Search: “papers”

Transferability for General Reasoning: An Automated Curriculum for Multi-Domain RLVR

arXiv:2606.25178v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has been extended from single-domain training to multi-domain reasoning suites spanning mathematic

safetyarxiv-cs-ai

Transferable Attack against Face Swapping in an Extended Space

DGX agent

arXiv:2606.25376v1 Announce Type: new Abstract: Although deep Face Swapping (FS) models may benefit the entertainment industry, they pose severe threats to privacy and security. Existing protections,

researcharxiv-cs-cv

25 Jun 2026

TRUSTMEM: Learning Trustworthy Memory Consolidation for LLM Agents with Long-Term Memory

arXiv:2606.25161v1 Announce Type: new Abstract: Large language model (LLM) agents rely on long-term memory to support extended interactions and personalized assistance beyond finite context windows. E

Type Checking Project Haystack Grids using JSON Schema and Pydantic

arXiv:2606.24891v1 Announce Type: cross Abstract: Ontologies enable scalable energy services in buildings by supporting interoperability and automation. Project Haystack is a building ontology that is

Variable Bound Tightening for Nash Equilibrium Computation in Multiplayer Imperfect-Information Games

arXiv:2606.25997v1 Announce Type: cross Abstract: There has been significant recent progress in algorithms for approximation of Nash equilibrium in large two-player zero-sum imperfect-information game

Variational Autoencoder Layer

arXiv:2606.25900v1 Announce Type: new Abstract: Variational Autoencoders (VAEs) belong to a family of autoencoders with probabilistic properties, making them well suited for generating data by produci

researcharxiv-cs-lg

Verifiable Manifest Signing and Transparency Enforcement for Secure MCP-Based LLM Pipelines

arXiv:2601.23132v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in tool-driven environments such as healthcare analytics, financial systems, retrieval-

Video models are hard. Real-time video models are even harder. Loved this breakdown by @itunpredictable on how we productionized Runway Char…

model-releasescristobal-valenzuela--x

Video models are hard. Real-time video models are even harder. Loved this breakdown by @itunpredictable on how we productionized Runway Characters, our real-time interactive avatar model. We had to fi

When Does Synthetic Data Augmentation Improve Score-Based Imbalanced Classification?

arXiv:2606.26053v1 Announce Type: cross Abstract: Synthetic data augmentation is widely used to mitigate class imbalance, but its theoretical effects on score-based classification remain poorly unders

safetyarxiv-cs-lg

A Benchmark for Hallucination Detection in VLMs for Gastrointestinal Endoscopy

arXiv:2606.24115v1 Announce Type: cross Abstract: Vision-language models (VLMs) are prone to hallucination, which remains a major barrier to their safe deployment in clinical practice. To date, most h

A Hybrid Quantum-Classical Approach for Melt Pool Prediction in Laser Powder Bed Fusion

model-releasesarxiv-cs-lg

arXiv:2606.23719v1 Announce Type: cross Abstract: Laser powder bed fusion (LPBF) is a promising additive manufacturing technique that suffers from quality assurance concerns. Predicting melt pools fro

A novel Framework for Open-Vocabulary Multi-Object Recognition using CLIP

arXiv:2603.05962v2 Announce Type: replace Abstract: To address the limitations of existing open-vocabulary object recognition methods, including high system complexity, substantial training costs, and

researcharxiv-cs-cv

A Survey on Federated Causal Discovery and Inference

arXiv:2606.23741v1 Announce Type: cross Abstract: Causal reasoning, which encompasses the discovery of causal structures and the inference of causal effects, is fundamental to data-driven decision mak

A Synthetic Reliability-Aware PINN Benchmark for Offshore Wind Turbine Support-Structure Monitoring with Bayesian Inverse Identification

model-releasesarxiv-cs-cl

arXiv:2606.24176v1 Announce Type: new Abstract: Reliable structural health monitoring (SHM) of offshore wind turbine (OWT) support structures requires fast state estimation from sparse measurements. R

Local Ai

Accuracy and Satisfaction in Multi-Turn LLM Dialogues for NFR Assessment

arXiv:2606.24834v1 Announce Type: new Abstract: LLM-based dialogue assistants have become mainstream tools for software developers, yet current evaluation benchmarks focus exclusively on functional co

local-aiarxiv-cs-ai

Applications

Adaptive Machine Learning Framework for UAV Trajectory Optimization in O-RAN

arXiv:2606.24483v1 Announce Type: cross Abstract: The deployment of unmanned aerial vehicles (UAV) as open radio units (O-RUs) in 6G cellular systems presents a promising opportunity to achieve scalab

applicationsarxiv-cs-ai

Agentic AI for Bilevel Long-Term Optimization of Policy-Driven Physical Layer Systems

arXiv:2606.24416v1 Announce Type: new Abstract: Network operators' changing policies, service requirements, and stringent real-time constraints render existing methods designed with fixed objectives a

safetyarxiv-cs-ai

Agentic Collaborative Cognition for Zero-Shot 3D Understanding

arXiv:2606.24649v1 Announce Type: new Abstract: Recent advancements have explored agentic zero-shot 3D understanding by reformulating it as video keyframe understanding with Multimodal Large Language

agentsarxiv-cs-cv

AgentRivet: an automated system for producing Rivet routines from journal publications

arXiv:2606.13535v3 Announce Type: replace-cross Abstract: Particle physics collider experiments provide Rivet routines as part of the analysis preservation strategy for model-independent measurements.

agentsarxiv-cs-ai

AI-Driven Predictive Maintenance with Environmental Context Integration for Connected Vehicles: Simulation, Benchmarking, and Field Validation

arXiv:2603.13343v3 Announce Type: replace-cross Abstract: Predictive maintenance for connected vehicles offers the potential to reduce unexpected breakdowns and improve fleet reliability, but most exi

AI-PAVE-Br: Leveraging Large Language Models for Enhanced Product Attribute Value Extraction through a Golden Set Approach

arXiv:2606.24655v1 Announce Type: cross Abstract: The explosive growth and complexity of product data within the dynamic Brazilian e-commerce landscape demand robust and specialized methods for struct

An LLM-based Two-Stage Transformer Framework for Cross-Domain Bearing Fault Diagnosis with Limited Data

arXiv:2606.24459v1 Announce Type: cross Abstract: Bearing fault diagnosis faces critical challenges when dataset heterogeneity, operating condition variations, and limited labeled data occur simultane

safetyarxiv-cs-cl

Are We Ready For An Agent-Native Memory System?

model-releasesarxiv-cs-cl

arXiv:2606.24775v1 Announce Type: new Abstract: Memory for large language model (LLM) agents has rapidly evolved from simple retrieval-augmented mechanisms into a data management system that supports

ASALT: Adaptive State Alignment for Lateral Transfer in Multi-agent Reinforcement Learning

arXiv:2606.24601v1 Announce Type: new Abstract: Multi-agent reinforcement learning (MARL) addresses the problem of training multiple agents that pursue collaborative, competitive, or mixed objectives.

Aspect-Based Sentiment Evolution and its Correlation with Review Rounds in Multi-Round Peer Reviews: A Deep Learning Approach

arXiv:2606.24188v1 Announce Type: new Abstract: Mining sentiment information from the textual content of peer review comments offers valuable insights into the scientific evaluation process. However,

Assessing Distribution Shift in Human Activity Recognition for Domain Generalization

arXiv:2606.24781v1 Announce Type: new Abstract: While the field of Human Activity Recognition (HAR) continues to draw interest from researchers and advance in important ways, some key challenges remai

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models

arXiv:2606.24152v1 Announce Type: new Abstract: Existing literature claims that video generation essentially is world modelling. On the one hand, the claim is productive because it pushes generative A

agentsarxiv-cs-cv

BioMedArena: An Open-source Toolkit for Building and Evaluating Biomedical Deep Research Agents

arXiv:2605.06177v2 Announce Type: replace Abstract: Reproducing and comparing deep research agents today is hard: the same backbone evaluated on the same benchmark can report different accuracies acro

Blockwise Policy-Drift Gating for On-Policy Distillation

arXiv:2606.24084v1 Announce Type: cross Abstract: On-policy distillation (OPD) trains a student policy using teacher signals computed on trajectories sampled by the student itself. Recent work shows t

Boosting Text-Driven Video Segmentation via Geometry-Aware Distillation

arXiv:2606.24464v1 Announce Type: new Abstract: Text-driven Referring Video Object Segmentation (RVOS) aims to locate and segment target objects in videos given natural language. However, existing mod

safetyarxiv-cs-cv

CanadaFireSat: Toward high-resolution wildfire forecasting with multiple modalities

model-releasesarxiv-cs-cv

arXiv:2506.08690v3 Announce Type: replace Abstract: Canada experienced in 2023 one of the most severe wildfire seasons in recent history, causing damage across ecosystems, destroying communities, and

Compact Object-Level Representations with Open-Vocabulary Understanding for Indoor Visual Relocalization

model-releasesarxiv-cs-cv

arXiv:2606.24767v1 Announce Type: new Abstract: Indoor visual relocalization plays a critical role in emerging spatial and embodied AI applications. However, prior research was predominantly devoted t

ComputeFHE: A Privacy-Preserving General-Purpose Computation Library

arXiv:2606.24379v1 Announce Type: cross Abstract: Fully Homomorphic Encryption (FHE) enables computations to be performed directly on encrypted data while preserving data confidentiality. However, its

Tutorials

Coordinate-Queryable Neural Field Reconstruction for EEG Spatial Super-Resolution with Unseen-Electrode Generation

arXiv:2606.23707v1 Announce Type: cross Abstract: EEG spatial super-resolution (EEGSR) in real deployments is challenged by random channel missingness, unstable electrode quality, and changing visible

tutorialsarxiv-cs-ai

Cross-Dataset, Age, and Gender Generalization: A Comprehensive Analysis of Fine-Tuning Strategies for Low-Resource Children's ASR

arXiv:2606.19791v2 Announce Type: replace-cross Abstract: The challenge associated with recognizing dysarthric speech primarily arises from pronounced acoustic variability attributed to impaired artic

Decentralized Coordination of Autonomous Traffic Through Advanced Air Mobility Corridors

arXiv:2606.23832v1 Announce Type: cross Abstract: The use of dedicated corridors for Advanced Air Mobility (AAM) traffic is one of the most commonly proposed pathways to integrating them into existing

agentsarxiv-cs-ai

Applications

Decentralized Pose Graph Riemannian Optimization for Object-based Multi-Robot SLAM

arXiv:2606.24489v1 Announce Type: new Abstract: Pose graph optimization (PGO) is a key back-end component for state estimation in networked multi-robot simultaneous localization and mapping (SLAM). In

applicationsarxiv-cs-ro

Local Ai

Decoherence as Defence and the Magnitude of Noise Regularisation: A Rigorous N -Qubit Theory of Stochastic Quantum Neural Networks for Adversarially Robust Network Intrusion Detection

arXiv:2606.24219v1 Announce Type: new Abstract: Stochastic quantum neural networks (SQNNs) encode neuronal activations as qubits, synaptic topology as entanglement, and neural noise through a Lindblad

local-aiarxiv-cs-cl

Does My Embedding Reflect That A = B? Evaluating Mathematical Equivalence in Embedding Models

arXiv:2606.23959v1 Announce Type: new Abstract: Because mathematics is highly abstract, a single statement can take very different forms depending on what subfield it is framed in. There are many exam

DriveStack-VLA: Render-Teacher Alignment for BEV-Based DeepStack Vision-Language-Action Model

arXiv:2606.24051v1 Announce Type: new Abstract: Vision-Language-Action driving models convert a pretrained Vision-Language Model into a driving policy, allowing them to use world knowledge and follow

safetyarxiv-cs-cv

EERLoss: A Novel Loss Function for Training Deep Biometric Models. A Case Study in Keystroke Dynamics

model-releasesarxiv-cs-cv

arXiv:2606.24586v1 Announce Type: new Abstract: Deep learning approaches to biometric verification are commonly trained by optimizing indirect objectives, creating a misalignment between the optimizat

Ensemble Feature Selection and Harris Hawks Optimization for Explainable Mental Health Risk Prediction in Female Sex Workers

arXiv:2606.24047v1 Announce Type: new Abstract: One of the significant mental health issues affecting female sex workers (FSWs) is mental disorders, especially depression. Exposure to violence, stigma

agentsarxiv-cs-ai

ErrorLLM: Modeling SQL Errors for Text-to-SQL Refinement

arXiv:2603.03742v2 Announce Type: replace Abstract: Despite the remarkable performance of large language models (LLMs) in text-to-SQL (SQL generation), correctly producing SQL queries remains challeng

Local Ai

ESBMC-GraphPLC: Formal Verification of Graphical PLCopen XML Ladder Diagram Programs Using SMT-Based Model Checking

arXiv:2606.18941v3 Announce Type: replace-cross Abstract: PLCopen XML defines two encoding formats for IEC 61131-3 Ladder Diagram programs: a textual encoding using elements, and a graphical encoding

local-aiarxiv-cs-cl

ESBMC-PLC+: A Unified IEC~61131-3 Formal Verification Framework as a PLCverif Successor

model-releasesarxiv-cs-cl

arXiv:2606.23870v1 Announce Type: cross Abstract: PLCverif is the most mature open-source platform for PLC formal verification, developed at CERN and in production use since 2019. Yet it has two funda

Exact Schur-Sylvester Dimensionality Reductions for Non-Smooth Stochastic Complexity and Manifold Sampling

arXiv:2606.23867v1 Announce Type: new Abstract: The exact computation of the Normalized Maximum Likelihood (NML) codelength for regular non-smooth estimators (e.g., Lasso) has been historically limite

researcharxiv-cs-lg

Experiments with Optimal Model Trees

model-releasesarxiv-cs-lg

arXiv:2503.12902v4 Announce Type: replace Abstract: Model trees provide an appealing way to perform interpretable machine learning for both classification and regression problems. In contrast to ``cla

Exploring Dualistic Meta-Learning to Enhance Domain Generalization in Open Set Scenarios

arXiv:2606.23758v1 Announce Type: cross Abstract: Domain generalization learns from multiple source domains to generalize to unseen target domains. However, it often neglects the realistic case of lab