Search: “research”

Weighted Rules under the Stable Model Semantics

arXiv:2605.09519v1 Announce Type: new Abstract: We introduce the concept of weighted rules under the stable model semantics following the log-linear models of Markov Logic. This provides versatile met

What Concepts Lie Within? Detecting and Suppressing Risky Content in Diffusion Transformers

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arXiv:2605.10180v1 Announce Type: new Abstract: The rise of text-to-image (T2I) models has increasingly raised concerns regarding the generation of risky content, such as sexual, violent, and copyrigh

researcharxiv-cs-cv

12 May 2026

What Does Flow Matching Bring To TD Learning?

arXiv:2603.04333v2 Announce Type: replace-cross Abstract: Recent work shows that flow matching can be effective for scalar Q-value function estimation in reinforcement learning (RL), but it remains un

When and Why Grouping Attention Heads Accelerates Muon Optimization

arXiv:2605.08933v1 Announce Type: new Abstract: Muon orthogonalizes matrix updates, but multi-head attention naturally operates at the level of heads. This granularity mismatch raises the question of

When Can Human-AI Teams Outperform Individuals? Tight Bounds with Impossibility Guarantees

arXiv:2605.08710v1 Announce Type: new Abstract: Human-AI teams fail to outperform their best member in 70% of studies, yet no theory specifies when complementarity is achievable. We derive tight bound

When Does Value-Aware KV Eviction Help? A Fixed-Contract Diagnostic for Non-Monotone Cache Compression

arXiv:2605.08234v1 Announce Type: cross Abstract: Long-context LLM inference is bottlenecked by the memory and bandwidth cost of reading large KV caches during decoding. KV compression reduces this co

When Efficient Communication Explains Convexity

arXiv:2602.02821v2 Announce Type: replace Abstract: Much recent work has argued that the variation in the languages of the world can be explained from the perspective of efficient communication; in pa

When Few Steps Are Enough: Training-Free Acceleration of Identity-Preserved Generation

arXiv:2605.09460v1 Announce Type: cross Abstract: Identity-preserved image generation is typically built on many-step diffusion backbones, making personalized generation expensive at deployment time.

When Less is More: The LLM Scaling Paradox in Context Compression

arXiv:2602.09789v3 Announce Type: replace Abstract: Scaling up model parameters has long been a prevalent training paradigm driven by the assumption that larger models yield superior generation capabi

When Style Similarity Scores Fail: Diagnosing Raw CSD Cosine in Artist-Style Evaluation

arXiv:2605.09030v1 Announce Type: new Abstract: Raw cosine in the 768-dimensional output space of the Contrastive Style Descriptor (CSD) is now widely read as an absolute, calibrated style-fidelity sc

When Tables Leak: Attacking String Memorization in LLM-Based Tabular Data Generation

arXiv:2512.08875v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have recently demonstrated remarkable performance in generating high-quality tabular synthetic data. In practice,

Where do aspectual variants of light verb constructions belong?

arXiv:2605.10605v1 Announce Type: new Abstract: Expressions with an aspectual variant of a light verb, e.g. 'take on debt' vs. 'have debt', are frequent in texts but often difficult to classify betwee

Where Do Reasoning Models Refuse?

arXiv:2507.03167v3 Announce Type: replace-cross Abstract: Chat models without chain-of-thought (CoT) reasoning must decide whether to refuse a harmful request before generating their first response to

Where Reliability Lives in Vision-Language Models: A Mechanistic Study of Attention, Hidden States, and Causal Circuits

arXiv:2605.08200v1 Announce Type: new Abstract: A pervasive intuition holds that vision-language models (VLMs) are most trustworthy when their attention maps look sharp: concentrated attention on the

WorldSpeech: A Multilingual Speech Corpus from Around the World

arXiv:2605.09167v1 Announce Type: cross Abstract: Automatic speech recognition (ASR) performs well for high-resource languages with abundant paired audio-transcript data, but its accuracy degrades sha

xApp Empowered Resource Management for Non-Terrestrial Users in 5G O-RAN Networks

arXiv:2605.10704v1 Announce Type: cross Abstract: This paper introduces a proactive Unmanned Aerial Vehicle (UAV) mobility management xApp for Open Radio Access Network (O-RAN) Near Real-Time Radio In

researcharxiv-cs-ro

XPERT: Expert Knowledge Transfer for Effective Training of Language Models

arXiv:2605.08842v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) language models organize knowledge into explicitly routed expert modules, making expert-level representations traceable and ana

XTinyU-Net: Training-Free U-Net Scaling via Initialization-Time Sensitivity

arXiv:2605.09639v1 Announce Type: cross Abstract: While U-Net architectures remain the gold standard for medical image segmentation, their deployment in resource-constrained environments demands aggre

Yeti: A compact protein structure tokenizer for reconstruction and multi-modal generation

arXiv:2605.09981v1 Announce Type: cross Abstract: Multimodal models that jointly reason over protein sequences, structures, and function annotations within a unified representation hold immense potent

YEZE at SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization via Heterogeneous Ensembling

arXiv:2605.06231v2 Announce Type: replace Abstract: This paper presents our system for SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization, which identifies p

ZAYA1-VL-8B Technical Report

arXiv:2605.08560v1 Announce Type: cross Abstract: We present ZAYA1-VL-8B, a compact mixture-of-experts vision-language model built upon our in-house language model, ZAYA1-8B. Despite its compact size,

3D tomography of exchange phase in a Si/SiGe quantum dot device

arXiv:2603.16025v2 Announce Type: replace-cross Abstract: The exchange interaction is a foundational building block for the operation of spin-based quantum processors. Extracting the exchange interact

3DSS: 3D Surface Splatting for Inverse Rendering

arXiv:2605.05876v2 Announce Type: replace-cross Abstract: We present 3D Surface Splatting (3DSS), the first differentiable surface splatting renderer for physically-based inverse rendering from multi-

6D Pose Estimation via Keypoint Heatmap Regression with RGB-D Residual Neural Networks

arXiv:2605.08059v1 Announce Type: new Abstract: In this paper, we propose a modular framework for 6D pose estimation based on keypoint heatmap regression. Our approach combines YOLOv10m for object det

A Behavioral Framework for Data-Driven Modeling of Nonlinear Systems in Vector-Valued Reproducing Kernel Hilbert Spaces

arXiv:2605.07052v1 Announce Type: cross Abstract: We generalize Jan Willems' behavioral approach to a class of discrete-time nonlinear systems in a vector-valued reproducing kernel Hilbert space (RKHS

A Comparative Analysis of Classical Machine Learning and Deep Learning Approaches for Sentiment Classification on IMDb Movie Reviews

arXiv:2605.07811v1 Announce Type: new Abstract: This paper presents a comparative study of classical machine learning and deep learning methods for sentiment classification on the IMDb movie reviews d

A Computer Vision Pipeline for Individual-Level Behavior Analysis: Benchmarking on the Edinburgh Pig Dataset

arXiv:2509.12047v2 Announce Type: replace-cross Abstract: Animal behavior analysis plays a crucial role in understanding animal welfare, health status, and productivity in agricultural settings. Howev

A Flexible Adaptive Stable Clustering Algorithm for Archive-Scale Online Mass Spectrometry

arXiv:2605.07424v1 Announce Type: new Abstract: Modern online mass spectrometry generates multi-terabyte data streams critical for understanding Earth's environmental systems. However, extracting acti

A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks

arXiv:2603.22586v2 Announce Type: replace Abstract: In-context learning (ICL) enables task adaptation at inference time by conditioning on demonstrations rather than updating model parameters. Althoug

A Hybrid Graph Neural Network for Enhanced EEG-Based Depression Detection

arXiv:2410.18103v2 Announce Type: replace-cross Abstract: Graph neural networks (GNNs) are becoming increasingly popular for EEG-based depression detection. However, previous GNN-based methods fail to

A Linear-Transformer Hybrid for SNP-Based Genotype-to-Phenotype Prediction in Grapevine

arXiv:2605.06762v1 Announce Type: cross Abstract: Robust genotype-to-phenotype (G2P) prediction is essential for accelerating breeding decisions and genetic gain. However, it remains challenging to me

A lot of people are being deliberately obtuse about this tweet. Would it help if I said 'theory' instead of 'idea'? Because it would still m…

researchfrancois-chollet--x

A lot of people are being deliberately obtuse about this tweet. Would it help if I said 'theory' instead of 'idea'? Because it would still mean the exact same. FYI reading comprehension is about inter

A Note on Non-Negative L_1-Approximating Polynomials

arXiv:2605.08072v1 Announce Type: cross Abstract: L_1-Approximating polynomials, i.e., polynomials that approximate indicator functions in L_1-norm under certain distributions, are widely used in comp

A Refined Generalization Analysis for Extreme Multi-class Supervised Contrastive Representation Learning

arXiv:2605.07596v1 Announce Type: cross Abstract: Contrastive Representation Learning (CRL) has achieved strong empirical success in multiple machine learning disciplines, yet its theoretical sample c

A Resilience Framework for Bi-Criteria Combinatorial Optimization with Bandit Feedback

arXiv:2503.12285v2 Announce Type: replace-cross Abstract: We study bi-criteria combinatorial optimization under noisy function evaluations. While resilience and black-box offline-to-online reductions

A Rod Flow Model for Adam at the Edge of Stability

arXiv:2605.06821v1 Announce Type: cross Abstract: Cohen et al. (arXiv:2207.14484) observed that adaptive gradient methods such as Adam operate at the edge of stability. While there has been significan

A Step to Decouple Optimization in 3DGS

arXiv:2601.16736v5 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful technique for real-time novel view synthesis. As an explicit representation optimized through

A Theory of Online Learning with Autoregressive Chain-of-Thought Reasoning

arXiv:2605.06819v1 Announce Type: new Abstract: Autoregressive generation lies at the heart of the mechanism of large language models. It can be viewed as the repeated application of a next-token gene

A Unified Framework for the Detection and Classification of Fatty Pancreas in Ultrasound Images

arXiv:2605.07466v1 Announce Type: new Abstract: Non-alcoholic fatty pancreas disease (NAFPD) is an underdiagnosed condition associated with metabolic syndrome, insulin resistance, and increased risk o

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models

arXiv:2605.06829v1 Announce Type: cross Abstract: We survey continuous-time generative modeling methods based on transporting a simple reference distribution to a data distribution via stochastic or d

A Wasserstein GAN-based climate scenario generator for risk management and insurance: the case of soil subsidence

arXiv:2605.06678v1 Announce Type: new Abstract: According to the United Nations Office for Disaster Risk Reduction (2025), the average annual cost of natural catastrophes increased from 70--80 billion

Abductive Reasoning with Probabilistic Commonsense

arXiv:2605.08011v1 Announce Type: new Abstract: Recent efforts to improve the reasoning abilities of Large Language Models (LLMs) have focused on integrating formal logic solvers within neurosymbolic

Accelerated and data-efficient flow prediction in stirred tanks via physics-informed learning

arXiv:2605.07444v1 Announce Type: cross Abstract: The simulation of fluid flows is computationally expensive due to the complexity of its governing partial differential equations. Machine learning mod

Active Embodiment Identification with Reinforcement Learning for Legged Robots

arXiv:2605.08020v1 Announce Type: new Abstract: We present an active embodiment identification method for legged robots that jointly learns information-seeking behavior and explicit embodiment predict

researcharxiv-cs-ro

AdaCorrection: Adaptive Offset Cache Correction for Accurate Diffusion Transformers

arXiv:2602.13357v2 Announce Type: replace-cross Abstract: Diffusion Transformers (DiTs) achieve state-of-the-art performance in high-fidelity image and video generation but suffer from expensive infer

AdaHOP: Fast and Accurate Low-Precision Training via Outlier-Pattern-Aware Rotation

arXiv:2604.02525v2 Announce Type: replace Abstract: Hadamard transforms have become a key tool for stabilizing low-precision training, but existing methods apply them uniformly across tensors and comp

Adaptive auditing of AI systems with anytime-valid guarantees

arXiv:2605.07002v1 Announce Type: new Abstract: A major bottleneck in characterizing the failure modes of generative AI systems is the cost and time of annotation and evaluation. Consequently, adaptiv

Adaptive Domain Decomposition Physics-Informed Neural Networks for Traffic State Estimation with Sparse Sensor Data

arXiv:2605.08028v1 Announce Type: new Abstract: Traffic state estimation from sparse fixed sensors is challenging because physics-informed neural networks (PINNs) tend to over-smooth the shockwaves ad