research

arXiv:2604.11637v1 Announce Type: new Abstract: 4D point cloud videos capture rich spatial and temporal dynamics of scenes which possess unique values in various 4D understanding tasks. However, most

arXiv:2506.18831v2 Announce Type: replace Abstract: Large Language Models employing extended chain-of-thought (CoT) reasoning often suffer from the overthinking phenomenon, generating excessive and re

arXiv:2601.12038v3 Announce Type: replace Abstract: Dung's abstract argumentation frameworks model acceptability solely in terms of an attack relation, thereby conflating two conceptually distinct asp

arXiv:2603.21942v2 Announce Type: replace-cross Abstract: We introduce Suiren-1.0, a family of molecular foundation models for the accurate modeling of diverse organic systems. Suiren-1.0 comprising t

arXiv:2604.10000v1 Announce Type: new Abstract: Precise medical image segmentation is fundamental for enabling computer aided diagnosis and effective treatment planning. Traditional models that rely s

arXiv:2604.11797v1 Announce Type: new Abstract: We present SyncFix, a framework that enforces cross-view consistency during the diffusion-based refinement of reconstructed scenes. SyncFix formulates r

arXiv:2511.06101v3 Announce Type: replace-cross Abstract: Web agents struggle to adapt to new websites due to the scarcity of environment specific tasks and demonstrations. Recent works have explored

arXiv:2603.01420v2 Announce Type: replace Abstract: This work presents a finite element-guied physics-informed learning framework for multiphysics problems with coupled partial differential equations

arXiv:2509.04123v2 Announce Type: replace Abstract: Text-to-story visualization is challenging due to the need for consistent interaction among multiple characters across frames. Existing methods stru

arXiv:2604.10912v1 Announce Type: new Abstract: Medical image segmentation remains challenging due to limited fine-grained annotations, complex anatomical structures, and image degradation from noise,

arXiv:2604.10582v1 Announce Type: new Abstract: Tracking-Any-Point (TAP) models aim to track any point through a video which is a crucial task in AR/XR and robotics applications. The recently introduc

arXiv:2504.04099v2 Announce Type: replace-cross Abstract: Large Vision-Language Models have demonstrated remarkable capabilities, yet they suffer from hallucinations that limit practical deployment. W

arXiv:2604.10895v1 Announce Type: cross Abstract: For a robot to be called socially intelligent, it must be able to infer users internal states from their current behaviour, predict the users future b

arXiv:2501.06786v2 Announce Type: replace Abstract: With the rapid growth of dynamic vision sensor (DVS) data, constructing a low-energy, efficient data retrieval system has become an urgent task. Has

arXiv:2603.28287v2 Announce Type: replace Abstract: Despite the growing need for data of more and more sophisticated 3D reconstruction pipelines, we can still observe a scarcity of suitable public dat

arXiv:2604.11025v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) have begun to support Thinking with Images by invoking visual tools such as zooming and cropping during

arXiv:2604.09560v1 Announce Type: new Abstract: Transformers, diffusion-maps, and magnetic Laplacians are usually treated as separate tools; we show they are all different regimes of a single Markov g

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Want to understand the current state of AI? Check out these ch

arXiv:2604.09614v1 Announce Type: new Abstract: This paper develops a measure-theoretic framework establishing when and how a possibilistic representation of incomplete knowledge contracts into a prob

The greatest triumph of the incessant hurricane of lies coming from Russia, MAGA, and the likes of Elon Musk has been convincing a significant share of the world, including Europeans, to believe in a

arXiv:2604.09780v1 Announce Type: new Abstract: Mixture of Experts (MoEs) are now ubiquitous in large language models, yet the mechanisms behind their 'expert specialization' remain poorly understood.

arXiv:2411.06376v3 Announce Type: replace-cross Abstract: Peripheral Component Interconnect Express (PCIe) is the de facto interconnect standard for high-speed peripherals and CPUs. The development of

You’ve probably heard some version of this idea before: that many of us have an “inner Neanderthal.” That is to say, around 45,000 years ago, when Homo sapiens first arrived in Europe, they met member

Francois Chollet argues that memorization and knowledge function as a cache for previously completed cognitive work, allowing it to be reused efficiently rather than recomputed. The purpose of storing

arXiv:1810.07793v2 Announce Type: replace Abstract: We introduce the Wasserstein Transform (WT), a general unsupervised framework for updating distance structures on given data sets with the purpose o

arXiv:2602.16309v2 Announce Type: replace-cross Abstract: Fault injection attacks on embedded neural network models have been shown as a potent threat. Numerous works studied resilience of models from

This appears to be a brief, informal reply post on X (formerly Twitter) directed at user @themaxburns, made in response to a conversation involving Yann LeCun, a prominent AI researcher and Chief AI S

arXiv:2604.11435v1 Announce Type: cross Abstract: Character description generation is an important capability for narrative-focused applications such as summarization, story analysis, and character-dr

arXiv:2512.15992v2 Announce Type: replace-cross Abstract: We develop a quantitative approximation theory for shallow neural networks using tools from time-frequency analysis. Working in weighted modul

arXiv:2505.11737v4 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) have demonstrated impressive capabilities, their output quality remains inconsistent across various applica

arXiv:2604.10553v1 Announce Type: new Abstract: Graph neural networks have demonstrated excellent applicability to a wide range of domains, including social networks, biological systems, recommendatio

arXiv:2604.10460v1 Announce Type: cross Abstract: The rapid growth of generative AI has introduced new challenges in content moderation and digital forensics. In particular, benign AI-generated images

arXiv:2604.10530v1 Announce Type: cross Abstract: How software developers interact with Artificial Intelligence (AI)-powered tools, including Large Language Models (LLMs), plays a vital role in how th

arXiv:2604.10969v1 Announce Type: cross Abstract: To ensure energy efficiency and reliable operations, it is essential to monitor solar panels in generation plants to detect defects. It is quite labor

arXiv:2604.11679v1 Announce Type: new Abstract: Clinical deployment of automated brain MRI analysis faces a fundamental challenge: clinical data is heterogeneous and noisy, and high-quality labels are

arXiv:2603.27960v2 Announce Type: replace-cross Abstract: Although Large Vision Language Models (LVLMs) have demonstrated impressive multimodal reasoning capabilities, their scalability and deployment

arXiv:2604.10458v1 Announce Type: cross Abstract: Wearable IMU-based Human Activity Recognition (HAR) relies heavily on Deep Neural Networks (DNNs), which are burdened by immense computational and buf

arXiv:2604.11077v1 Announce Type: new Abstract: Customer service chatbots are increasingly expected to serve not merely as reactive support tools for users, but as strategic interfaces for harvesting

arXiv:2604.11006v1 Announce Type: new Abstract: 3D texture generation is receiving increasing attention, as it enables the creation of realistic and aesthetic texture materials for untextured 3D meshe

arXiv:2506.05014v2 Announce Type: replace-cross Abstract: We propose a novel, flexible, and efficient framework for designing Concept Bottleneck Models (CBMs) that enables practitioners to explicitly

arXiv:2604.09648v1 Announce Type: new Abstract: Quantifying exhaled CO2 from free-roaming cattle is both a direct indicator of rumen metabolic state and a prerequisite for farm-scale carbon accounting

arXiv:2604.09716v1 Announce Type: cross Abstract: Deep visual recognition models are usually trained and evaluated using metrics such as loss and accuracy. While these measures show whether a model is

arXiv:2604.11564v1 Announce Type: new Abstract: Single-image super-resolution has progressed from deep convolutional baselines to stronger Transformer and state-space architectures, yet the correspond

arXiv:2405.09866v2 Announce Type: replace-cross Abstract: In recent years, novel communication strategies have emerged to face the challenges that the increased number of connected devices and the hig

arXiv:2604.11288v1 Announce Type: new Abstract: At K=16 tokens (0.4% of a 4K context), every existing KV-cache compression method achieves 0% on credential retrieval. The failure mode is dormant token

arXiv:2602.11623v2 Announce Type: replace Abstract: We revisit the use of probabilistic values, which include the well-known Shapley and Banzhaf values, to rank features for explaining the local predi