Search: “models”

HAVEN: Hybrid Automated Verification ENgine for UVM Testbench Synthesis with LLMs

arXiv:2604.27643v1 Announce Type: cross Abstract: Integrated Circuit (IC) verification consumes nearly 70% of the IC development cycle, and recent research leverages Large Language Models (LLMs) to au

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Safety

How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance

DGX agent

arXiv:2604.27147v1 Announce Type: cross Abstract: In generative modeling, we often wish to produce samples that maximize a user-specified reward such as aesthetic quality or alignment with human prefe

safetyarxiv-cs-ai

1 May 2026

In Line with Context: Repository-Level Code Generation via Context Inlining

arXiv:2601.00376v2 Announce Type: replace-cross Abstract: Repository-level code generation has attracted growing attention in recent years. Unlike function-level code generation, it requires the model

InterPartAbility: Text-Guided Part Matching for Interpretable Person Re-Identification

arXiv:2604.27122v1 Announce Type: new Abstract: Text-to-image person re-identification (TI-ReID) relies on natural-language text description to retrieve top matching individuals from a large gallery o

Kernelized Advantage Estimation: From Nonparametric Statistics to LLM Reasoning

arXiv:2604.28005v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have increasingly relied on reinforcement learning (RL) to improve their reasoning capabilities. Three a

safetyarxiv-cs-lg

Latent Adversarial Detection: Adaptive Probing of LLM Activations for Multi-Turn Attack Detection

arXiv:2604.28129v1 Announce Type: cross Abstract: Multi-turn prompt injection follows a known attack path -- trust-building, pivoting, escalation but text-level defenses miss covert attacks where indi

applicationsarxiv-cs-ai

Learning When to Remember: Risk-Sensitive Contextual Bandits for Abstention-Aware Memory Retrieval in LLM-Based Coding Agents

arXiv:2604.27283v1 Announce Type: cross Abstract: Large language model (LLM)-based coding agents increasingly rely on external memory to reuse prior debugging experience, repair traces, and repository

LLM-based User Profile Management for Recommender System

arXiv:2502.14541v3 Announce Type: replace Abstract: The rapid advancement of Large Language Models (LLMs) has opened new opportunities in recommender systems by enabling zero-shot recommendation witho

applicationsarxiv-cs-cl

LLM Biases

arXiv:2604.26960v1 Announce Type: cross Abstract: Transformer-based agentic AI is rapidly being deployed on major platforms to help users shop, watch, and navigate content with less effort. While thes

LM-CartSeg: Automated Segmentation of Lateral and Medial Cartilage and Subchondral Bone for Radiomics Analysis

arXiv:2512.03449v3 Announce Type: replace Abstract: Background and Objective: Radiomics of knee MRI requires robust, anatomically meaningful regions of interest (ROIs) that jointly capture cartilage a

Hardware

MARS: Efficient, Adaptive Co-Scheduling for Heterogeneous Agentic Systems

arXiv:2604.26963v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as the execution core of autonomous agents rather than as standalone text generators. Agentic w

hardwarearxiv-cs-lg

Normativity and Productivism: Ableist Intelligence? A Degrowth Analysis of AI Sign Language Translation Tools for Deaf People

arXiv:2604.28125v1 Announce Type: new Abstract: Sign languages, of any geographical or accentual variation, understandably face continuous scrutiny under the ever present popularity of verbal dictatio

Performance-Driven QUBO for Recommender Systems on Quantum Annealers

arXiv:2410.15272v3 Announce Type: replace-cross Abstract: Quantum annealers offer a promising hardware platform for solving combinatorial optimization problems, especially those formulated as Quadrati

PPA-Plan: Proactive Pitfall Avoidance for Reliable Planning in Long-Context LLM Reasoning

arXiv:2601.11908v2 Announce Type: replace Abstract: Large language models (LLMs) struggle with reasoning over long contexts where relevant information is sparsely distributed. Although plan-and-execut

Tutorials

Predicting Atomistic Transitions with Transformers

arXiv:2603.06526v2 Announce Type: replace-cross Abstract: Accurate knowledge of the atomistic transition pathways in materials and material surfaces is crucial for many material science problems. Howe

tutorialsarxiv-cs-lg

Tutorials

Reasoning over Object Descriptions Improves Coreference Resolution in Task-Based Dialogue Systems

arXiv:2604.27850v1 Announce Type: new Abstract: Task-based dialogue systems assist users in achieving specific goals, such as executing actions or retrieving information, through natural language inte

tutorialsarxiv-cs-cl

RHyVE: Competence-Aware Verification and Phase-Aware Deployment for LLM-Generated Reward Hypotheses

arXiv:2604.28056v1 Announce Type: new Abstract: Large language models (LLMs) make reward design in reinforcement learning substantially more scalable, but generated rewards are not automatically relia

Safe Bilevel Delegation (SBD): A Formal Framework for Runtime Delegation Safety in Multi-Agent Systems

arXiv:2604.27358v1 Announce Type: new Abstract: As large language model (LLM) agents are deployed in high-stakes environments, the question of how safely to delegate subtasks to specialized sub-agents

Shuffling-Aware Optimization for Private Vector Mean Estimation

arXiv:2604.28032v1 Announce Type: new Abstract: We study d-dimensional unbiased mean estimation in the single-message shuffle model, where each user sends a single privatized message and the analyzer

researcharxiv-cs-lg

Splitting Assumption-Based Argumentation Frameworks

arXiv:2604.27964v1 Announce Type: new Abstract: Assumption-Based Argumentation (ABA) is a well-established formalism for modelling and reasoning over debates, with a wide range of applications. Howeve

SQuadGen: Generating Simple Quad Layouts via Chart Distance Fields

arXiv:2604.27329v1 Announce Type: cross Abstract: 3D shapes from scanning, reconstruction, or AI-generated content often lack simple quad mesh layouts -- critical for efficient editing and modeling. E

Why Mean Pooling Works: Quantifying Second-Order Collapse in Text Embeddings

arXiv:2604.27398v1 Announce Type: new Abstract: For constructing text embeddings, mean pooling, which averages token embeddings, is the standard approach. This paper examines whether mean pooling actu

A Multimodal and Explainable Machine Learning Approach to Diagnosing Multi-Class Ejection Fraction from Electrocardiograms

arXiv:2604.25942v1 Announce Type: new Abstract: Left ventricular ejection fraction (LVEF) assessment depends on echocardiography, limiting access in primary care and resource-constrained settings. We

applicationsarxiv-cs-lg

A Multimodal Pre-trained Network for Integrated EEG-Video Seizure Detection

arXiv:2604.26379v1 Announce Type: new Abstract: Reliable seizure detection in mouse models is essential for preclinical epilepsy research, yet manual review of synchronized video-EEG recordings is lab

safetyarxiv-cs-cv

Hardware

AdaFRUGAL: Adaptive Memory-Efficient Training with Dynamic Control

arXiv:2601.11568v2 Announce Type: replace-cross Abstract: Training Large Language Models (LLMs) is highly memory-intensive due to optimizer state overhead. The FRUGAL framework mitigates this with gra

hardwarearxiv-cs-ai

Adversarial Robustness of NTK Neural Networks

arXiv:2604.25965v1 Announce Type: cross Abstract: Deep learning models are widely deployed in safety-critical domains, but remain vulnerable to adversarial attacks. In this paper, we study the adversa

safetyarxiv-cs-lg

Are Data Augmentation and Segmentation Always Necessary? Insights from COVID-19 X-Rays and a Methodology Thereof

arXiv:2604.26437v1 Announce Type: new Abstract: Purpose: Rapid and reliable diagnostic tools are crucial for managing respiratory diseases like COVID-19, where chest X-ray analysis coupled with artifi

Asynchronous Federated Unlearning with Invariance Calibration for Medical Imaging

arXiv:2604.26809v1 Announce Type: new Abstract: Federated Unlearning (FU) is an emerging paradigm in Federated Learning (FL) that enables participating clients to fully remove their contributions from

researcharxiv-cs-lg

Benchmarking PyCaret AutoML Against BiLSTM for Fine-Grained Emotion Classification: A Comparative Study on 20-Class Emotion Detection

arXiv:2604.26310v1 Announce Type: new Abstract: Fine-grained emotion classification, which identifies specific emotional states such as happiness, anger, sadness, and fear, remains a challenging task

CacheRAG: A Semantic Caching System for Retrieval-Augmented Generation in Knowledge Graph Question Answering

arXiv:2604.26176v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) has significantly advanced Knowledge Graph Question Answerin

Co-Learning Port-Hamiltonian Systems and Optimal Energy-Shaping Control

arXiv:2604.26172v1 Announce Type: cross Abstract: We develop a physics-informed learning framework for energy-shaping control of port-Hamiltonian (pH) systems from trajectory data. The proposed approa

Data Balancing Strategies: A Systematic Survey of Resampling and Augmentation Methods

arXiv:2505.13518v2 Announce Type: replace-cross Abstract: Imbalanced datasets, where one class significantly outnumbers others, remain a persistent challenge in machine learning, often biasing predict

Local Ai

DUAL-BLADE: Dual-Path NVMe-Direct KV-Cache Offloading for Edge LLM Inference

arXiv:2604.26557v1 Announce Type: cross Abstract: The increasing deployment of Large Language Model (LLM) inference on edge AI systems demands efficient execution under tight memory budgets. A key cha

local-aiarxiv-cs-ai

Tutorials

Efficient Traffic Forecasting on Large-Scale Road Network by Regularized Adaptive Graph Convolution

arXiv:2506.07179v2 Announce Type: replace-cross Abstract: Traffic prediction is a critical task in spatial-temporal forecasting with broad applications in travel planning and urban management. To mode

tutorialsarxiv-cs-ai

Evaluation Revisited: A Taxonomy of Evaluation Concerns in Natural Language Processing

arXiv:2604.25923v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have prompted a growing body of work that questions the methodology of prevailing evaluation practices.

FASTER: Rethinking Real-Time Flow VLAs

arXiv:2603.19199v2 Announce Type: replace-cross Abstract: Real-time execution is crucial for deploying Vision-Language-Action (VLA) models in the physical world. Existing asynchronous inference method

applicationsarxiv-cs-cv

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

Agents

Hierarchical Long-Term Semantic Memory for LinkedIn's Hiring 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

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

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

Agents

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

researcharxiv-cs-lg

Agents

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

Local Ai

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

local-aiarxiv-cs-cv

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