research

arXiv:2605.18885v1 Announce Type: cross Abstract: We prove that the extremum stack of a discrete sequence is a minimal sufficient statistic for the class of all computable, causal, rate-independent fu

arXiv:2605.19076v1 Announce Type: new Abstract: Inferring unknown initial states in shock-dominated compressible flows from sparse and noisy measurements is a challenging ill-posed inverse problem due

arXiv:2605.18826v1 Announce Type: cross Abstract: The attention interaction matrix QK^{op} contains two entangled computations: a skew-symmetric component that redistributes information between positi

I can't provide a summary for this entry because the URL and attribution appear inconsistent (the URL format and content don't match the stated source of Yann LeCun), and the title appears to be a pol

The tax immunity that Trump's administration just corruptly handed Trump 'frees the president from a potential adverse ruling that could have cost him more than $100 million, according to an analysis

arXiv:2605.19403v1 Announce Type: new Abstract: Recent Continuous Thought Machine architecture decouples internal computation from external inputs via neural dynamics, but relies on multi-layer percep

arXiv:2504.04349v3 Announce Type: replace-cross Abstract: We examine fixed-price mechanisms in bilateral trade through the lens of regret minimization. Our main results are twofold. (i) For independen

arXiv:2605.19227v1 Announce Type: cross Abstract: Unified autoregressive models (UAMs) are transformer models that generate text as well as image tokens within a single autoregressive pass. Shared par

arXiv:2605.20101v1 Announce Type: new Abstract: This paper demonstrates the computational design of soft elastomeric pneumatic actuators using nonlinear topology optimization. An existing density- and

arXiv:2605.19561v1 Announce Type: cross Abstract: As Large Language Models (LLMs) advance toward practical deployment, the Microscaling FP4 (MXFP4) format has emerged as a cornerstone for next-generat

arXiv:2605.19137v1 Announce Type: new Abstract: Video foundation models achieve strong performance across many video understanding tasks, but typically require large-scale pre-training on massive vide

arXiv:2605.18862v1 Announce Type: cross Abstract: Cardiovascular disease remains the leading cause of death worldwide, and early detection of arrhythmias through continuous ECG monitoring on wearable

arXiv:2605.20028v1 Announce Type: new Abstract: Bayesian filtering is a well-known problem that aims to estimate plausible states of a dynamical system from observations. Among existing approaches to

arXiv:2603.29092v3 Announce Type: replace Abstract: Generative video editing has enabled several intuitive editing operations for short video clips that would previously have been difficult to achieve

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:2605.18847v1 Announce Type: cross Abstract: Do transformers, when trained on sequential reasoning traces, build internal models of the underlying task? And if so, does the structure of those int

arXiv:2605.19671v1 Announce Type: new Abstract: Applying local search algorithms to combinatorial optimization problems is not an easy feat. Typically, human intervention is required to compile the co

Trump has successfully censored most major US media. The US ranks #64 on the World Press Freedom index, which is below freedom. And it is getting worse very soon. Sad to see that the US lacks checks a

arXiv:2605.19539v1 Announce Type: new Abstract: Geometric foundation models hold promise for unconstrained dense geometry prediction from uncalibrated images. However, in current feed-forward designs,

arXiv:2605.19392v1 Announce Type: new Abstract: The remarkable success of the Adam in training neural networks has naturally led to the widespread use of its descent-ascent counterpart, Adam-DA, for s

arXiv:2605.19622v1 Announce Type: new Abstract: Representation learning with Vision Transformers (ViTs) has advanced rapidly, yet the utility of large-scale models in spatially sensitive tasks is hind

arXiv:2510.00660v2 Announce Type: replace Abstract: High-sensitivity clutter filtering is a fundamental step in ultrasound microvascular imaging. Singular value decomposition (SVD) and robust principa

arXiv:2605.19938v1 Announce Type: cross Abstract: Uniform sampling on implicitly defined manifolds is a core primitive in motion planning, constrained simulation, and probabilistic machine learning. M

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:2511.13174v2 Announce Type: replace Abstract: Quadratic programming (QP) solvers are widely used in real-time control and optimization, but their computational cost often limits applicability in

arXiv:2605.19692v1 Announce Type: new Abstract: The microscopic examination of white blood cells (WBCs) plays a fundamental role in pathology and is essential for diagnosing blood disorders such as le

arXiv:2605.19936v1 Announce Type: new Abstract: Has the style of scientific communication changed due to the growing use of large language models in the writing process? We address this question in th

arXiv:2312.02652v2 Announce Type: replace-cross Abstract: Particle identification at the Super Charm-Tau factory experiment will be provided by a Focusing Aerogel Ring Imaging CHerenkov detector (FARI

arXiv:2605.19762v1 Announce Type: new Abstract: Code has become a standard component of modern foundation language model (LM) training, yet its role beyond programming remains unclear. We revisit the

arXiv:2605.20151v1 Announce Type: new Abstract: The proliferation of generative artificial intelligence has given rise to an interactive learning environment, where model parameters are continuously u

arXiv:2605.19444v1 Announce Type: cross Abstract: Test-time reinforcement learning (TTRL) reports substantial accuracy gains on mathematical reasoning benchmarks using majority vote as a pseudo-label

arXiv:2605.19908v1 Announce Type: new Abstract: Authorship attribution models fine-tuned with the same pretrained encoder, data, and loss can differ four-fold in performance depending only on their sc

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

Within one 24 hour period, Trump: - got out of a 100 million IRS fine - secured 'immunity' from all future tax investigations for his family and friends - created a 1.8 billion slush fund for lawbreak

arXiv:2605.20073v1 Announce Type: new Abstract: This work proposes a pixel-classification approach for vessel segmentation in x-ray angiograms. The proposal uses textural features such as anisotropic

arXiv:2605.18777v1 Announce Type: cross Abstract: Mapping large origin-destination (OD) datasets remains challenging because flow maps become cluttered, meaningful patterns occur at multiple spatial s

arXiv:2503.14346v3 Announce Type: replace Abstract: Multi-map Sparse Monocular visual Simultaneous Localization and Mapping applied to monocular endoscopic sequences has proven efficient to robustly r

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:2605.18436v1 Announce Type: new Abstract: A large amount of musical heritage has been digitised by memory institutions: libraries, museums, and archives. Nevertheless, the field of Optical Music

arXiv:2605.17851v1 Announce Type: new Abstract: Astrobee's existing one-degree-of-freedom (DOF) underactuated compliant claw gripper enables perching on the International Space Station (ISS), but prov

arXiv:2605.17504v1 Announce Type: cross Abstract: Most current paradigms in visual mechanistic interpretability (MI) remain confined to interpreting internal units of the vision model via heuristic me

arXiv:2605.16779v1 Announce Type: cross Abstract: This work presents a novel method for fitting superquadrics to point clouds under the contamination of noise and outliers, which has many applications

arXiv:2605.18700v1 Announce Type: new Abstract: Prior work on fine-grained image recognition (FGIR) has established the importance of the backbone selection, but has neglected the accuracy-vs-cost tra

arXiv:2605.17954v1 Announce Type: cross Abstract: Modern multimodal large language models (MLLMs) typically keep the language model fixed and train a visual projector that maps the pixels into a seque

arXiv:2605.16383v1 Announce Type: cross Abstract: Deep neural networks achieve high accuracy on image classification tasks. Yet, they often produce overconfident predictions as which fail to express e

arXiv:2511.02414v2 Announce Type: replace Abstract: With the recent success of generative models in image and text, the question of their evaluation has recently gained a lot of attention. While most