arXiv AI
Jun 11
Every Act Has Its Price: Compressed Moral Composition in Frontier LLMs
arXiv:2606. 11232v1 Announce Type: cross Abstract: Existing LLM moral benchmarks usually ask which isolated moral act, value, or foundation a model prefers.
Benchmarks and evaluation
Leaderboards, eval harnesses and ablations — the contested business of deciding which model is actually better.
arXiv AI
Jun 11
Quality Adaptive Angular Margin Learning for Respiratory Sound Classification
arXiv:2606. 11915v1 Announce Type: cross Abstract: We present a quality-adaptive angular-margin learning framework that improves feature generalization by enforcing intra-class compactness and inter-class separability.
arXiv AI
Jun 11
WorldReasoner: Evaluating Whether Language Model Agents Forecast Events with Valid Reasoning
arXiv:2606. 11816v1 Announce Type: cross Abstract: Forecasting real-world events requires language-model agents to reason under uncertainty from incomplete, time-bounded information.
arXiv AI
Jun 11
FlowBank: Query-Adaptive Agentic Workflows Optimization through Precompute-and-Reuse
arXiv:2606. 11290v1 Announce Type: cross Abstract: Large Language Model (LLM)-based multi-agent systems are increasingly powerful, but current agentic workflow optimization paradigms make an unsatisfying trade-off.
arXiv Machine Learning
Jun 11
Restless bandits with imperfect binary feedback: PCL-indexability analysis and computation
arXiv:2606. 11192v1 Announce Type: new Abstract: We study restless bandits with binary latent states and imperfect binary feedback, motivated by opportunistic spectrum access with sensing errors.
arXiv AI
Jun 11
NightFeats @ MMU-RAGent NeurIPS 2025: A Context-Optimized Multi-Agent RAG System for the Text-to-Text Track
arXiv:2606. 11199v1 Announce Type: cross Abstract: We present NightFeats, a structured multi-agent retrieval-augmented generation (RAG) system submitted to the MMU-RAGent competition at NeurIPS 2025, where it was awarded Best Dynamic Evaluation in the text-to-text track.
arXiv AI
Jun 11
OpenMedReason: Scientific Reasoning Supervision for Medical Vision-Language Models
arXiv:2606. 12169v1 Announce Type: cross Abstract: High-stakes clinical use of large vision-language models (LVLMs) requires reasoning that is grounded in visual evidence and clinical knowledge, not just correct final answers.
arXiv Machine Learning
Jun 11
Context-Driven Incremental Compression for Multi-Turn Dialogue Generation
arXiv:2606. 12411v1 Announce Type: cross Abstract: Modern conversational agents condition on an ever-growing dialogue history at each turn, incurring redundant attention and encoding costs that grow with conversation length.
arXiv AI
Jun 11
Diffusing to Coordinate: Efficient Online Multi-Agent Diffusion Policies
arXiv:2602. 18291v2 Announce Type: replace Abstract: Online Multi-Agent Reinforcement Learning (MARL) is a prominent framework for efficient agent coordination.
arXiv AI
Jun 11
Estimating Tail Risks in Language Model Output Distributions
arXiv:2604. 22167v2 Announce Type: replace-cross Abstract: Language models are increasingly capable and are being rapidly deployed on a population-level scale.
arXiv AI
Jun 11
Atlas H&E-TME: Scalable AI-Based Tissue Profiling at Expert Pathologist-Level Accuracy
arXiv:2606. 12346v1 Announce Type: cross Abstract: Hematoxylin and eosin (H&E) staining is the cornerstone of histopathology, yet scalable, quantitative analysis of H&E whole-slide images (WSIs) remains a central challenge in computational pathology.
arXiv AI
Jun 11
AnchorEdit: Maintaining Temporal Consistency in Multi-turn Image Editing via Causal Memory
arXiv:2606. 11751v1 Announce Type: cross Abstract: Multi-turn image editing is essential for iterative design, yet current models often struggle with identity drift and error accumulation over successive steps.
arXiv AI
Jun 11
Weakly Supervised Segmentation as Semantic-Based Regularization
arXiv:2605. 13674v2 Announce Type: replace-cross Abstract: Weakly supervised semantic segmentation (WSSS) trains dense pixel-level segmentation models from partial or coarse annotations such as bounding boxes, scribbles, or image-level tags.
arXiv AI
Jun 11
Improving Generalization and Data Efficiency with Diffusion in Offline Multi-agent RL
arXiv:2307. 01472v2 Announce Type: replace Abstract: We present a novel Diffusion Offline Multi-agent Model (DOM2) for offline Multi-Agent Reinforcement Learning (MARL).
arXiv AI
Jun 11
Brain-IT-VQA: From Brain Signals to Answers
arXiv:2605. 29588v2 Announce Type: replace-cross Abstract: Decoding visual content from fMRI signals recorded while a person views images, and specifically answering questions about the seen images, is a long-standing challenge.
arXiv AI
Jun 11
KAN-MLP-Mixer: A comprehensive investigation of the usage of Kolmogorov-Arnold Networks (KANs) for improving IMU-based Human Activity Recognition
arXiv:2605. 19031v2 Announce Type: replace Abstract: Kolmogorov-Arnold Networks (KANs) have demonstrated an exceptional ability to learn complex functions on clean, low-dimensional data but struggle to maintain performance on noisy and imperfect real-world datasets.
arXiv AI
Jun 11
A Five-Plane Reference Architecture for Runtime Governance of Production AI Agents
arXiv:2606. 12320v1 Announce Type: new Abstract: Enterprise security was built to govern data boundaries: the protected surface was data at rest and in transit, and the controls -- access control, data-loss prevention, perimeter inspection -- governed crossings of that boundary.
arXiv Machine Learning
Jun 11
GraspLLM: Towards Zero-Shot Generalization on Text-Attributed Graphs with LLMs
arXiv:2606. 11898v1 Announce Type: cross Abstract: Research on Text-Attributed Graphs (TAGs) has gained significant attention recently due to its broad applications across various real-world data scenarios, such as citation networks, e-commerce platforms, social media, and web pages.
arXiv AI
Jun 11
SirenFNO: Efficient and Full Frequency Learning of Fourier Neural Operators
arXiv:2606. 11518v1 Announce Type: cross Abstract: Fourier neural operators (FNOs) are effective and efficient surrogates for approximating solutions of PDEs and generalize across discretizations.
arXiv Machine Learning
Jun 11
Hybrid Iterative Neural Low-Regularity Integrator for Nonlinear Dispersive Equations
arXiv:2605. 04853v2 Announce Type: replace Abstract: We propose HIN-LRI, a hybrid framework that augments a classical numerical solver with a neural operator trained to correct the solver's structured truncation error.