Knowledge catalogue
arXiv:2605.19185v1 Announce Type: cross Abstract: Sparse goal-conditioned planning with few cost-to-go labels can be viewed as a graph-PDE Dirichlet extension problem: extend sparse labels on a goal-d
arXiv:2605.19145v1 Announce Type: new Abstract: In the literature, many continual learning (CL) algorithms have been proposed to address the issue of catastrophic forgetting in ML models (i.e., learni
arXiv:2605.19943v1 Announce Type: new Abstract: Tiny Recursive Models (TRM) solve complex reasoning tasks with a fraction of the parameters of modern large language models (LLMs) by iteratively refini
arXiv:2605.20079v1 Announce Type: cross Abstract: Diffusion and flow-based generative models dominate visual synthesis, with guidance aligning samples to user input and improving perceptual quality. H
arXiv:2605.19721v1 Announce Type: new Abstract: Graph combinatorial optimization (GCO) has attracted growing interest, as many NP-hard problems naturally admit graph formulations, yet their combinator
arXiv:2605.19052v1 Announce Type: cross Abstract: Lagrangian Relaxation (LR) is a powerful technique for solving large-scale Mixed Integer Linear Programming (MILP), particularly those with decomposab
arXiv:2510.03824v2 Announce Type: replace-cross Abstract: The task of learning a diffusion-based neural sampler for drawing samples from an unnormalized target distribution can be viewed as a stochast
arXiv:2603.07561v2 Announce Type: replace Abstract: Existing concept customization methods have achieved remarkable outcomes in high-fidelity and multi-concept customization. However, they often negle
arXiv:2603.01009v2 Announce Type: replace Abstract: Over the past years, Automated Essay Scoring (AES) systems have gained increasing attention as scalable and consistent solutions for assessing the p
arXiv:2605.18821v1 Announce Type: new Abstract: Machine learning has revolutionized numerous industrial domains. Despite recent advances, machine learning models remain vulnerable to adversarial threa
arXiv:2503.22823v3 Announce Type: replace-cross Abstract: In classical information theory, the Doeblin coefficient of a classical channel provides an efficiently computable upper bound on the total-va
arXiv:2605.18775v1 Announce Type: cross Abstract: Graph-based Retrieval-Augmented Generation (RAG) systems leverage interconnected knowledge structures to capture complex relationships that flat retri
arXiv:2603.09473v2 Announce Type: replace Abstract: Equipping robotic systems with the capacity to generate extit{ex novo} hardware during operation extends control of physical adaptability. Unlike mo
arXiv:2605.18799v1 Announce Type: cross Abstract: Large language models can fail in critic interaction not only by answering incorrectly, but also by abandoning an initially correct scientific solutio
arXiv:2511.17166v2 Announce Type: replace Abstract: Reflections of active markers in the environment are a common source of ambiguity in onboard visual relative localization. This work presents a nove
arXiv:2605.19344v1 Announce Type: new Abstract: Linguistic cues such as 'I believe' and 'probably' offer an intuitive interface for communicating confidence, yet a generalisable, principled calibratio
arXiv:2605.18766v1 Announce Type: cross Abstract: Retrieving relevant tables from extensive databases for a given natural language query is essential for accurately answering questions in tasks such a
arXiv:2605.19510v1 Announce Type: new Abstract: Unsupervised video domain adaptation (UVDA) is a practical but under-explored problem. In this paper, we propose a frustratingly easy UVDA method, calle
arXiv:2605.19073v1 Announce Type: cross Abstract: Representations on the Symmetric Positive Definite (SPD) manifold have garnered significant attention across different applications. In contrast, the
arXiv:2605.19230v1 Announce Type: new Abstract: Age dependent performance disparities in medical image classification often arise because age acts as a confounder, linking imaging morphology with dise
arXiv:2510.09174v3 Announce Type: replace Abstract: This paper takes a closer look at Git Re-Basin, an interesting new approach to merge trained models. We propose a hierarchical model merging scheme
arXiv:2512.11234v2 Announce Type: replace Abstract: Generating controllable indoor scenes is fundamental to applications in game development, architectural visualization, and embodied AI. However, exi
arXiv:2605.19218v1 Announce Type: cross Abstract: Vision-Language Models suffer severe KV cache pressure at inference, as a single image often encodes into thousands of tokens. Most existing methods e
arXiv:2605.18913v1 Announce Type: cross Abstract: The U.S. financial system processes approximately 1.3 million interbank transactions daily, yet no system in the reviewed literature models fraud prop
arXiv:2503.19877v2 Announce Type: replace Abstract: As language model (LM) outputs get more and more natural, it is becoming more difficult than ever to evaluate their quality. Simultaneously, increas
arXiv:2503.12172v4 Announce Type: replace-cross Abstract: Generative models have rapidly evolved to generate realistic outputs. However, their synthetic outputs increasingly challenge the clear distin
arXiv:2605.19340v1 Announce Type: new Abstract: Vision foundation models (VFMs) have achieved strong performance across various vision tasks. However, it still remains challenging to apply VFMs for cr
arXiv:2605.19431v1 Announce Type: new Abstract: Multirotor aerial robots excel at maneuvering in three-dimensional space, and recent advances enable nimble navigation in cluttered and confined environ
arXiv:2605.20110v1 Announce Type: new Abstract: Referring segmentation grounds natural-language queries to pixel-level masks, but extending it to complex scenarios with multiple instances, cross-categ
arXiv:2605.18971v1 Announce Type: cross Abstract: What determines the quality of a tabular foundation model? Unlike language or vision, tabular foundation models acquire their inductive biases almost
arXiv:2605.19355v1 Announce Type: cross Abstract: Retargeting motion across characters with varying body shapes while preserving interaction semantics, such as self-contact and near-body proximity, re
arXiv:2505.09067v2 Announce Type: replace-cross Abstract: In this article, we consider the infinite-horizon reach-avoid (RA) and stabilize-avoid (SA) zero-sum game problems for general nonlinear conti
arXiv:2605.06270v2 Announce Type: replace Abstract: Feed-forward 3D reconstruction models based on Vision Transformers can directly estimate scene geometry and camera poses from a small set of input i
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:2605.18836v1 Announce Type: cross Abstract: Dataset Distillation (DD) synthesizes a compact synthetic dataset that preserves the training utility of a full dataset. However, its standard formula
arXiv:2605.19607v1 Announce Type: cross Abstract: Integrated Gradients (IG) is a widely adopted feature attribution method that satisfies desirable axiomatic properties. However, the choice of integra
arXiv:2605.18856v1 Announce Type: cross Abstract: Long-context inference is increasingly constrained by the KV cache: resident memory grows with context length, and decoding becomes limited by repeate
arXiv:2605.19974v1 Announce Type: new Abstract: The generation of immersive and navigable 3D environments is increasingly prevalent with the growing adoption of virtual reality and 3D content. However
arXiv:2605.20035v1 Announce Type: new Abstract: Omni-modal large language models (om-LLMs) achieve unified audio-visual understanding by encoding video and audio into temporally aligned token sequence
arXiv:2605.18835v1 Announce Type: new Abstract: Traditional sheet metal forming relies on time-consuming and expensive Finite Element Analysis (FEA) for design validation, a process that significantly
arXiv:2603.05933v2 Announce Type: replace Abstract: Applying Small Language Models (SLMs) to Chinese character-driven generation remains challenging due to data scarcity and the difficulty of disentan
arXiv:2511.16766v3 Announce Type: replace Abstract: Scalable Vector Graphics are a standard representation for editable visual design, yet they are usually authored as single view two dimensional illu
arXiv:2605.19319v1 Announce Type: new Abstract: Visual prediction has emerged as a promising paradigm for embodied control, where future observations are generated and then translated into actions. Ho
arXiv:2605.19799v1 Announce Type: cross Abstract: We present a semi-supervised framework for joint segmentation and classification of fetal cardiac ultrasound images. Built upon the EchoCare multi-tas
arXiv:2605.18979v1 Announce Type: new Abstract: We propose Tabular Q-Learning (TabQL), a reinforcement learning framework that replaces the conventional parametric Q-network in Deep Q-Learning (DQN) w
arXiv:2605.20030v1 Announce Type: new Abstract: While optimal transport (OT) enforces a rigid constraint by requiring two measures to be matched exactly, partial optimal transport relaxes this require
arXiv:2409.08248v2 Announce Type: replace Abstract: In this paper, we introduce TextBoost, an efficient one-shot personalization approach for text-to-image diffusion models. Traditional personalizatio
The Codex 'goal' feature will take any silly shortcut possible in order to avoid doing the work (including rewriting your external checks), but if you manage to sufficiently constrain it so that it ha
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. Colossal Biosciences is growing chickens in a 3D-printed artif
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