Search: “models”

Agentic Insight Generation in VSM Simulations

arXiv:2604.12421v1 Announce Type: new Abstract: Extracting actionable insights from complex value stream map simulations can be challenging, time-consuming, and error-prone. Recent advances in large l

agentsarxiv-cs-cl

Audio Source Separation in Reverberant Environments using eta-divergence based Nonnegative Factorization

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DGX agent

arXiv:2604.12480v1 Announce Type: cross Abstract: In Gaussian model-based multichannel audio source separation, the likelihood of observed mixtures of source signals is parametrized by source spectral

researcharxiv-cs-ai

15 Apr 2026

Automatic Road Subsurface Distress Recognition from Ground Penetrating Radar Images using Deep Learning-based Cross-verification

arXiv:2507.11081v3 Announce Type: replace-cross Abstract: Ground penetrating radar (GPR) has become a rapid and non-destructive solution for road subsurface distress (RSD) detection. However, recogniz

Black-Box Optimization From Small Offline Datasets via Meta Learning with Synthetic Tasks

arXiv:2604.12325v1 Announce Type: cross Abstract: We consider the problem of offline black-box optimization, where the goal is to discover optimal designs (e.g., molecules or materials) from past expe

safetyarxiv-cs-ai

CLEAR: Cross-Lingual Enhancement in Alignment via Reverse-training

arXiv:2604.05821v2 Announce Type: replace Abstract: Existing multilingual embedding models often encounter challenges in cross-lingual scenarios due to imbalanced linguistic resources and less conside

CoG: Controllable Graph Reasoning via Relational Blueprints and Failure-Aware Refinement over Knowledge Graphs

arXiv:2601.11047v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable reasoning capabilities but often grapple with reliability challenges like hallucinations.

researcharxiv-cs-cl

CoSyncDiT: Cognitive Synchronous Diffusion Transformer for Movie Dubbing

arXiv:2604.12292v1 Announce Type: cross Abstract: Movie dubbing aims to synthesize speech that preserves the vocal identity of a reference audio while synchronizing with the lip movements in a target

safetyarxiv-cs-cv

Hardware

DreamStereo: Towards Real-Time Stereo Inpainting for HD Videos

arXiv:2604.12270v1 Announce Type: new Abstract: Stereo video inpainting, which aims to fill the occluded regions of warped videos with visually coherent content while maintaining temporal consistency,

hardwarearxiv-cs-cv

Efficient and Scalable Granular-ball Graph Coarsening Method for Large-scale Graph Node Classification

arXiv:2603.29148v2 Announce Type: replace-cross Abstract: Graph Convolutional Network (GCN) is a model that can effectively handle graph data tasks and has been successfully applied. However, for larg

Enhancing Agentic Textual Graph Retrieval with Synthetic Stepwise Supervision

arXiv:2510.03323v2 Announce Type: replace Abstract: Integrating textual graphs into Large Language Models (LLMs) is promising for complex graph-based QA. However, a key bottleneck is retrieving inform

Evolving the Complete Muscle: Efficient Morphology-Control Co-design for Musculoskeletal Locomotion

arXiv:2604.12855v1 Announce Type: new Abstract: Musculoskeletal robots offer intrinsic compliance and flexibility, providing a promising paradigm for versatile locomotion. However, existing research t

researcharxiv-cs-ro

Applications

FlowPlan-G2P: A Structured Generation Framework for Transforming Scientific Papers into Patent Descriptions

arXiv:2601.02589v2 Announce Type: replace-cross Abstract: Over 3.5 million patents are filed annually, with drafting patent descriptions requiring deep technical and legal expertise. Transforming scie

applicationsarxiv-cs-ai

From edges to meaning: Semantic line sketches as a cognitive scaffold for ancient pictograph invention

arXiv:2604.12865v1 Announce Type: new Abstract: Humans readily recognize objects from sparse line drawings, a capacity that appears early in development and persists across cultures, suggesting neural

From Myopic Selection to Long-Horizon Awareness: Sequential LLM Routing for Multi-Turn Dialogue

arXiv:2604.12385v1 Announce Type: new Abstract: Multi-turn dialogue is the predominant form of interaction with large language models (LLMs). While LLM routing is effective in single-turn settings, ex

GAM: Hierarchical Graph-based Agentic Memory for LLM Agents

arXiv:2604.12285v1 Announce Type: new Abstract: To sustain coherent long-term interactions, Large Language Model (LLM) agents must navigate the tension between acquiring new information and retaining

GigaCheck: Detecting LLM-generated Content via Object-Centric Span Localization

arXiv:2410.23728v3 Announce Type: replace Abstract: With the increasing quality and spread of LLM assistants, the amount of generated content is growing rapidly. In many cases and tasks, such texts ar

local-aiarxiv-cs-cl

Goal-Conditioned Neural ODEs with Guaranteed Safety and Stability for Learning-Based All-Pairs Motion Planning

arXiv:2604.02821v2 Announce Type: replace Abstract: This paper presents a learning-based approach for all-pairs motion planning, where the initial and goal states are allowed to be arbitrary points in

safetyarxiv-cs-ro

Hear Both Sides: Efficient Multi-Agent Debate via Diversity-Aware Message Retention

arXiv:2603.20640v2 Announce Type: replace Abstract: Multi-Agent Debate has emerged as a promising framework for improving the reasoning quality of large language models through iterative inter-agent c

agentsarxiv-cs-cl

Learned Incremental Nonlinear Dynamic Inversion for Quadrotors with and without Slung Payloads

arXiv:2503.09441v2 Announce Type: replace Abstract: The increasing complexity of multirotor applications demands flight controllers that can accurately account for all forces acting on the vehicle. Co

researcharxiv-cs-ro

Tutorials

LLM-Guided Task- and Affordance-Level Exploration in Reinforcement Learning

arXiv:2509.16615v2 Announce Type: replace Abstract: Reinforcement learning (RL) is a promising approach for robotic manipulation, but it can suffer from low sample efficiency and requires extensive ex

tutorialsarxiv-cs-ro

Machine Learning-Based Real-Time Detection of Compensatory Trunk Movements Using Trunk-Wrist Inertial Measurement Units

arXiv:2604.12591v1 Announce Type: new Abstract: Compensatory trunk movements (CTMs) are commonly observed after stroke and can lead to maladaptive movement patterns, limiting targeted training of affe

researcharxiv-cs-ro

Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain

arXiv:2510.05159v4 Announce Type: replace-cross Abstract: While finetuning AI agents on interaction data -- such as web browsing or tool use -- improves their capabilities, it also introduces critical

MAST: Mask-Guided Attention Mass Allocation for Training-Free Multi-Style Transfer

arXiv:2604.12281v1 Announce Type: cross Abstract: Style transfer aims to render a content image with the visual characteristics of a reference style while preserving its underlying semantic layout and

MoDora: Tree-Based Semi-Structured Document Analysis System

arXiv:2602.23061v3 Announce Type: replace-cross Abstract: Semi-structured documents integrate diverse interleaved data elements (e.g., tables, charts, hierarchical paragraphs) arranged in various and

local-aiarxiv-cs-ai

MolMem: Memory-Augmented Agentic Reinforcement Learning for Sample-Efficient Molecular Optimization

arXiv:2604.12237v1 Announce Type: cross Abstract: In drug discovery, molecular optimization aims to iteratively refine a lead compound to improve molecular properties while preserving structural simil

safetyarxiv-cs-ai

Multilingual Multi-Label Emotion Classification at Scale with Synthetic Data

arXiv:2604.12633v1 Announce Type: new Abstract: Emotion classification in multilingual settings remains constrained by the scarcity of annotated data: existing corpora are predominantly English, singl

researcharxiv-cs-cl

OmniFood8K: Single-Image Nutrition Estimation via Hierarchical Frequency-Aligned Fusion

arXiv:2604.12356v1 Announce Type: new Abstract: Accurate estimation of food nutrition plays a vital role in promoting healthy dietary habits and personalized diet management. Most existing food datase

researcharxiv-cs-cv

OpenTME: An Open Dataset of AI-powered H&E Tumor Microenvironment Profiles from TCGA

arXiv:2604.12075v1 Announce Type: cross Abstract: The tumor microenvironment (TME) plays a central role in cancer progression, treatment response, and patient outcomes, yet large-scale, consistent, an

Probabilistic Feature Imputation and Uncertainty-Aware Multimodal Federated Aggregation

arXiv:2604.12970v1 Announce Type: cross Abstract: Multimodal federated learning enables privacy-preserving collaborative model training across healthcare institutions. However, a fundamental challenge

safetyarxiv-cs-cv

Progress-Think: Semantic Progress Reasoning for Vision-Language Navigation

arXiv:2511.17097v2 Announce Type: replace Abstract: Vision-Language Navigation requires agents to act coherently over long horizons by understanding not only local visual context but also how far they

safetyarxiv-cs-ro

Reliability-Guided Depth Fusion for Glare-Resilient Navigation Costmaps

arXiv:2604.12753v1 Announce Type: new Abstract: Specular glare on reflective floors and glass surfaces frequently corrupts RGB-D depth measurements, producing holes and spikes that accumulate as persi

safetyarxiv-cs-ro

Rethinking the Personalized Relaxed Initialization in the Federated Learning: Consistency and Generalization

arXiv:2604.12768v1 Announce Type: new Abstract: Federated learning (FL) is a distributed paradigm that coordinates massive local clients to collaboratively train a global model via stage-wise local tr

local-aiarxiv-cs-lg

Ride the Wave: Precision-Allocated Sparse Attention for Smooth Video Generation

arXiv:2604.12219v1 Announce Type: cross Abstract: Video Diffusion Transformers have revolutionized high-fidelity video generation but suffer from the massive computational burden of self-attention. Wh

local-aiarxiv-cs-ai

Tutorials

RLGT: A reinforcement learning framework for extremal graph theory

arXiv:2602.17276v2 Announce Type: replace Abstract: Reinforcement learning (RL) is a subfield of machine learning that focuses on developing models that can autonomously learn optimal decision-making

tutorialsarxiv-cs-lg

Robust Federated Inference

arXiv:2510.00310v3 Announce Type: replace Abstract: Federated inference, in the form of one-shot federated learning, edge ensembles, or federated ensembles, has emerged as an attractive solution to co

local-aiarxiv-cs-lg

SAM3-I: Segment Anything with Instructions

arXiv:2512.04585v3 Announce Type: replace Abstract: Segment Anything Model 3 (SAM3) advances open-vocabulary segmentation through promptable concept segmentation, enabling users to segment all instanc

safetyarxiv-cs-cv

Security and Resilience in Autonomous Vehicles: A Proactive Design Approach

arXiv:2604.12408v1 Announce Type: cross Abstract: Autonomous vehicles (AVs) promise efficient, clean and cost-effective transportation systems, but their reliance on sensors, wireless communications,

Self-Distillation Zero: Self-Revision Turns Binary Rewards into Dense Supervision

arXiv:2604.12002v1 Announce Type: new Abstract: Current post-training methods in verifiable settings fall into two categories. Reinforcement learning (RLVR) relies on binary rewards, which are broadly

Applications

SmellNet: A Large-scale Dataset for Real-world Smell Recognition

arXiv:2506.00239v5 Announce Type: replace Abstract: The ability of AI to sense and identify various substances based on their smell alone can have profound impacts on allergen detection (e.g. smelling

applicationsarxiv-cs-ai

SpanKey: Dynamic Key Space Conditioning for Neural Network Access Control

arXiv:2604.12254v1 Announce Type: cross Abstract: SpanKey is a lightweight way to gate inference without encrypting weights or chasing leaderboard accuracy on gated inference. The idea is to condition

Stress Detection Using Wearable Physiological and Sociometric Sensors

arXiv:2604.12746v1 Announce Type: new Abstract: Stress remains a significant social problem for individuals in modern societies. This paper presents a machine learning approach for the automatic detec

researcharxiv-cs-lg

Technical Report -- A Context-Sensitive Multi-Level Similarity Framework for First-Order Logic Arguments: An Axiomatic Study

arXiv:2604.12534v1 Announce Type: new Abstract: Similarity in formal argumentation has recently gained attention due to its significance in problems such as argument aggregation in semantics and enthy

The Stackelberg Speaker: Optimizing Persuasive Communication in Social Deduction Games

arXiv:2510.09087v2 Announce Type: replace Abstract: Large language model (LLM) agents have shown remarkable progress in social deduction games (SDGs). However, existing approaches primarily focus on i

safetyarxiv-cs-ai

Training single-electron and single-photon stochastic physical neural networks

arXiv:2604.10861v1 Announce Type: cross Abstract: The computational demands of deep learning motivate the investigation of alternative approaches to computation. One alternative is physical neural net

researcharxiv-cs-lg

UniMark: Unified Adaptive Multi-bit Watermarking for Autoregressive Image Generators

arXiv:2604.11843v1 Announce Type: new Abstract: Invisible watermarking for autoregressive (AR) image generation has recently gained attention as a means of protecting image ownership and tracing AI-ge

researcharxiv-cs-cv

VidTAG: Temporally Aligned Video to GPS Geolocalization with Denoising Sequence Prediction at a Global Scale

arXiv:2604.12159v1 Announce Type: new Abstract: The task of video geolocalization aims to determine the precise GPS coordinates of a video's origin and map its trajectory; with applications in forensi

researcharxiv-cs-cv

WebFactory: Automated Compression of Foundational Language Intelligence into Grounded Web Agents

arXiv:2603.05044v2 Announce Type: replace Abstract: Current paradigms for training GUI agents are fundamentally limited by a reliance on either unsafe, non-reproducible live web interactions or costly

XANE(3): An E(3)-Equivariant Graph Neural Network for Accurate Prediction of XANES Spectra from Atomic Structures

arXiv:2604.12140v1 Announce Type: new Abstract: We present XANE(3), a physics-based E(3)-equivariant graph neural network for predicting X-ray absorption near-edge structure (XANES) spectra directly f

researcharxiv-cs-lg