arXiv AI
Jun 8
FreeAnimate: Training-Free Human Image Animation with Preview-Guided Denoising
arXiv:2606. 06885v1 Announce Type: cross Abstract: Human Image Animation has seen significant advancements, primarily driven by diffusion models.
AI safety and alignment
Alignment, interpretability, red-teaming, bias and privacy: the research on what these systems do when they misbehave.
arXiv Machine Learning
Jun 8
The Capacity of Information-Theoretic Secure Aggregation in Federated Learning
arXiv:2606. 07277v1 Announce Type: cross Abstract: Secure aggregation allows a server to aggregate users' local updates while preserving update privacy.
arXiv AI
Jun 8
It's a TRAP! Task-Redirecting Agent Persuasion Benchmark for Web Agents
arXiv:2512. 23128v2 Announce Type: replace-cross Abstract: Web-based agents powered by large language models are increasingly used for tasks such as email management or professional networking.
arXiv Machine Learning
Jun 8
Uncertainty-Guided Label Rebalancing for CPS Safety Monitoring
arXiv:2603. 25670v3 Announce Type: replace Abstract: Safety monitoring is essential for Cyber-Physical Systems (CPSs).
arXiv Machine Learning
Jun 8
Explaining Unsupervised Disease Staging in Huntington's Disease: Insights into Model Representations and Clusters
arXiv:2606. 07135v1 Announce Type: new Abstract: Huntington's disease (HD) is a progressive neurodegenerative disorder that affects motor, cognitive, and behavioral functions, where accurate characterization of disease progression remains essential to improve patient outcome and quality of life.
arXiv Machine Learning
Jun 8
Sparsely gated tiny linear experts
arXiv:2606. 07414v1 Announce Type: new Abstract: Sparsity allows scaling model parameters without proportionally increasing computational cost.
arXiv AI
Jun 8
$\mathrm{ECI}_{\mathrm{sem}}$: Semantic Residual Effective Contrastive Information for Evaluating Hard Negatives
arXiv:2603. 20990v3 Announce Type: replace-cross Abstract: Hard-negative source selection for dense retrieval is usually decided only after fine-tuning and downstream evaluation.
arXiv AI
Jun 8
Automatic Causal Fairness Analysis with LLM-Generated Reporting
arXiv:2604. 27011v2 Announce Type: replace-cross Abstract: AutoML, intended as the process of automating the application of machine learning to real-world problems, is a key step for AI popularisation.
arXiv AI
Jun 8
Re-imagining ISO 26262 in the Age of Autonomous Vehicles: Enhancing Controllability through Transferability and Predictability
arXiv:2606. 07437v1 Announce Type: cross Abstract: The ISO 26262 standard defines functional safety for road vehicles through risk assessments based on Severity, Exposure, and Controllability, grounded in a human-driven vehicle paradigm.
arXiv AI
Jun 8
When Large Language Models Fail in Healthcare: Evaluating Sensitivity to Prompt Variations
arXiv:2606. 07237v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in healthcare for tasks such as clinical question answering, diagnosis support, and report summarization.
arXiv Machine Learning
Jun 8
GRASP: Geometry-aware Residual Alignment for Scalable Pretraining Data Attribution
arXiv:2606. 06892v1 Announce Type: new Abstract: Scalable data attribution methods typically assign isolated utility scores to individual training examples.
arXiv Machine Learning
Jun 8
Learning Fair Demand Models
arXiv:2606. 06830v1 Announce Type: cross Abstract: Data-driven pricing is increasingly prevalent in sectors such as airlines, lending, insurance, and retail.
arXiv Machine Learning
Jun 8
The discovery of the effects of women employment participation on the fertility of developing countries: A panel data approach
arXiv:2606. 07093v1 Announce Type: new Abstract: The fertility trend in developing countries has experienced a significant decline in the last few decades; at the same time, the role of women in the workplace has improved.
arXiv AI
Jun 8
FIGMA: Towards FIne-Grained Music retrievAl
arXiv:2606. 06615v1 Announce Type: cross Abstract: Retrieving music using natural language descriptions has improved with contrastive audio-text models such as CLAP, but current systems remain limited to coarse semantic queries.
arXiv AI
Jun 8
Breaking the Lock-in: Diversifying Text-to-Image Generation via Representation Modulation
arXiv:2606. 06813v1 Announce Type: cross Abstract: Recent text-to-image models built on large-scale Transformer backbones and flow-based objectives deliver strong text-image alignment and high visual quality, yet often produce overly similar samples under a fixed prompt.
arXiv Machine Learning
Jun 8
Principles and Practice of Deep Representation Learning: or a Mathematical Theory of Memory
arXiv:2606. 06624v1 Announce Type: new Abstract: In the current era of deep learning and especially generative models, there is significant investment in training very large generative models.
arXiv AI
Jun 8
Evidence Graph Consistency in Retrieval-Augmented Generation: A Model-Dependent Analysis of Hallucination Detection
arXiv:2606. 06748v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) reduces but does not eliminate hallucination in large language models.
arXiv AI
Jun 8
SlimSearcher: Training Efficiency-Aware Web Agents via Adaptive Reward Gating
arXiv:2606. 07074v1 Announce Type: cross Abstract: Deep research agents have demonstrated remarkable capabilities in complex information-seeking tasks, yet this power comes at a steep computational cost.
arXiv AI
Jun 8
Inside the Visual Mind: Neuroscience-Motivated Concept Circuits for Interpreting and Steering Vision Transformers
arXiv:2606. 06664v1 Announce Type: cross Abstract: Despite high accuracy, Vision Transformer (ViT) predictions can be driven by spurious cues, raising the need to understand their inner workings before safe deployment.
arXiv AI
Jun 8
Workflow-to-Skill: Skill Creation via Routing-Workflow-Semantics-Attachments Decomposition
arXiv:2606. 06893v1 Announce Type: new Abstract: Large language model agents increasingly rely on Skills to encode procedural knowledge, yet high-quality Skills remain costly to hand-write.