Knowledge catalogue
arXiv:2601.17657v4 Announce Type: replace Abstract: Robotic and autonomous systems need dense spatial cues, yet adding a dedicated depth estimator can duplicate visual processing already performed by
arXiv:2610.05029v1 Announce Type: new Abstract: Vision-language foundation models such as CLIP provide strong semantic representations, but their patch tokens are not directly optimized for dense metr
arXiv:2610.06383v1 Announce Type: new Abstract: Inference-time steering offers cheap, fine-grained control over a language model's outputs by estimating a concept's representation in activation space
arXiv:2610.03799v1 Announce Type: new Abstract: Recovering executable CAD programs from 3D meshes is challenging due to the compositional nature of CAD construction and the interaction between discret
arXiv:2610.05961v1 Announce Type: new Abstract: Valuing player actions in football requires accounting for strategic interactions among 22 players, including off-ball movements and defensive positioni
arXiv:2610.03947v1 Announce Type: new Abstract: Finding a compact formula that fits a set of input-output pairs and predicts outputs on unseen inputs is a fundamental problem in science. Symbolic regr
arXiv:2601.02799v3 Announce Type: replace Abstract: Uniform-noise discrete diffusion and flow models generate sequences non-autoregressively through iterative, context-dependent token replacements. Ho
arXiv:2610.03828v1 Announce Type: new Abstract: Quadruped robots entering hospitals, care homes, and quiet offices must be context-appropriate not only in where they move but in how loudly they move:
arXiv:2610.06658v1 Announce Type: new Abstract: In daily life, each person exhibits unique speaking habits, leading to subtle yet consistent lip-shape variations even when pronouncing the same word. A
arXiv:2610.04529v1 Announce Type: new Abstract: Text-driven motion editing modifies an existing motion sequence according to a text instruction while preserving the content of the source motion. Exist
arXiv:2610.06814v1 Announce Type: new Abstract: World models learn to predict how their environment will evolve, making them an important foundation for general-purpose robotic control. Yet world acti
arXiv:2610.05350v1 Announce Type: new Abstract: Behavioral Foundation Models (BFMs) aim to solve a wide range of downstream tasks without test-time policy learning by inferring a task vector from the
arXiv:2607.18490v2 Announce Type: replace Abstract: How the dynamical regime of the observed system affects equation discovery has mainly been investigated through comparisons across systems. However,
arXiv:2407.21783v3 Announce Type: cross Abstract: Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It i
arXiv:2610.06156v1 Announce Type: new Abstract: A representation family is a distinct way of extracting features from time series. Ensemble algorithms that combine several representation families rema
arXiv:2610.05182v1 Announce Type: cross Abstract: Infrared image super-resolution is currently led by Mamba-based networks with 26 to 37 million parameters, which are difficult to deploy on the airbor
arXiv:2610.04156v1 Announce Type: cross Abstract: LLM agents for clinical text-to-SQL applications reason autonomously over multiple steps but cannot assess whether their own reasoning or outputs can
arXiv:2610.06288v1 Announce Type: new Abstract: Wi-Fi channel state information (CSI) enables contactless presence detection and gesture recognition. Its high-dimensional complex-valued time series re
arXiv:2610.06487v1 Announce Type: new Abstract: Heterogeneous multi-robot path planning is a well-studied problem in which agents with disparate kinematic and dynamic models must coordinate to achieve
arXiv:2610.06657v1 Announce Type: new Abstract: Workplace sensing studies combine long-running behaviour traces with self-reports, yet the tools that collect those data often sit apart from the interf
arXiv:2610.05854v1 Announce Type: new Abstract: Triangular attention is a core computation in AlphaFold3-style biomolecular models, with cubic cost in token count. Its shared pair bias adds a gradient
arXiv:2306.10426v3 Announce Type: replace Abstract: As robustness verification methods are becoming more precise, training certifiably robust neural networks is becoming ever more relevant. To this en
arXiv:2610.04092v1 Announce Type: new Abstract: Generating a boundary representation (B-rep) conditioned on a single image requires faithful reconstruction of geometry, valid topology, and support for
arXiv:2610.06831v1 Announce Type: new Abstract: Sliders provide an intuitive interface for continuous image editing. In current generative approaches, however, the slider is simply a rescaling of the
arXiv:2610.04588v1 Announce Type: cross Abstract: Molecular property prediction is central to computational drug discovery, where graph neural networks learn to weight neighboring atomic environments
arXiv:2610.05230v1 Announce Type: new Abstract: Most vision-language-action models represent future motion as fixed-rate action chunks, tying temporal resolution and prediction horizon to a fixed outp
arXiv:2610.06293v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable potential in video understanding, yet their reliance on retrospective summarizatio
arXiv:2610.04006v1 Announce Type: new Abstract: Limited training data diversity constrains generative modeling of 3D human bodies: conservative models remain close to observed examples, whereas explor
arXiv:2610.06063v1 Announce Type: new Abstract: Semantic segmentation of street panoramas can support detailed descriptions of urban environments, yet small datasets and unequal training costs make mo
arXiv:2610.05095v1 Announce Type: cross Abstract: Latent Dirichlet Allocation (LDA) and models derived from it remain widely used topic models. LDA observes each document as a bag-of-words and models
arXiv:2610.06540v1 Announce Type: new Abstract: Spatio-temporal graph models typically encode each snapshot with a GNN and then connect the resulting representations through a temporal module. This sp
arXiv:2610.06176v1 Announce Type: cross Abstract: Near-term quantum natural language processing (QNLP) experiments often run on classical simulators, so simulator cost is part of the field's practical
arXiv:2610.04303v1 Announce Type: new Abstract: Recursive computation repeatedly compresses or reuses intermediate states, creating a simple tension: information that must remain useful across longer
arXiv:2610.04686v1 Announce Type: cross Abstract: Multi-agent debate can improve reasoning, yet often fails to beat simple majority voting. We argue that successful debate requires two distinct mechan
arXiv:2610.05492v1 Announce Type: new Abstract: Vision-language-action (VLA) models have shown strong potential as generalist robot policies, but adapting them to unseen tasks often requires costly pa
Over the past several months, we conducted an empirical post-mortem investigation into 109 autonomous AI agent security incidents (cataloged with 193 falsification criteria across tool-use and multi-a
arXiv:2407.18137v2 Announce Type: replace Abstract: Small object detection and tracking in videos remain critical yet underexplored challenges in computer vision, particularly for applications such as
arXiv:2610.04869v1 Announce Type: new Abstract: An interaction has two parts: someone decides to act, and then chooses whom to act on. Temporal link prediction has concentrated on the second, and we s
arXiv:2610.03402v1 Announce Type: new Abstract: To deploy deep neural networks on edge hardware, highly efficient inference schemes are necessary that retain high accuracy. This work presents W16A16,
arXiv:2610.03715v1 Announce Type: cross Abstract: We introduce 4DCodeBench, a benchmark for 4D inverse graphics through code generation, in which agents reconstruct dynamic scenes from video as execut
A while ago, I posted here getting OSS-120B and GLM-4.6 playing full games of Civilization V. Since then, models have moved pretty far, and we wanted a better understanding about models' capabilities
arXiv:2610.02461v1 Announce Type: new Abstract: Accurate thermal analysis of heterogeneous 2.5D/3D-IC packages is essential yet computationally prohibitive. A single full-package FEM simulation can ta
arXiv:2610.02439v1 Announce Type: new Abstract: Generative graph models are central to understanding and simulating complex networks. However, existing approaches have complementary strengths and limi
arXiv:2610.02451v1 Announce Type: new Abstract: Effective wildfire monitoring requires relating visual evidence to physical fire dynamics, yet real videos with synchronized physical annotations are sc
arXiv:2508.11902v4 Announce Type: replace Abstract: This study examines how much handwritten-character information is retained by a deliberately simple first-order edge representation. Instead of lear
arXiv:2610.03396v1 Announce Type: new Abstract: Bayesian data assimilation combines model forecasts with noisy observations, but sampling high-dimensional, non-Gaussian posteriors remains challenging.
arXiv:2610.03563v1 Announce Type: new Abstract: Sampling-based model predictive control (MPC) is a powerful approach to trajectory optimization, but its performance depends on an informative cost func
arXiv:2603.19655v2 Announce Type: replace Abstract: This work addresses open-loop control of a soft continuum robot (SCR) from video-learned latent dynamics. Visual Oscillator Networks (VONs) from pre
arXiv:2610.02706v1 Announce Type: new Abstract: Visuomotor policies trained via imitation learning often inherit the unnecessarily slow timing of teleoperated demonstrations. Yet uniform speedup is un
arXiv:2610.02869v1 Announce Type: cross Abstract: Autonomous penetration testing agents conduct multi-step attacks by continuously adapting their plans and actions to target responses. As a common def
arXiv:2610.03413v1 Announce Type: new Abstract: Sequential learning systems often make decisions from accumulated experience while receiving high-dimensional inputs whose distribution may change over
This past year, OpenAI, Anthropic, and other labs have announced breakthroughs on numerous long-standing mathematical problems, in some cases pushing well beyond what researchers expected current syst
arXiv:2610.02421v1 Announce Type: new Abstract: Androgenetic alopecia (AGA) is characterized by patterned follicular miniaturization, increased single-hair follicular units, and altered hair-shaft dia
arXiv:2610.03078v1 Announce Type: new Abstract: Quantifying conversational dynamics requires reliable identification of interactional units and their temporal boundaries, but speech activity alone doe
arXiv:2505.13012v3 Announce Type: replace-cross Abstract: Time-Varying Bayesian Optimization (TVBO) is the go-to framework for optimizing a time-varying black-box objective function that may be noisy
arXiv:2609.35013v2 Announce Type: replace Abstract: The rising cost and demand for energy, together with environmental sustainability goals, create major challenges for energy management. Energy Consu
arXiv:2406.19892v5 Announce Type: replace Abstract: This article presents multilingual deep learning models for identifying web registers -- text varieties such as news reports and discussion forums -
arXiv:2610.02428v1 Announce Type: new Abstract: Autonomous mobile robots (AMRs) increasingly perform material transport in production logistics, where their operation is governed by job generation, di
arXiv:2610.03587v1 Announce Type: new Abstract: Joint embedding predictive architectures (JEPAs) predict future latent representations without reconstructing observations, enabling world models to foc
arXiv:2610.03007v1 Announce Type: cross Abstract: Long-output reasoning shifts the KV-cache bottleneck from the fixed prompt to the generated trace. Existing reasoning-cache eviction methods largely t