Search: “models”

FruitProM-V2: Robust Probabilistic Maturity Estimation and Detection of Fruits and Vegetables

arXiv:2604.26084v1 Announce Type: cross Abstract: Accurate fruit maturity identification is essential for determining harvest timing, as incorrect assessment directly affects yield and post-harvest qu

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Agents

Hierarchical Long-Term Semantic Memory for LinkedIn's Hiring Agent

DGX agent

arXiv:2604.26197v1 Announce Type: cross Abstract: Large Language Model (LLM) agents are increasingly used in real-world products, where personalized and context-aware user interactions are essential.

agentsarxiv-cs-lg

30 Apr 2026

Hybrid Diffusion for Simultaneous Symbolic and Continuous Planning

arXiv:2509.21983v2 Announce Type: replace-cross Abstract: Constructing robots to accomplish long-horizon tasks is a long-standing challenge within artificial intelligence. Approaches using generative

Applications

Is Human-Like Text Liked by Humans? Multilingual Human Detection and Preference Against AI

arXiv:2502.11614v3 Announce Type: replace-cross Abstract: Prior studies have shown that distinguishing text generated by Large Language Models (LLMs) from human-written one is highly challenging for h

applicationsarxiv-cs-ai

Last-Layer-Centric Feature Recombination: Unleashing 3D Geometric Knowledge in DINOv3 for Monocular Depth Estimation

arXiv:2604.26454v1 Announce Type: new Abstract: Monocular depth estimation (MDE) is a fundamental yet inherently ill-posed task. Recent vision foundation models (VFMs), particularly DINO-based transfo

LLMs Generate Kitsch

arXiv:2604.25929v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to generate pictures, texts, music, videos, and other works that have traditionally required human cr

MappingEvolve: LLM-Driven Code Evolution for Technology Mapping

arXiv:2604.26591v1 Announce Type: cross Abstract: Technology mapping is a critical yet challenging stage in logic synthesis. While Large Language Models (LLMs) have been applied to generate optimizati

agentsarxiv-cs-ai

Meta-Learning and Targeted Differential Privacy to Improve the Accuracy-Privacy Trade-off in Recommendations

arXiv:2604.26390v1 Announce Type: cross Abstract: Balancing differential privacy (DP) with recommendation accuracy is a key challenge in privacy-preserving recommender systems, since DP-noise degrades

Networks of Causal Abstractions: A Sheaf-theoretic Framework

arXiv:2509.25236v3 Announce Type: replace Abstract: A core challenge in causal artificial intelligence is the principled coordination of multiple, imperfect, and subjective causal perspectives arising

agentsarxiv-cs-ai

One Voice, Many Tongues: Cross-Lingual Voice Cloning for Scientific Speech

arXiv:2604.26136v1 Announce Type: cross Abstract: Preserving a speaker's voice identity while generating speech in a different language remains a fundamental challenge in spoken language technology, p

OVGGT: O(1) Constant-Cost Streaming Visual Geometry Transformer

arXiv:2603.05959v3 Announce Type: replace Abstract: Reconstructing 3D geometry from streaming video requires continuous inference under bounded resources. Recent geometric foundation models achieve im

PBiLoss: Popularity-Aware Regularization to Improve Fairness in Graph-Based Recommender Systems

arXiv:2507.19067v2 Announce Type: replace-cross Abstract: Recommender systems based on graph neural networks (GNNs) have been proved to perform well on user-item interactions. However, they commonly s

safetyarxiv-cs-ai

Probe-then-Plan: Environment-Aware Planning for Industrial E-commerce Search

arXiv:2603.15262v2 Announce Type: replace Abstract: Modern e-commerce search is evolving to resolve complex user intents. While Large Language Models (LLMs) offer strong reasoning, existing LLM-based

safetyarxiv-cs-ai

Provable Coordination for LLM Agents via Message Sequence Charts

arXiv:2604.17612v2 Announce Type: replace-cross Abstract: Multi-agent systems built on large language models (LLMs) are difficult to reason about. Coordination errors such as deadlocks or type-mismatc

local-aiarxiv-cs-ai

Quantamination: Dynamic Quantization Leaks Your Data Across the Batch

arXiv:2604.26505v1 Announce Type: cross Abstract: Dynamic quantization emerged as a practical approach to increase the utilization and efficiency of the machine learning serving flow. Unlike static qu

Rethinking the Harmonic Loss via Non-Euclidean Distance Layers

arXiv:2603.10225v3 Announce Type: replace-cross Abstract: Cross-entropy loss has long been the standard choice for training deep neural networks, yet it suffers from interpretability limitations, unbo

Robust Alignment: Harmonizing Clean Accuracy and Adversarial Robustness in Adversarial Training

arXiv:2604.26496v1 Announce Type: new Abstract: Adversarial Training (AT) is one of the most effective methods for developing robust deep neural networks (DNNs). However, AT faces a trade-off problem

Robust Federated Learning under Adversarial Attacks via Loss-Based Client Clustering

arXiv:2508.12672v4 Announce Type: replace-cross Abstract: Federated Learning (FL) enables collaborative model training across multiple clients without sharing private data. We consider FL scenarios wh

SecMate: Multi-Agent Adaptive Cybersecurity Troubleshooting with Tri-Context Personalization

arXiv:2604.26394v1 Announce Type: cross Abstract: Recent advances in large language models and agentic frameworks have enabled virtual customer assistants (VCAs) for complex support. We present SecMat

local-aiarxiv-cs-ai

Select to Think: Unlocking SLM Potential with Local Sufficiency

arXiv:2604.26940v1 Announce Type: new Abstract: Small language models (SLMs) offer computational efficiency for scalable deployment, yet they often fall short of the reasoning power exhibited by their

local-aiarxiv-cs-cl

SkyReels-Text: Fine-Grained Font-Controllable Text Editing for Poster Design

arXiv:2511.13285v2 Announce Type: replace Abstract: Artistic design, particularly poster design, often demands rapid yet precise modification of textual content while preserving visual harmony and typ

Applications

STLGT: A Scalable Trace-Based Linear Graph Transformer for Tail Latency Prediction in Microservices

arXiv:2604.26422v1 Announce Type: cross Abstract: Accurate end-to-end tail-latency forecasting is critical for proactive SLO management in microservice systems. However, modeling long-range dependency

applicationsarxiv-cs-ai

Vibe Check: Understanding the Effects of LLM-Based Conversational Agents' Personality and Alignment on User Perceptions in Goal-Oriented Tasks

arXiv:2509.09870v2 Announce Type: replace-cross Abstract: Large language models (LLMs) enable conversational agents (CAs) to express distinctive personalities, raising new questions about how such des

safetyarxiv-cs-ai

ViBE: Visual-to-M/EEG Brain Encoding via Spatio-Temporal VAE and Distribution-Aligned Projection

arXiv:2604.26218v1 Announce Type: new Abstract: Brain encoding models not only serve to decipher how visual stimuli are transformed into neural responses, but also represent a critical step toward vis

Applications

Why Domain Matters: A Preliminary Study of Domain Effects in Underwater Object Detection

arXiv:2604.26174v1 Announce Type: new Abstract: Domain shift, where deviations between training and deployment data distributions degrade model performance, is a key challenge in underwater environmen

applicationsarxiv-cs-cv

A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards

arXiv:2505.13766v5 Announce Type: replace-cross Abstract: Software Quality Assurance (SQA) is critical for delivering reliable, secure, and efficient software products. The Software Quality Assurance

safetyarxiv-cs-cl

Tutorials

Assessment of the quantitative impact of occlusal positioning splints on temporomandibular joint conditions

arXiv:2604.25322v1 Announce Type: new Abstract: A computational method for quantitative analysis of temporomandibular joint (TMJ) configuration using occlusal positioning splints is proposed and demon

tutorialsarxiv-cs-cv

Beyond Fidelity: Semantic Similarity Assessment in Low-Level Image Processing

arXiv:2604.25408v1 Announce Type: new Abstract: Low-level image processing has long been evaluated mainly from the perspective of visual fidelity. However, with the rise of deep learning and generativ

COMPASS: COmpact Multi-channel Prior-map And Scene Signature for Floor-Plan-Based Visual Localization

arXiv:2604.25388v1 Announce Type: new Abstract: Architectural floor plans are widely available priors which contain not only geometry but also the semantic information of the environment, yet existing

Cooperate to Compete: Strategic Coordination in Multi-Agent Conquest

arXiv:2604.25088v1 Announce Type: cross Abstract: Language Model (LM)-based agents remain largely untested in mixed-motive settings where agents must leverage short-term cooperation for long-term comp

agentsarxiv-cs-cl

DEGround: An Effective Baseline for Ego-centric 3D Visual Grounding with a Homogeneous Framework

arXiv:2506.05199v3 Announce Type: replace Abstract: A core task in embodied intelligence is ego-centric 3D visual grounding. Existing methods typically adopt two-stage, heterogeneous pipelines that pa

Digitizing Nepal's Written Heritage: A Comprehensive HTR Pipeline for Old Nepali Manuscripts

arXiv:2512.17111v2 Announce Type: replace Abstract: This paper presents the first end-to-end pipeline for Handwritten Text Recognition (HTR) for Old Nepali, a historically significant but low-resource

Diverse Image Priors for Black-box Data-free Knowledge Distillation

arXiv:2604.25794v1 Announce Type: cross Abstract: Knowledge distillation (KD) represents a vital mechanism to transfer expertise from complex teacher networks to efficient student models. However, in

Dynamic Decision Learning: Test-Time Evolution for Abnormality Grounding in Rare Diseases

arXiv:2604.24972v1 Announce Type: new Abstract: Clinical abnormality grounding for rare diseases is often hindered by data scarcity, making supervised fine-tuning impractical and single-pass inference

local-aiarxiv-cs-cl

From Ambiguity to Accuracy: The Transformative Effect of Coreference Resolution on Retrieval-Augmented Generation systems

arXiv:2507.07847v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has emerged as a crucial framework in natural language processing (NLP), improving factual consistency and redu

How RL Unlocks the Aha Moment in Geometric Interleaved Reasoning

arXiv:2603.01070v2 Announce Type: replace Abstract: Solving complex geometric problems inherently requires interleaved reasoning: a tight alternation between constructing diagrams and performing logic

safetyarxiv-cs-cl

I-INR: Iterative Implicit Neural Representations

arXiv:2504.17364v4 Announce Type: replace Abstract: Implicit Neural Representations (INRs) have revolutionized signal processing and computer vision by modeling signals as continuous, differentiable f

Improving Sensing Coverage and Compliance of 3D-Printed Artificial Skins Through Multi-Modal Sensing and Soft Materials

arXiv:2604.25563v1 Announce Type: new Abstract: 3D-printed artificial skins are a scalable approach to whole-body tactile and proximity coverage, but prior implementations have been limited to unimoda

researcharxiv-cs-ro

RABC-Net: Reliability-Aware Annotation-Free Skin Lesion Segmentation for Low-Resource Dermoscopy

arXiv:2604.05594v2 Announce Type: replace Abstract: Pixel-level annotation is costly in low-resource dermoscopy. We present RABC-Net, a reliability-aware annotation-free segmentation system that combi

Time-varying Interaction Graph ODE for Dynamic Graph Representation Learning

arXiv:2604.24811v1 Announce Type: new Abstract: Graph neural Ordinary Differential Equations (ODE) combine neural ODE with the message passing mechanism of Graph Neural Networks (GNN), providing a con

Why Do LLM-based Web Agents Fail? A Hierarchical Planning Perspective

arXiv:2603.14248v2 Announce Type: replace-cross Abstract: Large language model (LLM) web agents are increasingly used for web navigation but remain far from human reliability on realistic, long-horizo

2nd of the 5th PVUW MeViS-Audio Track: ASR-SaSaSa2VA

arXiv:2604.23935v1 Announce Type: new Abstract: Audio-based video object segmentation aims to locate and segment objects in videos conditioned on audio cues, requiring precise understanding of both ap

Accelerating New Product Introduction for Visual Quality Inspection via Few-Shot Diffusion-Based Defect Synthesis

arXiv:2604.22850v1 Announce Type: new Abstract: Industrial visual inspection systems often suffer from a severe scarcity of labeled defect data, particularly during the early stages of New Product Int

Active Inference: A method for Phenotyping Agency in AI systems?

arXiv:2604.23278v1 Announce Type: new Abstract: The proliferation of agentic artificial intelligence has outpaced the conceptual tools needed to characterize agency in computational systems. Prevailin

agentsarxiv-cs-ai

AMAVA: Adaptive Motion-Aware Video-to-Audio Framework for Visually-Impaired Assistance

arXiv:2604.23909v1 Announce Type: new Abstract: Navigational aids for blind and low vision individuals struggle conveying dynamic real-world environments, leading to cognitive overload from continuous

AnemiaVision: Non-Invasive Anemia Detection via Smartphone Imagery Using EfficientNet-B3 with TrivialAugmentWide, Mixup Augmentation, and Persistent Patient History Management

arXiv:2604.22964v1 Announce Type: new Abstract: Anemia affects over one billion people globally and remains severely under-diagnosed in low-resource regions where laboratory blood tests are inaccessib

Tutorials

Beyond Experience Retrieval: Learning to Generate Utility-Optimized Structured Experience for Frozen LLMs

arXiv:2602.02556v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are largely static and often redo reasoning or repeat mistakes. Prior experience reuse typically relies on extern

tutorialsarxiv-cs-ai

Beyond Match Maximization and Fairness: Retention-Optimized Two-Sided Matching

arXiv:2602.15752v2 Announce Type: replace Abstract: On two-sided matching platforms such as online dating and recruiting, recommendation algorithms often aim to maximize the total number of matches. H

safetyarxiv-cs-lg