Search: “models”

The value of information and the emergence of communication in evolved e-puck robots

arXiv:2610.13118v1 Announce Type: new Abstract: We study when communication emerges between autonomous agents and what role an innate action selection architecture plays. Two e-puck robots, reconstruc

agentsarxiv-cs-ro

12 Oct 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Training User Simulators with Latent Intrinsic Feedback

DGX agent

arXiv:2610.13617v1 Announce Type: new Abstract: User simulators are gaining attention as environments to train LLM assistants that can better cope with the nuances of multi-turn conversations with rea

researcharxiv-cs-cl

12 Oct 2026

Universal Bounds for Self-Normalized Kullback-Leibler Estimation

arXiv:2610.12851v1 Announce Type: cross Abstract: This work studies an entropy-based estimator of Kullback-Leibler (KL) divergence constructed from normalized importance weights. We prove a universal

safetyarxiv-cs-lg

12 Oct 2026

A Survey on Archetypal Analysis

arXiv:2504.12392v3 Announce Type: replace-cross Abstract: Archetypal analysis (AA) was originally proposed in 1994 by Adele Cutler and Leo Breiman as a computational procedure for extracting distinct

ActiveMedAgent: Cost-Aware Trajectory Learning for Multimodal Medical Diagnosis

arXiv:2610.11140v1 Announce Type: cross Abstract: Clinical diagnosis is inherently sequential: clinicians escalate from cheap to costly tests only when additional evidence is expected to resolve diagn

AgentEvolver: System-Wide Self-Evolution Through Task Execution

arXiv:2610.11613v1 Announce Type: new Abstract: An agent can complete a task without improving how it works. Turning task experience into reusable capability requires connecting the changed component

agentsarxiv-cs-ai

AgentGarten: Code Worlds for Evolving Agents

arXiv:2610.12374v1 Announce Type: new Abstract: Interactive virtual worlds allow agents to learn through exploration and interaction. What agents can learn is bounded by the environments they practice

tutorialsarxiv-cs-cv

All Verdicts are Not Equal: Rethinking LLM Judge Reliability

arXiv:2610.12083v1 Announce Type: cross Abstract: LLM-as-a-Judge is the standard paradigm for NLP evaluation, yet its systemic reliability remains poorly understood despite being widely treated as a d

Autonomous thermodynamic cycles via robotic mobility and sensing

arXiv:2610.11667v1 Announce Type: cross Abstract: Thermodynamic cycles are the foundation of energy conversion across natural and engineered systems, transforming heat into useful work. However, these

agentsarxiv-cs-ro

Autoregressive Retriever: Improving Query Understanding from Item Feedback for Universal Multimodal Retrieval

arXiv:2610.11666v1 Announce Type: cross Abstract: Universal multimodal retrieval typically encodes a query once and ranks independently indexed items by embedding similarity. This design supports effi

Hardware

Batch Before You Lift: Scalable Topological Deep Learning on Large Graphs

arXiv:2610.12247v1 Announce Type: cross Abstract: Topological Deep Learning extends graph-based learning to higher-order domains, such as hypergraphs, cellular, and simplicial complexes. These domains

hardwarearxiv-cs-ai

Bayesian Optimisation under State-Preservation Constraints

arXiv:2610.12150v1 Announce Type: new Abstract: In many engineering design problems, the objective and constraints depend on the state: the solution of a PDE determined by the design parameters. We co

Beyond Preset Identities: Selective Stance Accommodation and Interaction Reorganisation in Generative Agent Societies

arXiv:2603.23406v3 Announce Type: replace Abstract: Generative agent societies simulate people with assigned roles, preferences and relationships. As agents exchange arguments and choose partners, the

agentsarxiv-cs-ai

Beyond Spatio-Temporal Priors: A Generalizable Approach for Dense Correspondence Matching

arXiv:2610.12421v1 Announce Type: new Abstract: Dense correspondence matching has historically been bounded by simplifying spatio-temporal priors, such as smooth motion and rigid geometry. While effec

BridgeGuard: Explicit Safety Drift for Diffusion-based Autonomous Driving

arXiv:2610.11483v1 Announce Type: new Abstract: Diffusion-based driving planners capture diverse behaviors but can generate unsafe trajectories under distribution shift. We propose BridgeGuard, a safe

Calibrating Ambiguity Set via Diagnostic Transport for Distributionally Robust Optimization

arXiv:2610.10793v1 Announce Type: cross Abstract: Distributionally robust optimization (DRO) protects decisions against distributional uncertainty by optimizing over an ambiguity set, but poorly align

Camera-Noise Residuals for Face-Swap Detection: Redundant, Not Complementary, and Why

arXiv:2610.11683v1 Announce Type: new Abstract: Fusing a learned camera-noise fingerprint with an RGB appearance backbone is an appealing route to generator-independent deepfake detection, because the

Chronos Enables Code Agents to Reason over Software Evolution

arXiv:2610.11578v1 Announce Type: cross Abstract: Historical pull requests record the design decisions, compatibility constraints, and implementation patterns behind a codebase's current state. Experi

agentsarxiv-cs-cl

CoCam4D: Geometry-Aware Cooperative 4D Perception for Camera-Only Autonomous Driving

arXiv:2610.11577v1 Announce Type: cross Abstract: Autonomous vehicles often suffer from limited perception due to occlusions, blind spots, limited sensor range, and the complex nature of surrounding e

agentsarxiv-cs-cv

Cognitive Thermometers: Machine Learning and Logical Complexity

arXiv:2610.10724v1 Announce Type: new Abstract: How does the human mind represent semantic categories? Why do natural languages favor certain meanings over others? Prior explanations have relied on lo

researcharxiv-cs-cl

Local Ai

Conformal Data Contamination Tests for In-distribution Data Acquisition

arXiv:2507.13835v2 Announce Type: replace-cross Abstract: The amount of quality data in many machine learning tasks is limited to what is available locally to data owners. The set of quality data can

local-aiarxiv-cs-lg

Constrained Dynamic Gaussian Splatting

arXiv:2602.03538v2 Announce Type: replace Abstract: While Dynamic Gaussian Splatting enables high-fidelity 4D reconstruction, its deployment is severely hindered by a fundamental dilemma: unconstraine

CRISP: Fixing Flying Pixels in Latent LiDAR Generation via Diffusion Decoding

arXiv:2610.11376v1 Announce Type: cross Abstract: Latent LiDAR pipelines suffer from flying pixels: convolutional VAEs blur sharp radial depth discontinuities, yielding edge depths that back-project t

Applications

DOGS: Design-Space Sampling for Prompt-Driven Logo Generation

arXiv:2610.10760v1 Announce Type: new Abstract: Prompt optimization for text-to-image (T2I) generation has been pursued almost entirely as text rewriting, in which a short user brief is expanded into

applicationsarxiv-cs-cv

EgoPhys: Estimating Peak Contact Force and Mechanical Work from Egocentric Manipulation Video

arXiv:2610.11347v1 Announce Type: new Abstract: Physically grounded manipulation of articulated objects requires understanding both the maximum forces encountered during contact and the work performed

Evi-VN: Hard Region Guided Virtual Node Evidence Injection for GNN-Based Fraud Detection

arXiv:2610.11665v1 Announce Type: new Abstract: Online platforms contain growing numbers of bots, deceptive reviewers, and scam accounts that imitate legitimate users. Such camouflage blurs graph neig

tutorialsarxiv-cs-lg

Local Ai

Evidence-Traceable Dynamic Interviewer Architecture for Expertise-Adaptive Qualitative Interviews Using Local LLMs

arXiv:2610.11651v1 Announce Type: new Abstract: Automated interviewers and conversational agents are increasingly used in research, recruitment, customer service, and education. However, many existing

local-aiarxiv-cs-ai

Explaining the Saliency Map Sparsity of Adversarially-Trained Neural Networks

arXiv:2610.10666v1 Announce Type: new Abstract: Understanding why deep neural networks make a given prediction is of great importance for their safe deployment. In computer vision, saliency maps, whic

Exploiting Gradients in Bayesian Inference of Expensive Simulators

arXiv:2610.12076v1 Announce Type: new Abstract: Simulators based on differential equations are ubiquitous in science and engineering. They are often used in simulation-based inference to evaluate the

tutorialsarxiv-cs-lg

Local Ai

F^3NO: Frequency-Decomposed Finite-Time Flow-map Neural Operators with Cross-Scale Conditioning

arXiv:2610.10998v1 Announce Type: new Abstract: Neural operators enable fast PDE forecasting, but repeated predictions accumulate errors and fine-scale structures remain difficult to resolve. We intro

local-aiarxiv-cs-lg

Fractional Heat Kernel for Semi-Supervised Graph Learning with Small Training Sample Size

arXiv:2510.04440v2 Announce Type: replace Abstract: We develop a source-driven fractional heat-kernel framework for semi-super-vised graph learning that combines nonlocal propagation with sustained la

From Video Clips to Creation Trajectory: Sora100K for AI-Native Video Creation

arXiv:2610.11770v1 Announce Type: new Abstract: AI-Native video creation is shifting from isolated video clips toward iterative video creation workflows. However, existing datasets remain largely vide

Gaze Estimation for Human-Robot Interaction: Analysis Using the NICO Platform

arXiv:2509.24001v3 Announce Type: replace Abstract: This paper evaluates the current gaze estimation methods within a human-robot interaction (HRI) context of a shared workspace scenario. We introduce

tutorialsarxiv-cs-cv

Gen-PINNs: Generative Adversarial Physics Informed Neural Networks for solving partial differential equations

arXiv:2610.10897v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) are a widely used data-free method for solving Partial Differential Equations (PDEs) using machine learning. Wi

safetyarxiv-cs-lg

GPF-Net: Gated Progressive Fusion Learning for Polyp Re-Identification

arXiv:2512.21476v2 Announce Type: replace-cross Abstract: Colonoscopic Polyp Re-Identification (ReID) aims to match the same polyp across a large gallery of images captured from different viewpoints a

GROB: A Multi-Agent Architecture for Public-Trace Investigation of Candidate Agentic Activity

arXiv:2610.11467v1 Announce Type: cross Abstract: We present GROB, a multi-agent architecture for investigating candidate autonomous-agent activity through public Internet traces when privileged telem

agentsarxiv-cs-ai

HAND: A Biologically-Inspired Activation Function that Improves Generalisation and Sample Efficiency in Image Classification

arXiv:2610.11534v1 Announce Type: new Abstract: DNNs exhibit robustness and generalisation issues not seen in humans. They are also far less data-efficient learners, requiring considerably more traini

safetyarxiv-cs-cv

Higher-Order Action Supervision Makes A Strong Policy Class

arXiv:2610.11175v1 Announce Type: cross Abstract: Modern data-driven decision-making methods, such as imitation learning (IL) and reinforcement learning (RL), have achieved great success in solving ma

Higher-Order Morphology Priors for Quadruped Reinforcement Learning Under Actuator Degradation

arXiv:2610.10934v1 Announce Type: cross Abstract: Actuator degradation turns quadruped locomotion into a coordination problem requiring joints to compensate for lost actuation. Prior work suggests tha

safetyarxiv-cs-lg

Applications

How Firm Should a Grasp Be?

arXiv:2610.11221v1 Announce Type: cross Abstract: An ideal robot grasp is firm enough to securely handle an object, yet gentle enough to avoid damaging it. Achieving this balance requires knowledge of

applicationsarxiv-cs-cv

Improving Image-Based Nutrition Estimation Through Multimodal Food-Item Verification and Recovery

arXiv:2610.11144v1 Announce Type: cross Abstract: Single-image nutrition estimation can fail silently when visible foods are missed. Even when a food is correctly identified, its proposed region may n

Intent Graph: Navigating the Analytical Reasoning Space for Exploratory Data Analysis

arXiv:2610.11025v1 Announce Type: cross Abstract: Exploratory data analysis (EDA) is rarely open-ended in practice: analysts work from high-level domain questions toward the concrete analyses that can

Leakage-Controlled Multimodal Learning for Diagnosis and Progression Prediction in Alzheimer's Disease Research

arXiv:2610.10648v1 Announce Type: new Abstract: Alzheimer's disease prediction involves irregular visits, heterogeneous measurements and incomplete modalities. This study presents a multimodal multita

Learning How to Search for Plans with Exponentially Less Space

arXiv:2610.10954v1 Announce Type: new Abstract: Heuristic search for a plan can store exponentially many states, even when its heuristic is almost perfect. We instead learn search control, one specifi

Learning Language-Conditioned Traversability Representations for Adaptive Visual Navigation

arXiv:2610.11622v1 Announce Type: new Abstract: Traversability is essential for visual navigation but varies with robot capabilities and user preferences. Conventional pipelines often rely on explicit

researcharxiv-cs-ro

Learning qBIC Resonances across Metasurface Families in Dielectric Fourier Space

arXiv:2610.11500v1 Announce Type: cross Abstract: Bound states in the continuum (BIC) metasurfaces are typically described by geometry-specific parameters, hindering cross-geometry comparison, while u

Learning the Loop, Not Just the Page: Execution-Grounded Loop Learning for Web Generation

arXiv:2610.11543v1 Announce Type: new Abstract: Functional Web generation is increasingly optimized with executable rewards, yet existing methods largely focus on the quality of the final page and lea

safetyarxiv-cs-cl

Learning What to Trust in Multimodal Learning under Noisy Supervision

arXiv:2610.11057v1 Announce Type: new Abstract: Multimodal classification processes and relates information from multiple modalities to achieve more accurate predictions. However, existing methods typ

safetyarxiv-cs-cv