research

arXiv:2507.17335v2 Announce Type: replace-cross Abstract: License plate recognition in open environments is widely applicable across various domains; however, the diversity of license plate types and

arXiv:2605.31419v1 Announce Type: new Abstract: We present a dense RGB-D SLAM system using differentiable triangles as the 3D map representation. While 3D Gaussian Splatting has emerged as the leading

arXiv:2603.22867v1 Announce Type: cross Abstract: Multimodal stacks that mix ViTs, CNNs, GNNs, and transformer NLP strain embedded platforms because their compute/memory patterns diverge and hard real

arXiv:2605.30532v1 Announce Type: cross Abstract: We study true self-avoiding walk (TSAW) as a mechanism for improving empirical integral estimation via Markov chain Monte Carlo (MCMC). We consider fi

Trump claims to have mastered the “Art of the Deal,” but he has just given us a master class in negotiating incompetence. I explain why the Iranians have the upper hand after his disastrous war of cho

arXiv:2603.26885v2 Announce Type: replace Abstract: Convolutional neural networks (CNNs) achieve state-of-the-art performance in medical image analysis yet remain opaque, limiting adoption in high-sta

arXiv:2605.30780v1 Announce Type: new Abstract: In this paper, we use asymmetric vibrations to demonstrate two degree-of-freedom (DoF) in-hand manipulation of grasped parts. The asymmetric vibrations

arXiv:2605.30376v1 Announce Type: cross Abstract: Modern time series architectures face a fundamental trade-off: channel-independent models scale well with increasing data volume but ignore critical i

arXiv:2502.04554v2 Announce Type: replace Abstract: Data selection has emerged as a crucial downstream application of data valuation, yet the theoretical foundations for using data values in selection

arXiv:2510.15710v3 Announce Type: replace Abstract: Medical workflows routinely combine reading images with producing visual and textual outputs, making both image understanding and generation central

arXiv:2605.30694v1 Announce Type: new Abstract: Many theories of decision making -- planning, reinforcement learning, causal intervention, online learning, and game-theoretic equilibrium -- turn local

arXiv:2605.30479v1 Announce Type: new Abstract: We consider the problem of universal transductive online classification with a possibly unbounded label space. This setting considers online learning, w

arXiv:2605.30825v1 Announce Type: cross Abstract: Unlearning in diffusion models aims to remove undesirable data or concepts while preserving the utility of pretrained models -- two fundamentally conf

arXiv:2506.01318v4 Announce Type: replace-cross Abstract: Machine unlearning (MU) aims to expunge a designated forget set from a trained model without costly retraining, yet the existing techniques ov

arXiv:2605.31378v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) still struggle with fine-grained translation quality estimation (QE), even with long reasoning chains. We argue that LRMs

arXiv:2605.30920v1 Announce Type: new Abstract: Diffusion-based neural solvers have shown strong promise for combinatorial optimization (CO), but existing methods typically rely on supervised training

arXiv:2605.30370v1 Announce Type: cross Abstract: From their inception in the 1950s, artificial neural networks (ANNs) started using the so-called point neuron model then prevalent in neuroscience, ho

arXiv:2510.09364v2 Announce Type: replace Abstract: 3D Gaussian splatting (3DGS) has demonstrated impressive performance in synthesizing high-fidelity novel views. Nonetheless, its effectiveness criti

arXiv:2602.03639v2 Announce Type: replace Abstract: Sampling-based controllers, such as Model Predictive Path Integral (MPPI) methods, offer substantial flexibility but often suffer from high variance

arXiv:2605.30968v1 Announce Type: cross Abstract: The core of vision-language models lies in measuring cross-modal similarity within a unified representation space. However, most image-text matching o

arXiv:2508.20478v2 Announce Type: replace Abstract: Long-form video understanding, characterized by long-range temporal dependencies and multiple events, remains a challenge. Existing methods often re

arXiv:2512.11561v2 Announce Type: replace Abstract: Generalizing pretrained models to unseen datasets without retraining is a central challenge toward foundation models. Achieving fully inductive infe

arXiv:2605.30561v1 Announce Type: cross Abstract: Vision Language Models (VLMs) enable a unified model to solve various vision tasks through prompting. They have shown promising performance in semanti

arXiv:2605.31466v1 Announce Type: new Abstract: Reconstructing the complete geometry of a scene from a single RGB image remains challenging - especially when inferring hidden structures where visual e

arXiv:2605.31346v1 Announce Type: cross Abstract: Zeroth-order (black-box) optimization is applied when gradients are unavailable and objective evaluations rely on expensive simulations. In many such

arXiv:2601.05770v3 Announce Type: replace-cross Abstract: Algorithm extraction aims to synthesize executable programs directly from models trained on algorithmic tasks, enabling de novo recovery of ex

arXiv:2602.10286v2 Announce Type: replace Abstract: Pairwise preference learning is central to machine learning, with recent applications in aligning language models with human preferences. A typical

arXiv:2605.31564v1 Announce Type: cross Abstract: We present the first systematic study of masked diffusion language models (MDLMs) for graph-to-text generation. We analyze MDLM generation trajectorie

arXiv:2603.09787v2 Announce Type: replace Abstract: Explainable artificial intelligence (XAI) aims to provide human-interpretable insights into the behavior of deep neural networks (DNNs), typically b

arXiv:2605.31504v1 Announce Type: new Abstract: Multimodal models in oncology can produce accurate predictions, but accurate prediction does not reveal whether the model has learned biology that is sh

arXiv:2601.20774v2 Announce Type: replace Abstract: Multitask learning and related frameworks have achieved tremendous success in modern applications. In multitask learning problem, we are given a set

arXiv:2605.31281v1 Announce Type: new Abstract: As wind turbine fleets age, data-driven reliability engineering is essential to optimise their operation and maintenance for service life extension and

arXiv:2605.30362v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) hold promise for demonstrating superior learning and representation capabilities in deep models. Given the tremendous s

arXiv:2605.30573v1 Announce Type: new Abstract: Sampling from high-dimensional, non-log-concave distributions with unnormalized densities remains a fundamental challenge in machine learning, particula

Yann LeCun comments on the 'Magnificent 7' tech companies (likely referring to the largest AI and tech stocks like Apple, Microsoft, Google, etc.), suggesting that one of these prominent companies doe

This has quietly been a miracle month in medicine. In the last 5 weeks we’ve got news on: - retatrutide, the triple agonist GLP-1 from Lilly, basically melting fat and body-wide inflammation at record

Trump’s “little excursion to Iran” is 'universally perceived as a defeat. Almost regardless of the outcome – most likely a return to the…status quo – the war looks ill-conceived, a monument to confuse

Reviews and discussions for all accepted papers at ICML are made public on OpenReview after the reviewing period concludes. Authors of rejected papers may also opt-in to have their reviews and discuss

Bill Gurley: Anthropic Thinks It’s Building God @Jason: It is the ultimate level of narcissism and delusion of grandeur to think you can create God. @bgurley: “Anthropic is a mystery to me. I've never

Exxon Says We’re Two Weeks From Petrol Armageddon Right. So it turns out closing the world’s most important oil chokepoint has consequences. Who knew. Exxon’s Senior VP Neil Chapman stood up at a Bern

I'm MAGA's twisted sense of reality and morality, a scientist who developed treatments and vaccines that have saved hundreds of thousands of lives (without getting rich from it) should be sent to Gitm

In my Harvard fellowship I study the views of AI accelerationists, safetyists and skeptics. What I have come to realize is that both the Accelerationists and the Safetyists believe that we are creatin

Francois Chollet's post likely expresses a philosophical perspective on existential risk or civilizational decline, suggesting that humanity's downfall would be precipitated by a loss of human values,

arXiv:2605.29416v1 Announce Type: cross Abstract: Vision-Language-Action models have achieved remarkable progress in robotic manipulation, yet they suffer from a critical limitation: a lack of 3D scen

arXiv:2602.03890v2 Announce Type: replace Abstract: Point clouds provide a compact and expressive representation of 3D objects, and have recently been integrated into multimodal large language models

arXiv:2506.20344v3 Announce Type: replace-cross Abstract: Despite its wide range of applications across various domains, the optimization foundations of deep matrix factorization (DMF) remain largely