Search: “papers”

CARNet: Channel-Adaptive Receiver Network for Robust NextG Communications

arXiv:2608.02172v1 Announce Type: cross Abstract: Neural receivers have been recognized as a promising paradigm for the next-generation (NextG) communications. However, due to the reliance on a static

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CAVE: Competence-Aware Visual Boundary Evidence Alignment for Video Temporal Grounding

DGX agent

arXiv:2608.02078v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have achieved substantial performance gains in Video Temporal Grounding (VTG) through reinforcement learning (RL).

safetyarxiv-cs-cl

4 Aug 2026

Local Ai

CDG-MAE: Cross-view Masked Modeling using Diffusion Generated Views

arXiv:2506.18164v2 Announce Type: replace Abstract: Cross-view masked autoencoding has emerged as a powerful pretext task for learning dense correspondences, which are essential for applications such

local-aiarxiv-cs-cv

Credit Assignment and Efficient Exploration based on Influence Scope in Multi-agent Reinforcement Learning

arXiv:2505.08630v2 Announce Type: replace Abstract: Training cooperative agents in sparse-reward scenarios poses significant challenges for multi-agent reinforcement learning (MARL). Without clear fee

agentsarxiv-cs-lg

CRISP: Critical Step Perception for Training Efficient Deep Search Agents

arXiv:2608.01867v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly extended into deep search agents that solve complex questions through multi-step interaction with external

safetyarxiv-cs-cl

Crushing the Evidence: A Dual-Penalty Evasion Framework for Fooling White-Box Explainable AI Auditors

arXiv:2608.00566v1 Announce Type: new Abstract: Post-hoc model explainers such as LIME, SHAP, and Integrated Gradients are widely deployed to audit models in high-stakes sensitive domains, including f

CTRAG: An In-Context Retrieval-based Framework for Automated Compliance Checking using LLMs

arXiv:2608.02472v1 Announce Type: new Abstract: Trust is fundamental in modern regulatory ecosystems, and compliance checking plays a critical role in fostering that trust. Regulatory compliance verif

safetyarxiv-cs-cl

Applications

DAG-FM: A Foundation Model for Causal Discovery under Heterogeneous Causal Mechanisms

arXiv:2607.11510v2 Announce Type: replace Abstract: Causal discovery from observational tabular data remains fundamentally challenging, primarily due to the heterogeneity of underlying causal mechanis

applicationsarxiv-cs-lg

Deep Learning CNN and Recurrence Analysis for Alpha Gamma EEG Biomarkers in Fragile X Syndrome

arXiv:2608.00835v1 Announce Type: cross Abstract: Fragile X Syndrome (FXS) is a neurodevelopmental disorder caused by reduced expression of fragile X mental retardation protein (FMRP), leading to disr

Deep Learning for Retinal Degeneration Assessment: A Comprehensive Analysis of the MARIO Challenge

arXiv:2506.02976v4 Announce Type: replace Abstract: The MARIO challenge, held at MICCAI 2024, focused on advancing the automated detection and monitoring of age-related macular degeneration (AMD) thro

Deep Multimodal Fusion Detection through Spatial Mask and Channel Fusion

arXiv:2608.02092v1 Announce Type: new Abstract: Deep multimodal fusion for object detection has demonstrated good performance through mining modal characteristics. However, existing feature-level fusi

Deep Research Pretraining via Predictive Navigation

arXiv:2608.00432v1 Announce Type: new Abstract: Deep research agents are often trained on expensive, environment-grounded tool-use trajectories that require repeated retrieval, document inspection, an

safetyarxiv-cs-cl

DeepDefense: Robust Learning via Layer-Wise Gradient-Feature Alignment

arXiv:2511.13749v2 Announce Type: replace Abstract: Deep neural networks are known to be vulnerable to adversarial perturbations, which are small, carefully crafted inputs that lead to incorrect predi

Deployment-Ready UWB Localization for Industrial Ground Robots with Automatic Anchor Calibration and Terrain-Aware Fusion

model-releasesarxiv-cs-ro

arXiv:2607.15807v2 Announce Type: replace Abstract: Ultra-Wideband (UWB) ranging has become a viable option for industrial Autonomous Mobile Robot (AMR) localization due to improved accuracy and low c

DeVIT: Low-Power Vision Transformer Acceleration Using Delta Computation

arXiv:2608.01343v1 Announce Type: new Abstract: The emergence of transformer-based deep learning models has brought unprecedented performance across various domains, particularly in natural language p

DiffPhysCam: Differentiable Physics-Based Camera Simulation for Inverse Rendering and Embodied AI

arXiv:2508.08831v2 Announce Type: replace-cross Abstract: Generating synthetic images that closely mimic those from real cameras is instrumental in training visual models and enabling end-to-end visuo

agentsarxiv-cs-cv

DiffPrune: differentiable information throttling for token pruning in vision-language models

arXiv:2608.01985v1 Announce Type: new Abstract: Visual token pruning reduces the computational cost of Vision-Language Models (VLMs) by removing redundant visual tokens. The key is to learn a score th

DODA: A Database of Datasets for Aesthetics Research

arXiv:2608.00089v1 Announce Type: new Abstract: With rapid growth in the fields of empirical and computational aesthetics we have seen a vast increase in large image datasets annotated for aesthetics.

Does Explainability Transfer? A Controlled Benchmark of Attribution Methods on Vision Transformers and CNNs

arXiv:2608.02396v1 Announce Type: new Abstract: Most evidence on the effectiveness of explainable artificial intelligence (XAI) attribution methods has been established on convolutional neural network

Applications

Does the Competitive Component of Adversarial Self-Play Improve Legal Reasoning? A Controlled Negative Result

arXiv:2608.01559v1 Announce Type: cross Abstract: Adversarial self-play is an appealing recipe for legal reasoning: have a student model draft an argument, have an adversary attack it, and reward the

applicationsarxiv-cs-cl

Domain-Specific Evaluation of Text-to-Speech Systems: A Multi-Metric Benchmarking Study

model-releasesarxiv-cs-cl

arXiv:2608.02235v1 Announce Type: new Abstract: Recent advances in neural text-to-speech (TTS) systems have substantially improved speech naturalness and intelligibility across many languages. However

DriveCode: Domain Specific Numerical Encoding for LLM-Based Autonomous Driving

arXiv:2603.00919v3 Announce Type: replace Abstract: Large language models (LLMs) have shown great promise for autonomous driving. However, discretizing numbers into tokens limits precise numerical rea

agentsarxiv-cs-cv

DS@GT ARC at MEDIQA-CORE-Task-1 2026: Trimodal Model Fusion with Task-Specific Gates for Brain Tumor Subtype Classification

arXiv:2608.00086v1 Announce Type: new Abstract: Brain tumor diagnosis is a time-sensitive process in which patients may wait weeks for a finalized pathology report. This problem motivates automated sy

DynamicManip: Enabling Dynamic Manipulation from a Single Static Demonstration

arXiv:2608.01452v1 Announce Type: cross Abstract: Dynamic manipulation is a critical capability for robots operating in complex and dynamic environments, where robots must interact with objects that a

DynImmune-BERT: Dynamic Immune Repertoire Modeling with Neural ODE Driven Continuous Transformers

arXiv:2607.17244v2 Announce Type: replace Abstract: Longitudinal T cell receptor repertoires contain signals of clonal expansion, contraction, disappearance, and reappearance after immune perturbation

EchoCache: Energy-Guided Cross-Modal Caching for Efficient Audio-Driven Video Generation

arXiv:2608.02474v1 Announce Type: new Abstract: Audio-driven video generation (A2V) has achieved promising progress in synthesizing temporally coherent and audio-visually aligned videos, yet its infer

Local Ai

Empowering Credit Risk Detection in Weixin Pay with Billion-Scale Deep Graph Learning

arXiv:2608.02168v1 Announce Type: new Abstract: Credit risk detection, particularly mitigating individual fraud, is crucial for maintaining the stability of digital financial ecosystems. Accurately id

local-aiarxiv-cs-lg

Enhancing Large Language Model Reasoning with Reward Models: An Analytical Survey

arXiv:2510.01925v3 Announce Type: replace Abstract: Reward models (RMs) play a critical role in enhancing the reasoning performance of LLMs. For example, they can provide training signals to finetune

researcharxiv-cs-cl

Enriched text-guided variational multimodal knowledge distillation network (VMD) for automated diagnosis of plaque vulnerability in 3D carotid artery MRI

arXiv:2509.11924v2 Announce Type: cross Abstract: Multimodal learning has attracted much attention in recent years due to its ability to effectively utilize data features from a variety of different m

Ensemble of Unsupervised Deep Learning for Clustering Imbalanced Tabular Data

arXiv:2608.00346v1 Announce Type: new Abstract: Data imbalance poses a major challenge in supervised classification, where the majority-class bias contributes to false negatives and overestimates clas

EOVSAM: Efficient Open-Vocabulary Segmentation with SAM 3 in One Pass

arXiv:2608.02284v1 Announce Type: new Abstract: Open-vocabulary segmentation identifies and segments objects from arbitrary textual descriptions. SAM 3 supports noun-phrase-guided segmentation and ach

Extended Field of View Analysis for VideoGAN-based Trajectory Generation

arXiv:2608.02289v1 Announce Type: new Abstract: Realistic and diverse trajectory generation is central to enabling higher levels of vehicle automation. While rule-based and classical learning-based me

Factorized AdaBoost.MH Achieves the Same Convergence Rate as AdaBoost.MH

arXiv:2608.01091v1 Announce Type: new Abstract: AdaBoost.MH reduces multi-class classification to a collection of binary subproblems and enjoys the classical boosting-type convergence guarantee under

FairForensics: Seeing Expressions and Parsing Demographics via Vision-Language Modeling for Generalizable Fair Deepfake Detection

arXiv:2608.01661v1 Announce Type: new Abstract: The challenge of fair deepfake detection (FDD) has attracted increasing attention. Existing fairness-enhanced detectors often suffer from suboptimal gen

Fairness in Augmented Graph Learning: A Survey

arXiv:2504.21296v2 Announce Type: replace Abstract: Graph learning has evolved into Augmented Graph Learning (AGL) by integrating specialized machine learning (ML) techniques. Examples include federat

Fast Discovery of Inclusion Dependencies with Desbordante

arXiv:2608.02213v1 Announce Type: cross Abstract: Inclusion dependency is a relation between attributes of tables that indicates possible Primary Key-Foreign Key references. Automatic discovery of inc

FRA-NBV: A Fast and Reflectivity-Aware Next-Best-View Strategy

arXiv:2608.01950v1 Announce Type: new Abstract: Autonomous 3D reconstruction with depth sensors is strongly affected by reflective surfaces, which cause missing or unreliable measurements and reduce t

agentsarxiv-cs-ro

From Global to Local: A Scalable Benchmark for Local Posterior Sampling

arXiv:2507.21449v2 Announce Type: replace-cross Abstract: Degeneracy is an inherent feature of the loss landscape of neural networks, but it is not well understood how stochastic gradient MCMC (SGMCMC

From Vessel Trajectories to Safety-Critical Encounter Scenarios: A Generative AI Framework for Autonomous Ship Digital Testing

arXiv:2603.28067v2 Announce Type: replace Abstract: Digital testing has emerged as a key paradigm for the development and verification of autonomous maritime navigation systems, yet the availability o

Applications

Fruit-HSNet: A Machine Learning Approach for Hyperspectral Image-Based Fruit Ripeness Prediction

arXiv:2608.01202v1 Announce Type: new Abstract: Fruit ripeness prediction (FRP) is a classification-based agricultural computer vision task that has attracted much attention, thanks to its wide-rangin

applicationsarxiv-cs-cv

Gaokerena: A Small Persian Medical Language Model Family

model-releasesarxiv-cs-cl

arXiv:2608.00932v1 Announce Type: new Abstract: The integration of artificial intelligence into medical question-answering systems has advanced rapidly; however, research remains predominantly focused

Local Ai

Generalized Quadratic Gradient: A New Direction in Optimization via the Fusion of Positive-Definite Curvature Matrices and Gradients into A Unified Framework

arXiv:2608.01552v1 Announce Type: cross Abstract: Quadratic Gradient (QG) is a Newton-type optimization framework that bridges first-order gradient descent and second-order optimization by incorporati

local-aiarxiv-cs-lg

Generative Brownian Bridge Diffusion In Motion Space For Enhanced Myocardial Strain Analysis

arXiv:2608.01677v1 Announce Type: new Abstract: Myocardial strain analysis of cardiac magnetic resonance (CMR) images provides an important tool for evaluating cardiac function. However, current techn

Generative Models for Modeling and Synthesizing MIMO Channels in Adverse Weather Conditions

arXiv:2608.00156v1 Announce Type: cross Abstract: The push for broader coverage in future cellular networks depends on reliable service, yet this is increasingly harder to do as we encounter more inst

Gram-Space: Structure-Preserving Codebook Compression for Memory-Efficient Neuro-Symbolic AI

arXiv:2608.01528v1 Announce Type: new Abstract: Vector symbolic architectures (VSA) are widely used for reasoning in neuro-symbolic (NeSy) AI, yet high-dimensional codebooks often create severe memory

Grounded Vision-Language Interpreter for Long-Horizon Bimanual Task and Motion Planning

arXiv:2506.03270v3 Announce Type: replace Abstract: While recent advances in vision-language models have accelerated language-guided robot planning, their black-box nature lacks the safety guarantees

safetyarxiv-cs-ro

Hardware

HetRoute Heterogeneous and Cost-aware Collaborative Routing Framework for Distributed Edge MoE Inference

arXiv:2608.00577v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models have become a dominant architecture for large-scale AI services, yet deploying them over geo-distributed heterogeneous

hardwarearxiv-cs-cl

Hybrid-Domain Posterior Sampling for Inverse Problems via Latent Flow Matching

arXiv:2608.00537v1 Announce Type: new Abstract: Latent Flow Models have revolutionized compressed-space image synthesis, yet their application to high-fidelity inverse problems remains bottlenecked. I

safetyarxiv-cs-cv