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You Only Touch Once: 6-DoF Object Pose Estimation from Single Tactile Contact

model-releasesarxiv-cs-ro

arXiv:2606.28899v1 Announce Type: new Abstract: Accurate 6-DoF object pose estimation is fundamental to robotic manipulation, yet vision-based methods often fail under occlusion, poor lighting, and re

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Local Ai

Your Data Manifold is Secretly a Reward Model: Shell-LCC for Text-to-Video Generation

DGX agent

arXiv:2606.30248v1 Announce Type: new Abstract: Recent text-to-video (T2V) diffusion models rely heavily on auxiliary reward signals (e.g., via reward models or DPO) to align generated content with hu

local-aiarxiv-cs-cv

30 Jun 2026

Zero-Gated Language-conditioned Human Motion Prediction

arXiv:2606.29208v1 Announce Type: new Abstract: Pose histories provide the core kinematic evidence for 3D human motion prediction, but they lack explicit high-level semantic guidance. This paper intro

Zero-Label Driving Scenario Complexity Detection via Joint Embedding Predictive Architecture

arXiv:2606.28383v1 Announce Type: new Abstract: Identifying complex and safety-critical driving scenarios in large unlabelled datasets is an important but expensive problem. Existing approaches rely o

safetyarxiv-cs-cv

Zero-Shot Depth from Defocus

arXiv:2603.26658v2 Announce Type: replace Abstract: Depth from Defocus (DfD) is the task of estimating a dense metric depth map from a focus stack. Unlike previous works overfitting to a certain datas

A Comparison of Fusion Techniques for Multi-Modal Human Activity Recognition on the HARMES Dataset

arXiv:2606.27886v1 Announce Type: new Abstract: Recent advances in Human Activity Recognition (HAR) from wearable sensors have shown that multi-modal deep learning models consistently outperform their

A Comprehensive Survey on World Models for Embodied AI

arXiv:2510.16732v3 Announce Type: replace Abstract: Embodied AI requires agents that perceive, act, and anticipate how actions reshape future world states. World models serve as internal simulators th

agentsarxiv-cs-cv

A Gaussian Perspective for Distributional Discrepancy in Generative Diffusion Models

arXiv:2601.13602v3 Announce Type: replace-cross Abstract: This paper introduces an analytical approach to quantifying and optimizing the distributional discrepancy in generative diffusion models. For

A Multi-Attribute Latent Space for Visual Analysis of Watches

arXiv:2606.27897v1 Announce Type: new Abstract: We present a design rationale, embedding model, and interactive visual-analysis system for exploring large wristwatch collections through heterogeneous

A Primer on SO(3) Action Representations in Deep Reinforcement Learning

arXiv:2510.11103v3 Announce Type: replace-cross Abstract: Many robotic control tasks require policies to act on orientations, yet the geometry of SO(3) makes this nontrivial. Because SO(3) admits no g

A Study of Temporal Fusion Strategies for Named Entity Recognition in Historical Texts

arXiv:2606.27881v1 Announce Type: cross Abstract: Temporal variation poses a unique challenge for named entity recognition (NER) in historical texts, where entities drift in surface form and salience

A Survey of Automated Presentation Coaching: Systems, Methods, and Open Challenges

arXiv:2606.27380v1 Announce Type: new Abstract: Automated coaching for oral presentations sits at the intersection of computer-assisted pronunciation training (CAPT), prosody modeling, and speech synt

researcharxiv-cs-cl

A Tree-of-Thoughts Inspired Hybrid Approach for Legal Case Judgement Summarization using LLMs

model-releasesarxiv-cs-cl

arXiv:2606.28044v1 Announce Type: new Abstract: In recent times, Large Language Models (LLMs) are increasingly being used for legal case judgement summarization. Most prior works have tried traditiona

A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of O(2)

arXiv:2606.27864v1 Announce Type: new Abstract: Vision transformers have become a dominant architecture for visual recognition. However, standard models do not explicitly encode the planar symmetries

Accelerating Attention with Basis Decomposition

arXiv:2510.01718v2 Announce Type: replace Abstract: Attention is a core operation in large language models (LLMs). We present BD Attention (BDA), a lossless algorithmic reformulation of attention. BDA

Accelerating Hierarchical Sparse Predictive Coding with Hybrid Amortized Inference

arXiv:2606.27802v1 Announce Type: new Abstract: Hierarchical predictive coding provides an interpretable framework for perception as error-driven inference in multi-layer generative models, while spar

Active Exploration via Autoregressive Generation of Missing Data

arXiv:2405.19466v4 Announce Type: replace Abstract: We pose uncertainty quantification and exploration in online decision-making as a problem of training and generation from an autoregressive sequence

Adaptive Momentum and Nonlinear Damping for Neural Network Training

arXiv:2602.00334v2 Announce Type: replace Abstract: Momentum Stochastic Gradient Descent (mSGD) relies on a fixed momentum coefficient shared across all parameters, failing to account for the heteroge

Adaptive Probability Flow Residual Minimization for High-Dimensional Fokker-Planck Equations

arXiv:2512.19196v4 Announce Type: replace-cross Abstract: Solving high-dimensional Fokker-Planck (FP) equations remains a challenging problem in computational physics and stochastic dynamics, due to t

Adaptive Turn-Taking for Real-time Multi-Party Voice Agents

arXiv:2606.13544v3 Announce Type: replace-cross Abstract: Turn-taking in multi-party spoken conversations remains a fundamental challenge for voice-based agents, particularly under dynamic floor compe

Advancing Speaker-Based Vocal Effort Classification with WavLM and Data Augmentation in Naturalistic Non-Calibrated Speech Recordings

arXiv:2606.27543v1 Announce Type: cross Abstract: The variations in vocal effort range (e.g. whisper, soft, neutral, loud, shout) alter production and speech acoustics, reducing intelligibility and li

Adversarial Contamination Meets Hard Thresholding: An Iterative Algorithm with Signal Adaptivity and Minimax Optimality

arXiv:2606.27685v1 Announce Type: cross Abstract: Pervasive data contamination -- stemming from measurement errors, outliers, or adversarial corruption -- has motivated the development of robust stati

Applications

AeroGrab: A Unified Framework for Aerial Grasping in Cluttered Environments

arXiv:2603.15097v2 Announce Type: replace Abstract: Reliable aerial grasping in cluttered environments remains challenging due to occlusions and collision risks. Existing aerial manipulation pipelines

applicationsarxiv-cs-ro

Agent-Native Immune System: Architecture, Taxonomy, and Engineering

arXiv:2606.28270v1 Announce Type: new Abstract: The transition from static chat bots to autonomous agents--equipped with persistent memory, tool-use protocols, and multi-agent collaboration--has funda

Agentic AI-Powered Re-Identification: An Emerging, Scalable Threat to Mobility Microdata Privacy

arXiv:2606.27936v1 Announce Type: cross Abstract: The widespread collection of fine-grained location data by commercial data brokers creates a re-identification risk that is not widely recognised by t

Agentic Episodic Control

arXiv:2506.01442v2 Announce Type: replace Abstract: Reinforcement learning (RL) remains fundamentally limited by poor data efficiency and weak generalization. Prior episodic RL methods attempt to alle

Agentic Hardware Design as Repository-Level Code Evolution

model-releasesarxiv-cs-ai

arXiv:2606.28279v1 Announce Type: cross Abstract: We present HORIZON, a self-evolving agent framework that treats hardware design as repository-level code evolution. A Markdown harness is compiled int

Agentic Publication Protocol: An Attempt to Modernize Scientific Publication

arXiv:2606.27386v1 Announce Type: cross Abstract: Scientific publication is still organized primarily around static manuscripts, even though much of scientific progress depends on tacit know-how: how

AI-Driven Synthesis for High-Tech System Design: Automating Innovation

arXiv:2606.28126v1 Announce Type: new Abstract: This article addresses the combinatorial complexity inherent in modern high-tech system design by presenting automation-in-design (AiD) as a transformat

AI-Generated Image Recognition via Fusion of CNNs and Vision Transformers

arXiv:2606.27637v1 Announce Type: new Abstract: Recent advancements in synthetic data technology have opened a new era where images of remarkable quality are generated, blurring the lines between real

AI-Model Network: Concept, Current State and Future

arXiv:2606.27382v1 Announce Type: new Abstract: While the primary function of computers lies in computation and processing, the core value of the Internet is rooted in sharing and collaboration. Compu

AI Persuasive Framing in Collective Dilemmas

arXiv:2606.27951v1 Announce Type: cross Abstract: AI agents are promising tools that can act as flexible behavioral nudges to enhance human cooperation in addressing large-scale societal problems. How

researcharxiv-cs-cl

AirGroundBench: Probing Spatial Intelligence in Multimodal Large Models under Heterogeneous Multi-View Embodied Collaboration

arXiv:2606.28049v1 Announce Type: new Abstract: In recent years, multimodal large language models (MLLMs) have shown strong potential for embodied intelligence, yet their ability to maintain geometric

Algorithms for Deciding the Safety of States in Fully Observable Non-deterministic Problems: Technical Report

arXiv:2603.15282v2 Announce Type: replace Abstract: Learned action policies are increasingly popular in sequential decision-making, but suffer from a lack of safety guarantees. Recent work introduced

Aloe-Vision: Robust Vision-Language Models for Healthcare

model-releasesarxiv-cs-cl

arXiv:2606.27500v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) specialized in healthcare are emerging as a promising research direction due to their potential impact in clinica

An Approach to Enriching Surgical Video Datasets for Fine-Grained Spatial-Temporal Understanding of Vision-Language Models

arXiv:2604.00784v2 Announce Type: replace Abstract: Surgical video understanding is a crucial prerequisite for advancing Computer-Assisted Surgery. While vision-language models (VLMs) have recently be

An Embedded Real-Time License Plate Recognition System for Complex Traffic Scenes

arXiv:2606.27772v1 Announce Type: new Abstract: Vehicle license plate recognition is an integral component of intelligent transportation systems. In this work, we present an embedded real-time license

An Empirical Analysis of Factual Errors in Human-Written Text and its Application

model-releasesarxiv-cs-cl

arXiv:2606.27959v1 Announce Type: new Abstract: Factual Error Detection (FED), which is the task of identifying factually incorrect spans in a given text, has long been recognized as an important rese

An Expectation-Maximization Algorithm for Training Clean Diffusion Models from Corrupted Observations

arXiv:2407.01014v2 Announce Type: replace Abstract: Diffusion models excel in solving imaging inverse problems due to their ability to model complex image priors. However, their reliance on large, cle

Local Ai

An Interpretable, Controllable Time-Varying IIR Denoiser for On-Device Assistive Hearing

arXiv:2603.02794v2 Announce Type: replace-cross Abstract: We present TVF (Time-Varying Filtering), an interpretable, low-latency speech enhancement model for real-time, on-device assistive hearing. A

local-aiarxiv-cs-ai

Applications

AO-ARC: Almost-Surely Asymptotically Optimal Multi-Robot Motion Planning with ARC

arXiv:2606.27495v1 Announce Type: new Abstract: We present AO-ARC, an anytime multi-robot motion planning (MRMP) method that achieves initial solution times on par with state-of-the-art MRMP feasibili

applicationsarxiv-cs-ro

Applicability of memorization indicators for early spotting of overfitting while recalibrating sEMG-decoders on low sample sizes

model-releasesarxiv-cs-ai

arXiv:2606.27855v1 Announce Type: cross Abstract: Deep learning models for surface electromyography (sEMG) can benefit substantially from subject-specific (re-)calibration, since no sufficiently large

Applications

Are Time-Series Foundation Models Ready for E-Nose Data? An Empirical Assessment of Their Embeddings

arXiv:2606.27672v1 Announce Type: new Abstract: Inspired by advances in natural language processing and computer vision, 'time-series foundation models' (TSFMs) have recently been introduced with the

applicationsarxiv-cs-lg

Artificial Intelligence Index Report 2026

arXiv:2606.15708v2 Announce Type: replace Abstract: Welcome to the ninth edition of the AI Index report. As AI continues to advance rapidly, the question becomes whether the systems built around it ca

ATOD: Annealed Turn-aware On-policy Distillation for Multi-turn Autonomous Agents

arXiv:2606.27814v1 Announce Type: new Abstract: Training small language-model agents for long-horizon interactive tasks requires both fast imitation and reward-driven improvement. On-policy distillati

Aurora: A Leverage-Aware Spectral Optimizer

arXiv:2606.27715v1 Announce Type: new Abstract: We show that for tall matrix parameters, like projection matrices in the MLP layers, the Muon update can have row norms that are arbitrarily non-uniform

Autoencoder Architectures for Athlete Performance Scoring from Wearable Telemetry

arXiv:2606.28145v1 Announce Type: new Abstract: Wearable devices produce large, high dimensional training logs for everyday runners, and interpretation rather than data collection is now the limiting

Automated brain tumor detection in MRI images using CNN and ResNet architectures

arXiv:2606.27405v1 Announce Type: cross Abstract: Deep learning has shown significant potential in medical image analysis, particularly for disease detection using MRI scans. Accurate and early diagno