Knowledge catalogue
arXiv:2609.25386v1 Announce Type: cross Abstract: Footwear outsole impressions are a common form of forensic pattern evidence, yet quantitative methods for estimating wearer attributes from these imag
arXiv:2609.26304v1 Announce Type: new Abstract: Tendon-driven continuum manipulators are widely used in medical applications, where accurate tip-position estimation is essential for precise navigation
arXiv:2606.05438v2 Announce Type: replace Abstract: We study the deterministic first-order oracle complexity of finding (epsilon)-stationary points in smooth nonconvex optimization when the objective
arXiv:2609.25721v1 Announce Type: cross Abstract: Language models are increasingly trained on the outputs of other models, forming chains that we call lineages, in which a trait present in one generat
arXiv:2609.22408v1 Announce Type: new Abstract: AI systems are becoming participants in the evaluation and use of scientific research. They encounter citation counts, download statistics and lists of
arXiv:2412.11325v2 Announce Type: replace Abstract: 3D human mesh reconstruction (HMR) from RGB images often degrades under poor illumination, occlusion, and non-line-of-sight conditions. Acoustic sen
arXiv:2609.25067v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has become an effective approach for learning visual representations without manual annotations. Among SSL approaches,
arXiv:2609.26408v1 Announce Type: new Abstract: Map-based vision-language navigation (VLN) relies on persistent spatial representations to connect language understanding with geometric planning. Howev
arXiv:2609.24847v1 Announce Type: cross Abstract: LLM inference on edge devices is constrained by computational and memory resources, making efficient autoregressive decoding challenging. Speculative
arXiv:2603.02293v3 Announce Type: replace Abstract: Frozen pretrained features are often treated as a safe interface for downstream learning: only a small linear readout is trained, while the backbone
arXiv:2609.26165v1 Announce Type: new Abstract: Weight-space structure often correlates with language-model behavior, but correlation alone does not establish computational involvement. We study conce
arXiv:2609.22620v1 Announce Type: new Abstract: Scanned mail, uploaded PDFs, and consolidated attachments often arrive as page streams that must be split into individual documents before downstream cl
arXiv:2609.26488v1 Announce Type: new Abstract: While Chain-of-Thought (CoT) reasoning has improved the capability of language models, directly applying it to Spoken Language Models (SLMs) may introdu
arXiv:2609.25143v1 Announce Type: new Abstract: Unsupervised Continual chunking is a fundamental problem in machine learning and neuroscience, where the goal is to identify groups of states that frequ
arXiv:2609.26774v1 Announce Type: new Abstract: Vector Quantization (VQ) is fundamental to discrete visual tokenizers that power modern autoregressive and masked image generation models. While recent
arXiv:2511.02769v2 Announce Type: replace Abstract: Many molecular Transformers lack probabilistic latent variables for posterior inference and latent interpolation. We introduce STAR-VAE, a SELFIES-e
arXiv:2609.26647v1 Announce Type: cross Abstract: We study statistical rates in entropic optimal transport in the semi-discrete regime where one measure has finite support and the other is subGaussian
arXiv:2603.01765v5 Announce Type: replace Abstract: Monocular depth foundation models generalize across diverse scenes, but recovering accurate metric depth consistent with a target sensor remains cha
arXiv:2603.05294v3 Announce Type: replace Abstract: Existing LLM-based web agents struggle on complex, long-horizon tasks due to limited in-context memory, weak planning abilities, and greedy behavior
arXiv:2609.26406v1 Announce Type: cross Abstract: Principal component analysis (PCA) is a fundamental tool to reduce the dimensionality of the data in many applications. PCA finds a few signal directi
arXiv:2609.25546v1 Announce Type: cross Abstract: Music creation often involves iterative refinement, changing selected musical details while retaining the rest. To support such refinement, we introdu
arXiv:2609.22628v1 Announce Type: new Abstract: Every document QA system begins with a choice that is rarely studied on its own: whether to feed the model page images, extracted text, or both. We isol
Brace yourself: It turns out AI is being optimized for cheating. OpenAI’s agents hacked into Hugging Face to get the answers to a cybersecurity test. Next, they solved a prestigious math problem (or j
arXiv:2609.26018v1 Announce Type: new Abstract: Many learning problems combine a dominant regularity with systematic exceptions. Motivated by U-shaped learning in language acquisition, we study this i
arXiv:2609.25144v1 Announce Type: cross Abstract: Lepto-regression is defined as the machine learning process of constructing a Regression Tree of a target feature on itself. It is a novel, model-free
arXiv:2609.25134v1 Announce Type: new Abstract: This paper presents a probabilistic perspective on large language models (LLMs), developed with the aim of bringing together, in a single self-contained
arXiv:2609.25678v1 Announce Type: cross Abstract: Large language model (LLM) agents must generalize from tools seen during training to unseen tools at deployment. A key challenge is tool trialing, i.e
arXiv:2609.26078v1 Announce Type: new Abstract: In this paper, we propose ToW3D that enables precise and consistent control over 3D generative adversarial networks (GANs) with the Tug-of-War competiti
arXiv:2603.20988v2 Announce Type: replace Abstract: Artificial Intelligence is starting to automate scientific discovery, raising the prospect of an automated science of the mind. We chart this field
arXiv:2609.26603v1 Announce Type: new Abstract: Hierarchical latent communication improves the generalization of a multi-grid power-flow model to new operating scenarios. The module exchanges informat
arXiv:2609.25775v1 Announce Type: new Abstract: Recent advances in generative video models have enabled the synthesis of visually realistic content, posing significant challenges to synthetic video de
arXiv:2609.26347v1 Announce Type: new Abstract: The scarcity of non-English language data in specialized domains significantly limits the development of effective Natural Language Processing (NLP) too
arXiv:2609.25588v1 Announce Type: cross Abstract: In this note, we show that the problem of checking, whether a sequence of bits is ordered, is not doable by 1-head 1-layer transformers but is doable
arXiv:2609.25604v1 Announce Type: new Abstract: Stochastic rendering eliminates the sorting and alpha blending process in Gaussian splatting, at the cost of introducing spatial noise. Formulating temp
arXiv:2609.24688v1 Announce Type: cross Abstract: Angular-margin speaker encoders are widely used in voice conversion, yet the geometry of their classifier prototypes remains poorly understood. We ana
arXiv:2609.26753v1 Announce Type: new Abstract: Spatial flow measurements support underwater navigation, but distributed sensing is constrained by robot size and sensor layout. We use a causal observe
arXiv:2609.26598v1 Announce Type: cross Abstract: The future 6G networks are expected to incorporate a proliferation of wireless services in diverse environments, which presents a significant challeng
arXiv:2609.26513v1 Announce Type: new Abstract: Multimodal language models traditionally rely on dedicated perceptual encoders to construct task-usable representations. More integrated architectures h
arXiv:2609.25785v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as general-purpose robotic manipulation policies. However, in dexterous hand manipulation, contact forc
arXiv:2609.25917v1 Announce Type: new Abstract: In this work, we propose a communication-free framework for vision-based formation control of fully actuated underwater robots subject to sensing constr
arXiv:2609.26561v1 Announce Type: cross Abstract: We present an improvement on previous spacecraft pose estimation architectures that results in the lowest published mean rotation errors we know of on
arXiv:2609.25845v1 Announce Type: cross Abstract: Many vision applications ask several independent, forced-choice questions about the same image. Visual Jev encodes the image and public context once,
arXiv:2609.26117v1 Announce Type: new Abstract: Human-centric audio-visual generation spans several closely related tasks: animating a person from driving speech, jointly generating speech and video f
arXiv:2509.04600v2 Announce Type: replace Abstract: Reconstructing global human motion from monocular video is fundamental to VR, graphics, and robotics, yet remains ill-posed due to depth ambiguity,
arXiv:2609.25123v1 Announce Type: cross Abstract: Pathologists integrate morphology across magnifications and across the slides of a patient case, whereas pathology foundation models encode thousands
arXiv:2609.26037v1 Announce Type: new Abstract: Explanations are central to causal reasoning, and cognitive science has long established that the human drive to explain is itself a mechanism for learn
arXiv:2609.25809v1 Announce Type: new Abstract: Fine-grained mixture-of-experts (MoE) architectures have become a mainstream design for open-weight LLMs, with hundreds of experts and increasingly many
arXiv:2501.16698v2 Announce Type: replace Abstract: Spatial intelligence, encompassing 3D perception and reasoning, is the essential next frontier of AI. Scaling current 3D vision-language models (VLM
arXiv:2609.22681v1 Announce Type: new Abstract: Dexterous manipulation in confined spaces requires local control of hand orientation. Without a wrist, a dexterous hand must obtain this local orientati
arXiv:2609.23907v1 Announce Type: new Abstract: Generative models of neural activity could help characterize tissue dynamics, compare experimental conditions, and simulate population activity for appl
arXiv:2609.24718v1 Announce Type: new Abstract: While a centralized approach involving patient consent to collect and analyze data centrally would theoretically offer the best data quality and predict
arXiv:2609.22099v1 Announce Type: new Abstract: Cooking is a complex process that transforms raw ingredients into delicious and nutritious dishes, yet the recipes that encode this process remain large
arXiv:2609.22839v1 Announce Type: cross Abstract: Can simple learning rules keep their regret bounded in self-play? Recent work achieves constant regret bounds through modified regularization and high
arXiv:2609.22974v1 Announce Type: new Abstract: In this paper, we investigate the Minimum Obstacle Displacement Planning problem from a robot motion planning perspective. The problem involves determin
arXiv:2609.23687v1 Announce Type: cross Abstract: This paper introduces a multi-temporal tabular dataset derived from satellite images to map burned areas in the Chapada dos Veadeiros National Park, i
arXiv:2609.23333v1 Announce Type: new Abstract: Digital direct-to-consumer (DTC) health campaigns are usually measured after the fact. In-flight forecasting commonly relies on a separate classifier fo
arXiv:2609.24761v1 Announce Type: new Abstract: Aerial manipulators represent the forefront of aerial robotics. Although potentially capable of complex interaction tasks, controlling aerial manipulato
arXiv:2609.22229v1 Announce Type: new Abstract: We generated synthetic multivariate time series for 27 refrigerators with a simplified physicsinspired simulator at one-minute resolution. The simulator
arXiv:2602.02940v2 Announce Type: replace-cross Abstract: Formal semantics and distributional semantics are distinct approaches to linguistic meaning: the former models meaning as reference via model-
arXiv:2609.24702v1 Announce Type: new Abstract: We study scalable peer-to-peer dynamic average consensus (DC) for multi-robot systems under finite-range, finite-rate, and interference-constrained comm