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VeriGraphi: A Multi-Agent Framework of Hierarchical RTL Generation for Large Hardware Designs

arXiv:2604.14550v1 Announce Type: cross Abstract: Generating synthesizable Verilog for large, hierarchical hardware designs remains a significant challenge for large language models (LLMs), which stru

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VeruSAGE: A Study of Agent-Based Verification for Rust Systems

DGX agent

arXiv:2512.18436v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown impressive capability to understand and develop code. However, their capability to rigorously reason a

model-releasesarxiv-cs-ai

17 Apr 2026

Vision-Based Safe Human-Robot Collaboration with Uncertainty Guarantees

arXiv:2604.15221v1 Announce Type: cross Abstract: We propose a framework for vision-based human pose estimation and motion prediction that gives conformal prediction guarantees for certifiably safe hu

VisPCO: Visual Token Pruning Configuration Optimization via Budget-Aware Pareto-Frontier Learning for Vision-Language Models

arXiv:2604.15188v1 Announce Type: new Abstract: Visual token pruning methods effectively mitigate the quadratic computational growth caused by processing high-resolution images and video frames in vis

VisRet: Visualization Improves Knowledge-Intensive Text-to-Image Retrieval

arXiv:2505.20291v4 Announce Type: replace-cross Abstract: Text-to-image retrieval (T2I retrieval) remains challenging because cross-modal embeddings often behave as bags of concepts, underrepresenting

VoxSafeBench: Not Just What Is Said, but Who, How, and Where

arXiv:2604.14548v1 Announce Type: cross Abstract: As speech language models (SLMs) transition from personal devices into shared, multi-user environments, their responses must account for far more than

Wasserstein Formulation of Reinforcement Learning. An Optimal Transport Perspective on Policy Optimization

arXiv:2604.14765v1 Announce Type: new Abstract: We present a geometric framework for Reinforcement Learning (RL) that views policies as maps into the Wasserstein space of action probabilities. First,

WaveSFNet: A Wavelet-Based Codec and Spatial--Frequency Dual-Domain Gating Network for Spatiotemporal Prediction

arXiv:2603.23284v2 Announce Type: replace Abstract: Spatiotemporal predictive learning aims to forecast future frames from historical observations in an unsupervised manner, and is critical to a wide

Weight Patching: Toward Source-Level Mechanistic Localization in LLMs

model-releasesarxiv-cs-ai

arXiv:2604.13694v1 Announce Type: new Abstract: Mechanistic interpretability seeks to localize model behavior to the internal components that causally realize it. Prior work has advanced activation-sp

What Is the Minimum Architecture for Prolepsis? Early Irrevocable Commitment Across Tasks in Small Transformers

arXiv:2604.15010v1 Announce Type: cross Abstract: When do transformers commit to a decision, and what prevents them from correcting it? We introduce extbf{prolepsis}: a transformer commits early, task

When Does Content-Based Routing Work? Representation Requirements for Selective Attention in Hybrid Sequence Models

arXiv:2603.20997v2 Announce Type: replace Abstract: We identify a routing paradox in hybrid sequence models: content-based routing - deciding which tokens deserve expensive attention - requires pairwi

researcharxiv-cs-lg

When Fairness Metrics Disagree: Evaluating the Reliability of Demographic Fairness Assessment in Machine Learning

arXiv:2604.15038v1 Announce Type: cross Abstract: The evaluation of fairness in machine learning systems has become a central concern in high-stakes applications, including biometric recognition, heal

When Flat Minima Fail: Characterizing INT4 Quantization Collapse After FP32 Convergence

arXiv:2604.15167v1 Announce Type: new Abstract: Post-training quantization (PTQ) assumes that a well-converged model is a quantization-ready model. We show this assumption fails in a structured, measu

When Missing Becomes Structure: Intent-Preserving Policy Completion from Financial KOL Discourse

arXiv:2604.14333v1 Announce Type: new Abstract: Key Opinion Leader (KOL) discourse on social media is widely consumed as investment guidance, yet turning it into executable trading strategies without

When PCOS Meets Eating Disorders: An Explainable AI Approach to Detecting the Hidden Triple Burden

arXiv:2604.14356v1 Announce Type: new Abstract: Women with polycystic ovary syndrome (PCOS) face substantially elevated risks of body image distress, disordered eating, and metabolic challenges, yet e

Applications

Which bird does not have wings: Negative-constrained KGQA with Schema-guided Semantic Matching and Self-directed Refinement

arXiv:2604.14749v1 Announce Type: new Abstract: Large language models still struggle with faithfulness and hallucinations despite their remarkable reasoning abilities. In Knowledge Graph Question Answ

applicationsarxiv-cs-cl

Why Do Vision Language Models Struggle To Recognize Human Emotions?

arXiv:2604.15280v1 Announce Type: new Abstract: Understanding emotions is a fundamental ability for intelligent systems to be able to interact with humans. Vision-language models (VLMs) have made trem

WILD-SAM: Phase-Aware Expert Adaptation of SAM for Landslide Detection in Wrapped InSAR Interferograms

arXiv:2604.14540v1 Announce Type: new Abstract: Detecting slow-moving landslides directly from wrapped Interferometric Synthetic Aperture Radar (InSAR) interferograms is crucial for efficient geohazar

Tutorials

World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems

arXiv:2604.14732v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for building embodied agents that ground perception and language into action.

tutorialsarxiv-cs-lg

Agents

WybeCoder: Verified Imperative Code Generation

arXiv:2603.29088v2 Announce Type: replace-cross Abstract: Recent progress in large language models (LLMs) has substantially advanced automatic code generation and formal theorem proving, yet software

agentsarxiv-cs-ai

xFODE: An Explainable Fuzzy Additive ODE Framework for System Identification

arXiv:2604.14883v1 Announce Type: new Abstract: Recent advances in Deep Learning (DL) have strengthened data-driven System Identification (SysID), with Neural and Fuzzy Ordinary Differential Equation

xFODE+: Explainable Type-2 Fuzzy Additive ODEs for Uncertainty Quantification

arXiv:2604.14880v1 Announce Type: new Abstract: Recent advances in Deep Learning (DL) have boosted data-driven System Identification (SysID), but reliable use requires Uncertainty Quantification (UQ)

XMark: Reliable Multi-Bit Watermarking for LLM-Generated Texts

arXiv:2604.05242v2 Announce Type: replace Abstract: Multi-bit watermarking has emerged as a promising solution for embedding imperceptible binary messages into Large Language Model (LLM)-generated tex

researcharxiv-cs-cl

XQ-MEval: A Dataset with Cross-lingual Parallel Quality for Benchmarking Translation Metrics

arXiv:2604.14934v1 Announce Type: new Abstract: Automatic evaluation metrics are essential for building multilingual translation systems. The common practice of evaluating these systems is averaging m

Agents

Young people's perceptions and recommendations for conversational generative artificial intelligence in youth mental health

arXiv:2604.13381v1 Announce Type: cross Abstract: Conversational generative artificial intelligence agents (or genAI chatbots) could benefit youth mental health, yet young people's perspectives remain

agentsarxiv-cs-ai

Your LLM Agents are Temporally Blind: The Misalignment Between Tool Use Decisions and Human Time Perception

arXiv:2510.23853v3 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly used to interact with and execute tasks in dynamic environments. However, a critical yet overlook

safetyarxiv-cs-cl

Zero-Ablation Overstates Register Content Dependence in DINO Vision Transformers

arXiv:2604.14433v1 Announce Type: new Abstract: Zero-ablation -- replacing token activations with zero vectors -- is widely used to probe token function in vision transformers. Register zeroing in DIN

Zero-Shot Retail Theft Detection via Orchestrated Vision Models: A Model-Agnostic, Cost-Effective Alternative to Trained Single-Model Systems

arXiv:2604.14846v1 Announce Type: new Abstract: Retail theft costs the global economy over 100 billion annually, yet existing AI-based detection systems require expensive custom model training on prop

Zeroth-Order Optimization at the Edge of Stability

arXiv:2604.14669v1 Announce Type: new Abstract: Zeroth-order (ZO) methods are widely used when gradients are unavailable or prohibitively expensive, including black-box learning and memory-efficient f

researcharxiv-cs-lg

3DRealHead: Few-Shot Detailed Head Avatar

arXiv:2604.13171v1 Announce Type: new Abstract: The human face is central to communication. For immersive applications, the digital presence of a person should mirror the physical reality, capturing t

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview

arXiv:2604.13244v1 Announce Type: new Abstract: The 4th Workshop on Maritime Computer Vision (MaCVi) is organized as part of CVPR 2026. This edition features five benchmark challenges with emphasis on

A 3D SAM-Based Progressive Prompting Framework for Multi-Task Segmentation of Radiotherapy-induced Normal Tissue Injuries in Limited-Data Settings

arXiv:2604.13367v1 Announce Type: new Abstract: Radiotherapy-induced normal tissue injury is a clinically important complication, and accurate segmentation of injury regions from medical images could

A Bayesian Framework for Uncertainty-Aware Explanations in Power Quality Disturbance Classification

arXiv:2604.13658v1 Announce Type: new Abstract: Advanced deep learning methods have shown remarkable success in power quality disturbance (PQD) classification. To enhance model transparency, explainab

A closer look at how large language models trust humans: patterns and biases

arXiv:2504.15801v2 Announce Type: replace Abstract: As large language models (LLMs) and LLM-based agents increasingly interact with humans in decision-making contexts, understanding the trust dynamics

researcharxiv-cs-cl

A Comparative Study of Dynamic Programming and Reinforcement Learning in Finite Horizon Dynamic Pricing

arXiv:2604.14059v1 Announce Type: cross Abstract: This paper provides a systematic comparison between Fitted Dynamic Programming (DP), where demand is estimated from data, and Reinforcement Learning (

A Complete Symmetry Classification of Shallow ReLU Networks

arXiv:2604.14037v1 Announce Type: new Abstract: Parameter space is not function space for neural network architectures. This fact, investigated as early as the 1990s under terms such as ``reverse engi

Applications

A Comprehensive Survey on Network Traffic Synthesis: From Statistical Models to Deep Learning

arXiv:2507.01976v2 Announce Type: replace-cross Abstract: Synthetic network traffic generation has emerged as a promising alternative for various data-driven applications in the networking domain. It

applicationsarxiv-cs-lg

Local Ai

A Domain-Specific Language for LLM-Driven Trigger Generation in Multimodal Data Collection

arXiv:2604.13046v1 Announce Type: cross Abstract: Data-driven systems depend on task-relevant data, yet data collection pipelines remain passive and indiscriminate. Continuous logging of multimodal se

local-aiarxiv-cs-cl

A Dynamic-Growing Fuzzy-Neuro Controller, Application to a 3PSP Parallel Robot

arXiv:2604.13763v1 Announce Type: cross Abstract: To date, various paradigms of soft-Computing have been used to solve many modern problems. Among them, a self organizing combination of fuzzy systems

A Function-Centric Perspective on Flat and Sharp Minima

arXiv:2510.12451v2 Announce Type: replace-cross Abstract: Flat minima are strongly associated with improved generalisation in deep neural networks. However, this connection has proven nuanced in recen

A ghost mechanism: An analytical model of abrupt learning in recurrent networks

arXiv:2501.02378v2 Announce Type: replace Abstract: Abrupt learning is a common phenomenon in recurrent neural networks (RNNs) trained on working memory tasks. In such cases, the networks develop tran

A High-Resolution Landscape Dataset for Concept-Based XAI With Application to Species Distribution Models

arXiv:2604.13240v1 Announce Type: new Abstract: Mapping the spatial distribution of species is essential for conservation policy and invasive species management. Species distribution models (SDMs) are

Local Ai

A KL Lens on Quantization: Fast, Forward-Only Sensitivity for Mixed-Precision SSM-Transformer Models

arXiv:2604.13440v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) on edge devices faces severe computational and memory constraints, limiting real-time processing and on-device in

local-aiarxiv-cs-lg

A Lightweight Multi-Metric No-Reference Image Quality Assessment Framework for UAV Imaging

arXiv:2604.13112v1 Announce Type: new Abstract: Reliable image quality assessment is essential in applications where large volumes of images are acquired automatically and must be filtered before furt

Local Ai

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems

arXiv:2603.25749v2 Announce Type: replace-cross Abstract: Arc-fault circuit interrupters (AFCIs) are essential for mitigating fire hazards in residential photovoltaic (PV) systems, yet achieving relia

local-aiarxiv-cs-lg

A Mechanistic Analysis of Sim-and-Real Co-Training in Generative Robot Policies

arXiv:2604.13645v1 Announce Type: cross Abstract: Co-training, which combines limited in-domain real-world data with abundant surrogate data such as simulation or cross-embodiment robot data, is widel

A Multi-Model Approach to English-Bangla Sentiment Classification of Government Mobile Banking App Reviews

arXiv:2604.13057v1 Announce Type: new Abstract: For millions of users in developing economies who depend on mobile banking as their primary gateway to financial services, app quality directly shapes f

safetyarxiv-cs-cl

A Multi-Stage Optimization Pipeline for Bethesda Cell Detection in Pap Smear Cytology

arXiv:2604.13939v1 Announce Type: new Abstract: Computer vision techniques have advanced significantly in recent years, finding diverse and impactful applications within the medical field. In this pap