires controlling the propagation of magnitudes across depth. Without such control, activations and gradients ma

arXiv:2605.20087v1 Announce Type: cross Abstract: Conversational AI has now reached billions of users, yet existing datasets capture only what people say, not what they think. We introduce ThoughtTrac

arXiv:2605.18831v1 Announce Type: cross Abstract: Cold-chain storage limits access to insulin for hundreds of millions of people; a thermally protective patch polymer could help, but the design space

arXiv:2605.20134v1 Announce Type: new Abstract: Learning generalizable trajectory representations from raw GPS traces remains difficult because the data is continuous, noisy, and irregularly sampled.

arXiv:2511.07347v2 Announce Type: replace-cross Abstract: Neural operators have emerged as powerful tools for learning solution operators of partial differential equations (PDEs). However, standard sp

arXiv:2605.19613v1 Announce Type: new Abstract: Color constancy aims to keep object colors consistent under varying illumination. Cross-camera generalization in color constancy remains challenging bec

arXiv:2605.17564v1 Announce Type: new Abstract: Paired RGB-thermal data has shown significant utility across a range of applications, including image fusion, object tracking, and anomaly detection; ho

arXiv:2605.16326v1 Announce Type: cross Abstract: Chronic neck pain is a leading cause of disability worldwide, and current treatment selection remains largely trial and error. We present a machine le

arXiv:2507.09148v2 Announce Type: replace-cross Abstract: Sparse Principal Component Analysis (SPCA) is a fundamental technique for dimensionality reduction, and is NP-hard. In this paper, we introduc

arXiv:2605.16654v1 Announce Type: cross Abstract: Manner and result verbs encode different aspects of event structure and have been discussed in developmental work as a potentially informative distinc

arXiv:2605.16993v1 Announce Type: cross Abstract: Current clinical artificial intelligence (AI) systems are evaluated almost exclusively on clean, standardised, English-language inputs, conditions tha

arXiv:2602.20042v2 Announce Type: replace Abstract: General Alignment has improved average-case helpfulness and safety, but current alignment practice still rewards confident, single-turn responses. T

arXiv:2405.14657v2 Announce Type: replace Abstract: Preferential Bayesian optimization (PBO) learns latent utilities from pairwise comparisons, but most existing methods assume homoscedastic compariso

arXiv:2605.16309v1 Announce Type: new Abstract: LLM-based agents can recover from individual execution errors, yet they repeatedly fail on the same fault when the underlying process knowledge--operato