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The Kinetics Observer: A Tightly Coupled Estimator for Legged Robots

arXiv:2406.13267v2 Announce Type: replace Abstract: This paper presents the Kinetics Observer, a novel proprioceptive state estimator for legged robots designed to provide the feedback required for ve

The Lattice of Transition Laws

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DGX agent

arXiv:2610.11216v1 Announce Type: cross Abstract: Diffusion and autoregression (AR) have long been seen as different categories of generative models, with diffusion specialising in continuous fields a

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9 Oct 2026

The optimal information complexity of VC learning

arXiv:2610.10600v1 Announce Type: cross Abstract: Steinke and Zakynthinou(2020) introduces the Conditional Mutual Information (CMI) framework of analyzing the information complexity of learning algori

The Sample Complexity of Membership Inference and Privacy Auditing

arXiv:2508.19458v2 Announce Type: replace Abstract: A membership-inference attack gets the output of a learning algorithm, and a target individual, and tries to determine whether this individual is a

Thought-Like-Pro: Enhancing Reasoning of Large Language Models through Self-Bootstrapped Prolog-based Chain-of-Thought

arXiv:2407.14562v3 Announce Type: replace Abstract: Large language models have demonstrated remarkable capabilities as general-purpose assistants, excelling in a wide range of reasoning tasks and supp

Toward Joint Optimization of Circuit Depth and Training Data Size in Adaptively Grown Quantum Classifiers

arXiv:2610.12428v1 Announce Type: cross Abstract: Building a quantum model involves a tradeoff: how complex the circuit should be, and how much training data it needs. Caro et al. show that models wit

Toward Lunar Legged Robots: Field Deployment Lessons at LUNA

arXiv:2610.12276v1 Announce Type: new Abstract: Legged robots are promising candidates for future lunar surface missions because they can traverse steep, loose, and obstacle-rich terrain that challeng

Transferability of Learned States in Neural PDE Solvers

arXiv:2610.10972v1 Announce Type: new Abstract: Assessing useful reuse in neural PDE solvers is challenging: final accuracy can reflect source learning and target-time computation. Our reuse contract

Transformed Samplers with Variance Reduction

arXiv:2610.10870v1 Announce Type: cross Abstract: Markov chain Monte Carlo (MCMC) methods are the standard tool for computing expectations under complex probability distributions. Control variates red

Transforming Image Editors into Video Editors

arXiv:2610.11037v1 Announce Type: new Abstract: Recent image editing systems have achieved impressive semantic understanding, visual fidelity, and instruction-following ability, while video editing re

Transmission Neural Networks: Inhibitory and Excitatory Connections

arXiv:2604.04246v2 Announce Type: replace-cross Abstract: This paper extends the Transmission Neural Network model proposed by Gao and Caines in [1]-[3] to incorporate inhibitory connections and neuro

Type-Checking for Pattern-Based Tree Transformations

arXiv:2610.11337v1 Announce Type: cross Abstract: We introduce and study pattern-based tree transformations. As an illustrating example, consider a source pattern (x dot y) + (x dot z) and a target pa

Understanding Latent-Dimension Scaling in Dynamical-System Learning through Spectral Reliability

arXiv:2610.11866v1 Announce Type: new Abstract: In deep learning, approximation theory motivates increasing representation size. We ask whether this benefit extends to dynamics learning through autore

Using Weisfeiler-Leman Features for Algorithm Selection in Constraint Optimisation

arXiv:2610.12119v1 Announce Type: cross Abstract: Algorithm Selection is essential for efficient Constraint Programming. Over the years, many algorithm selectors based on machine learning methods have

UXBench Pro: Benchmarking Personalized User Experience in Multi-Turn Dialogue Interactions

arXiv:2610.11638v1 Announce Type: new Abstract: Evaluating user experience (UX) with automated computational methods has gained increasing attention, supported by empirical evidence from UXBench. Howe

V-CoLA: Vision Token Compression with Linear Attention

arXiv:2610.11251v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated impressive capabilities but suffer from substantial computational overhead, as vision tokens dominate th

VEDJE: Video-Efficient Discriminative Joint Encoder for Scalable Video-Text Retrieval

arXiv:2610.11850v1 Announce Type: new Abstract: Finding the right video often requires distinguishing similar scenes in which different events occur. Joint matching improves retrieval, but processing

Velocity Scaling in Flow Matching

arXiv:2610.10823v1 Announce Type: new Abstract: Scaling a learned flow-matching velocity field v_heta by a gain gamma(t) was recently shown to greatly improve generation quality. Prior work argued tha

Verification with Transfer: Exact Information Frontiers and Their Price in Calls

arXiv:2610.12211v1 Announce Type: new Abstract: A verifier that accepts or rejects whole answers reveals little: under a flat prior over k-bit answers, zero error needs 2^k-1 verifications. The usual

VersaCamVLA: Camera-Configurable VLA Policies for Robotic Manipulation

arXiv:2610.12451v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as powerful foundations for robotic manipulation, but their reliance on fixed camera configurations dur

VesselSDF: Distance Field Priors for Vascular Network Reconstruction

arXiv:2506.16556v2 Announce Type: replace-cross Abstract: Accurate segmentation of vascular networks from sparse CT scan slices remains a significant challenge in medical imaging, particularly due to

VESSI - VLM-Enhanced Support for Surveillance and Investigations

arXiv:2610.11674v1 Announce Type: new Abstract: Automated video surveillance analysis has become a critical component of intelligence infrastructures and Law Enforcement agencies. Traditional systems

VFold: Symmetry-Aware Cross-Layer Value Cache Compression

arXiv:2610.12338v1 Announce Type: new Abstract: While caching key-value (KV) states accelerates Large Language Model (LLM) decoding, this cache can dominate memory usage at long context lengths. One s

VICO: Visual Environments Co-Evolving for Vision-Language Model Reasoning

arXiv:2610.10782v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard recipe for post-training vision-language models (VLMs), but it typically a

VINCIE-NExT: Unlocking Video Editing from Images via In-Context Modeling

arXiv:2610.12104v1 Announce Type: cross Abstract: Building a capable video editor remains significantly harder than a video generator: editing requires (source, instruction, edited) triplets that are

What is the goal of unsupervised machine learning?

arXiv:2610.11697v1 Announce Type: new Abstract: Unsupervised learning is one of the main branches of machine learning. Here I argue that unlike the other branches of machine learning (supervised and r

When AI Finds Hidden Messages, Does It Report?

arXiv:2610.10620v1 Announce Type: cross Abstract: When an assistant encounters a message for another AI, does it tell its user? Four fixed model-provider deployments perform simulated source tasks in

When Can You Prune Your Network? A Study of Intermediate Neurons in Multilingual Speech Parsing

arXiv:2610.11520v1 Announce Type: new Abstract: End-to-end speech parsing, a task recently proposed, consists in predicting both the transcription and the syntactic tree for a spoken utterance. Existi

When Has a Bayesian Neural Network Sampled Enough? Adaptive Inference Time with Statistical Guarantees

arXiv:2610.12212v1 Announce Type: new Abstract: Bayesian neural network predictions are commonly approximated using a fixed number of Monte Carlo samples per input, without controlling the resulting e

When Lower Reconstruction Loss Hurts: Distributionally Robust Refinement for Low-Bit LLM Quantization

arXiv:2610.11226v1 Announce Type: new Abstract: Weight-only post-training quantization (PTQ) relies heavily on reconstruction loss minimization to preserve model quality at low precision. We show that

Where Draft Trees Lose Target Mass: Exit-Guided Speculative Decoding

arXiv:2610.11750v1 Announce Type: new Abstract: Tree-based speculative decoding verifies multiple draft continuations in one target-model pass, but finite trees built from draft scores face a fundamen

Why machines will still not rule the world

arXiv:2610.11424v1 Announce Type: new Abstract: In our book Why machines will never rule the world [13, 14] we argue that arti- ficial general intelligence is mathematically impossible. This is becaus

Wieszcz-XIX: A 3.1-Billion-Word Corpus of Pre-1918 Polish and Temporally Bounded Language Models Trained From Scratch

arXiv:2610.10592v1 Announce Type: new Abstract: Historical Polish is well documented as a language but annotated in machine-readable form only to about a million words for the period this paper covers

WorldCraft: From Camera Navigation to Object Manipulation in Interactive Video World Models

arXiv:2605.25077v2 Announce Type: replace Abstract: Recent video world models enable interactive camera navigation but provide limited control over individual objects. We study persistent object-state

WorldGuide: Goal-Directed Video World Model for Procedural Task Execution

arXiv:2610.12459v1 Announce Type: new Abstract: Video generators and video-based world models can synthesize plausible visual trajectories, but long-horizon procedural tasks require generation to adap

Writing for the Reviewer: Defensive Writing in GPT Models

arXiv:2610.11355v1 Announce Type: new Abstract: Researchers increasingly use ChatGPT to revise their papers, and recent GPT versions often narrow or even retract the authors' claims. We call such chan

YOCO: You Only Calibrate Once! Fast Mocap Calibration for Dexterous Teleoperation

arXiv:2610.11657v1 Announce Type: new Abstract: Dexterous teleoperation requires reliable human-hand state estimations. However, common low-cost motion-capture gloves and markerless trackers often exh

Zatom-2: Multitask Pretraining on Atomistic Data for Generative Modeling across Domains

arXiv:2610.11454v1 Announce Type: cross Abstract: Unified atomistic modeling has the potential to accelerate discovery in chemistry, materials science, and biology by bridging data-rich chemical domai

A conceptual framework for ideology in online discourse beyond the left and right

arXiv:2603.18945v2 Announce Type: replace-cross Abstract: Computational social science (CSS) has largely operationalized ideology along a single left/right partisan axis when studying online discourse

A Deterministic Evidence Layer for Vision-Language Autism Screening from Naturalistic Home Video

arXiv:2610.09217v1 Announce Type: new Abstract: Autism spectrum disorder (ASD) is diagnosed through specialist observation of a child's social behavior, and access to that expertise is the bottleneck

A Geometry-Based Capacity Theory for Finite-Feature Associative Memory

arXiv:2610.09056v1 Announce Type: new Abstract: We develop a geometry-based capacity theory for exact-key retrieval in compressed finite-feature Hebbian associative memory. For random or approximately

A Lightweight Vision-Language Fusion Framework for Predicting App Ratings from User Interfaces and Metadata

arXiv:2602.20531v2 Announce Type: replace Abstract: App ratings are among the most significant indicators of the quality, usability, and overall user satisfaction of mobile applications. However, exis

A method for multimodal analysis of TAIGA experiment data using essential features

arXiv:2610.08985v1 Announce Type: cross Abstract: The aim of processing and analyzing experimental data from physical experiments is to obtain physically significant information about the phenomenon u

A prism hierarchy of learning regimes in large linear autoencoders

arXiv:2606.05335v2 Announce Type: replace Abstract: Theoretical studies of machine learning models commonly consider different limiting regimes in which the learning dynamics of gradient descent becom

A Proof-of-Concept Study of Weakly Supervised Labeling of Fine-Grained EEG Components for Artifact Attenuation

arXiv:2610.09792v1 Announce Type: new Abstract: Electroencephalography (EEG) is highly susceptible to electromyographic (EMG) artifacts, whose temporal heterogeneity and spatial-spectral overlap with

A Self-Pruning Transformer: Extreme KV-Cache Compression with Universal Attention

arXiv:2610.09051v1 Announce Type: new Abstract: The large KV-cache size of modern LLMs creates a barrier to efficient deployment. Recent work has explored replacing attention layers' RoPE positional e

A Unified Kinematic Representation Enables Reusable Biological Joint Moment Estimation

arXiv:2610.09150v1 Announce Type: new Abstract: Objective: Data-driven models that estimate physiological states, particularly biological joint moments, are widely used in exoskeleton control. However

A Vehicle-Integrated Approach to Digital Twin Deployment for Bridges Through Drive-By Sensing

arXiv:2610.08822v1 Announce Type: new Abstract: Ageing bridge infrastructure is a growing global concern, yet conventional Structural Health Monitoring (SHM) systems are costly and difficult to scale,