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When LoRA Betrays: Backdooring Text-to-Image Models by Masquerading as Benign Adapters

arXiv:2602.21977v4 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has emerged as a leading technique for efficiently fine-tuning text-to-image diffusion models, and its widespread adoptio

researcharxiv-cs-cv

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Safety

When Models Outthink Their Safety: Unveiling and Mitigating Self-Jailbreak in Large Reasoning Models

DGX agent

arXiv:2510.21285v4 Announce Type: replace Abstract: Large Reasoning Models (LRMs) achieve strong performance on complex multi-step reasoning, yet they still exhibit severe safety failures such as harm

safetyarxiv-cs-ai

27 Apr 2026

Agents

When Quotes Crumble: Detecting Transient Mechanical Liquidity Erosion in Limit Order Books

arXiv:2604.21993v1 Announce Type: new Abstract: We study the detection of transient liquidity erosion ('crumbling quotes') in electronic limit order books, where observable quote deterioration may ref

agentsarxiv-cs-lg

Where Should LoRA Go? Component-Type Placement in Hybrid Language Models

arXiv:2604.22127v1 Announce Type: new Abstract: Hybrid language models that interleave attention with recurrent components are increasingly competitive with pure Transformers, yet standard LoRA practi

researcharxiv-cs-cl

Who Audits the Auditor? Tamper-Proof Fraud Detection with Blockchain-Anchored Explainable ML

arXiv:2604.22096v1 Announce Type: cross Abstract: In enterprise fraud detection, model accuracy alone is insufficient when insiders can tamper with audit logs or bypass approval workflows. Real-world

applicationsarxiv-cs-lg

Wiggle and Go! System Identification for Zero-Shot Dynamic Rope Manipulation

arXiv:2604.22102v1 Announce Type: cross Abstract: Many robotic tasks are unforgiving; a single mistake in a dynamic throw can lead to unacceptable delays or unrecoverable failure. To mitigate this, we

Zero-Shot Morphological Discovery in Low-Resource Bantu Languages via Cross-Lingual Transfer and Unsupervised Clustering

arXiv:2604.22723v1 Announce Type: cross Abstract: We present a method for discovering morphological features in low-resource Bantu languages by combining cross-lingual transfer learning with unsupervi

researcharxiv-cs-cl

2L-LSH: A Locality-Sensitive Hash Function-Based Method For Rapid Point Cloud Indexing

arXiv:2604.21442v1 Announce Type: new Abstract: The development of 3D scanning technology has enabled the acquisition of massive point cloud models with diverse structures and large scales, thereby pr

researcharxiv-cs-cv

Agents

A Bayesian Reasoning Framework for Robotic Systems in Autonomous Casualty Triage

arXiv:2604.21568v1 Announce Type: new Abstract: Autonomous robots deployed in mass casualty incidents (MCI) face the challenge of making critical decisions based on incomplete and noisy perceptual dat

agentsarxiv-cs-ro

Agents

A Case Study in Recovery of Drones using Discrete-Event Systems

arXiv:2604.21740v1 Announce Type: cross Abstract: Discrete-event systems and supervisory control theory provide a rigorous framework for specifying correct-by-construction behavior. However, their pra

agentsarxiv-cs-ro

A Compact Peristaltic Pump Based on Magneto-Elastic Hysteresis with Single Pneumatic Control

arXiv:2604.21729v1 Announce Type: new Abstract: Pumping fluids is fundamental to a wide range of industrial, environmental, and biomedical applications. Among various pumping mechanisms, peristaltic p

researcharxiv-cs-ro

Tutorials

A Comprehensive Guide to Differential Privacy: From Theory to User Expectations

arXiv:2509.03294v3 Announce Type: replace-cross Abstract: The increasing availability of personal data has enabled significant advances in fields such as machine learning, healthcare, and cybersecurit

tutorialsarxiv-cs-ai

A Deep U-Net Framework for Flood Hazard Mapping Using Hydraulic Simulations of the Wupper Catchment

arXiv:2604.21028v1 Announce Type: cross Abstract: The increasing frequency and severity of global flood events highlights the need for the development of rapid and reliable flood prediction tools. Thi

A Deployable Embodied Vision-Language Navigation System with Hierarchical Cognition and Context-Aware Exploration

arXiv:2604.21363v1 Announce Type: new Abstract: Bridging the gap between embodied intelligence and embedded deployment remains a key challenge in intelligent robotic systems, where perception, reasoni

applicationsarxiv-cs-ro

A Dynamic Framework for Grid Adaptation in Kolmogorov-Arnold Networks

arXiv:2601.18672v3 Announce Type: replace Abstract: Kolmogorov-Arnold Networks (KANs) have recently demonstrated promising potential in scientific machine learning, partly due to their capacity for gr

A Green-Integral-Constrained Neural Solver with Stochastic Physics-Informed Regularization

arXiv:2604.21411v1 Announce Type: new Abstract: Standard physics-informed neural networks (PINNs) struggle to simulate highly oscillatory Helmholtz solutions in heterogeneous media because pointwise m

A Hybridizable Neural Time Integrator for Stable Autoregressive Forecasting

arXiv:2604.21101v1 Announce Type: new Abstract: For autoregressive modeling of chaotic dynamical systems over long time horizons, the stability of both training and inference is a major challenge in b

A-IC3: Learning-Guided Adaptive Inductive Generalization for Hardware Model Checking

arXiv:2604.21688v1 Announce Type: cross Abstract: The IC3 algorithm represents the state-of-the-art (SOTA) hardware model checking technique, owing to its robust performance and scalability. A signifi

A Kernel Nonconformity Score for Multivariate Conformal Prediction

arXiv:2604.21595v1 Announce Type: cross Abstract: Multivariate conformal prediction requires nonconformity scores that compress residual vectors into scalars while preserving certain implicit geometri

A Metamorphic Testing Approach to Diagnosing Memorization in LLM-Based Program Repair

arXiv:2604.21579v1 Announce Type: cross Abstract: LLM-based automated program repair (APR) techniques have shown promising results in reducing debugging costs. However, prior results can be affected b

A Multi-Stage Warm-Start Deep Learning Framework for Unit Commitment

arXiv:2604.21891v1 Announce Type: cross Abstract: Maintaining instantaneous balance between electricity supply and demand is critical for reliability and grid instability. System operators achieve thi

A Multimodal Text- and Graph-Based Approach for Open-Domain Event Extraction from Documents

arXiv:2604.21885v1 Announce Type: cross Abstract: Event extraction is essential for event understanding and analysis. It supports tasks such as document summarization and decision-making in emergency

A Probabilistic Framework for Improving Dense Object Detection in Underwater Image Data via Annealing-Based Data Augmentation

arXiv:2604.21198v1 Announce Type: new Abstract: Object detection models typically perform well on images captured in controlled environments with stable lighting, water clarity, and viewpoint, but the

applicationsarxiv-cs-cv

A Quantale-Weakness Route to P neq NP via CD Evidence Normalization and Gauge-Buffered Locked Ensembles

arXiv:2510.08814v2 Announce Type: replace-cross Abstract: We present a proof architecture for (P neq NP) based on an upper--lower clash in polytime-capped conditional description length. We construct

A Replicable Robotics Awareness Method Using LLM-Enabled Robotics Interaction: Evidence from a Corporate Challenge

arXiv:2604.21377v1 Announce Type: new Abstract: Large language models are increasingly being explored as interfaces between humans and robotic systems, yet there remains limited evidence on how such t

researcharxiv-cs-ro

A Scale-Adaptive Framework for Joint Spatiotemporal Super-Resolution with Diffusion Models

arXiv:2604.21903v1 Announce Type: cross Abstract: Deep-learning video super-resolution has progressed rapidly, but climate applications typically super-resolve (increase resolution) either space or ti

A single algorithm for both restless and rested rotting bandits

arXiv:2604.21432v1 Announce Type: cross Abstract: In many application domains (e.g., recommender systems, intelligent tutoring systems), the rewards associated to the actions tend to decrease over tim

Safety

A Survey of Legged Robotics in Non-Inertial Environments: Past, Present, and Future

arXiv:2604.20990v1 Announce Type: new Abstract: Legged robots have demonstrated remarkable agility on rigid, stationary ground, but their locomotion reliability remains limited in non-inertial environ

safetyarxiv-cs-ro

A Systematic Review and Taxonomy of Reinforcement Learning-Model Predictive Control Integration for Linear Systems

arXiv:2604.21030v1 Announce Type: cross Abstract: The integration of Model Predictive Control (MPC) and Reinforcement Learning (RL) has emerged as a promising paradigm for constrained decision-making

A temporal deep learning framework for calibration of low-cost air quality sensors

arXiv:2604.21527v1 Announce Type: new Abstract: Low-cost air quality sensors (LCS) provide a practical alternative to expensive regulatory-grade instruments, making dense urban monitoring networks pos

A Tendon-Driven Wrist Abduction-Adduction Joint Improves Performance of a 5 DoF Upper Limb Exoskeleton -- Implementation and Experimental Evaluation

arXiv:2604.20898v1 Announce Type: new Abstract: Wrist function is essential in performing activities of daily living (ADLs). However, there is limited experimental evidence on the functional impact of

researcharxiv-cs-ro

A-THENA: Early Intrusion Detection for IoT with Time-Aware Hybrid Encoding and Network-Specific Augmentation

arXiv:2604.21623v1 Announce Type: cross Abstract: The proliferation of Internet of Things (IoT) devices has significantly expanded attack surfaces, making IoT ecosystems particularly susceptible to so

Absorber LLM: Harnessing Causal Synchronization for Test-Time Training

arXiv:2604.20915v1 Announce Type: cross Abstract: Transformers suffer from a high computational cost that grows with sequence length for self-attention, making inference in long streams prohibited by

Accelerating Vision Transformers with Adaptive Patch Sizes

arXiv:2510.18091v2 Announce Type: replace-cross Abstract: Vision Transformers (ViTs) partition input images into uniformly sized patches regardless of their content, resulting in long input sequence l

Accurate predictive model of band gap with selected important features based on explainable machine learning

arXiv:2503.04492v3 Announce Type: replace-cross Abstract: In the rapidly advancing field of materials informatics, nonlinear machine learning models have demonstrated exceptional predictive capabiliti

Achieving the Kesten-Stigum bound in the non-uniform hypergraph stochastic block model

arXiv:2604.20907v1 Announce Type: cross Abstract: We study the community detection problem in the non-uniform hypergraph stochastic block model (HSBM), where hyperedges of varying sizes coexist. This

Active Data

arXiv:2604.21044v1 Announce Type: new Abstract: In some complex domains, certain problem-specific decompositions can provide advantages over monolithic designs by enabling comprehension and specificat

Active Learning for Planet Habitability Classification under Extreme Class Imbalance

arXiv:2602.23666v2 Announce Type: replace-cross Abstract: The increasing size and heterogeneity of exoplanet catalogs have made systematic habitability assessment challenging, particularly given the e

Adaptive Defense Orchestration for RAG: A Sentinel-Strategist Architecture against Multi-Vector Attacks

arXiv:2604.20932v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) systems are increasingly deployed in sensitive domains such as healthcare and law, where they rely on private, do

Tutorials

Adaptive Instruction Composition for Automated LLM Red-Teaming

arXiv:2604.21159v1 Announce Type: cross Abstract: Many approaches to LLM red-teaming leverage an attacker LLM to discover jailbreaks against a target. Several of them task the attacker with identifyin

tutorialsarxiv-cs-ai

Safety

Adaptive Moments are Surprisingly Effective for Plug-and-Play Diffusion Sampling

arXiv:2603.16797v2 Announce Type: replace-cross Abstract: Guided diffusion sampling relies on approximating often intractable likelihood scores, which introduces significant noise into the sampling dy

safetyarxiv-cs-cv

Adaptive Soft Error Protection for Neural Network Processing

arXiv:2407.19664v3 Announce Type: replace Abstract: Previous research on selective protection for neural network components typically exploits only static vulnerability differences. Although these met

Adaptive Test-Time Compute Allocation with Evolving In-Context Demonstrations

arXiv:2604.21018v1 Announce Type: new Abstract: While scaling test-time compute can substantially improve model performance, existing approaches either rely on static compute allocation or sample from

Addressing divergent representations from causal interventions on neural networks

arXiv:2511.04638v5 Announce Type: replace-cross Abstract: A common approach to mechanistic interpretability is to causally manipulate model representations via targeted interventions in order to under

Addressing Image Authenticity When Cameras Use Generative AI

arXiv:2604.21879v1 Announce Type: cross Abstract: The ability of generative AI (GenAI) methods to photorealistically alter camera images has raised awareness about the authenticity of images shared on

ADS-POI: Agentic Spatiotemporal State Decomposition for Next Point-of-Interest Recommendation

arXiv:2604.20846v1 Announce Type: cross Abstract: Next point-of-interest (POI) recommendation requires modeling user mobility as a spatiotemporal sequence, where different behavioral factors may evolv

Adversarial Evasion in Non-Stationary Malware Detection: Minimizing Drift Signals through Similarity-Constrained Perturbations

arXiv:2604.21310v1 Announce Type: cross Abstract: Deep learning has emerged as a powerful approach for malware detection, demonstrating impressive accuracy across various data representations. However

applicationsarxiv-cs-ai

AEL: Agent Evolving Learning for Open-Ended Environments

arXiv:2604.21725v1 Announce Type: cross Abstract: LLM agents increasingly operate in open-ended environments spanning hundreds of sequential episodes, yet they remain largely stateless: each task is s