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Weighted Random Dot Product Graphs

arXiv:2505.03649v4 Announce Type: replace-cross Abstract: Modeling of intricate relational patterns has become a cornerstone of contemporary statistical research and related data science fields. Netwo

What Limits Does Quantization Place on Dense Top-k Retrieval? A Theoretical Study

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DGX agent

arXiv:2606.11780v1 Announce Type: cross Abstract: We establish conditions for embedding a corpus of N documents as d-dimensional vectors such that every k-subset S subseteq [N] is realizable as a resu

researcharxiv-cs-ai

11 Jun 2026

What Uncertainties Do We Need for Dynamical Systems?

arXiv:2606.11988v1 Announce Type: new Abstract: The distinction between aleatoric and epistemic uncertainty has received considerable attention in machine learning research, mainly in the context of s

When Do Data-Driven Systems Exhibit the Capability to Infer?

arXiv:2606.11769v1 Announce Type: new Abstract: The European AI Act is the first comprehensive regulation of artificial intelligence (AI), setting out extensive obligations, particularly for so-called

When Poison Fails After Retrieval: Revisiting Corpus Poisoning under Chunking and Reranking Pipelines

arXiv:2606.11265v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems are vulnerable to corpus poisoning attacks that manipulate downstream model outputs through malicious kno

When Probing Accuracy Saturates, Fragility Resolves: A Complementary Metric for LLM Pre-Training Analysis

arXiv:2606.11375v1 Announce Type: cross Abstract: Standard linear probing declares a property 'encoded' when a classifier on hidden states achieves high accuracy. The protocol works well on a snapshot

Where Do Backdoors Live? A Component-Level Analysis of Backdoor Propagation in Speech Language Models

arXiv:2510.01157v4 Announce Type: replace Abstract: Speech language models (SLMs) are systems of systems: independent components that unite to achieve a common goal. Despite their heterogeneous nature

Why Depth Matters in Parallelizable Sequence Models: A Lie Algebraic View

arXiv:2603.05573v2 Announce Type: replace Abstract: Scalable sequence models, such as Transformer variants and structured state-space models, often trade expressivity power for sequence-level parallel

XPR: An Extensible Cross-Platform Point-Based Differentiable Renderer

arXiv:2606.11529v1 Announce Type: cross Abstract: Point-based differentiable rendering underpins modern 3D reconstruction, novel-view synthesis, and learning-based graphics pipelines, but developing n

A Continuous-Time Markov Chain Framework for Insertion Language Models

arXiv:2606.10199v1 Announce Type: cross Abstract: Insertion Language Models (ILMs) offer several advantages over left-to-right generation and mask-based generation. However, existing formulations of i

A Controlled Audit of Pretraining Contamination in Public Medical Vision-Language Benchmarks

arXiv:2606.10066v1 Announce Type: cross Abstract: Medical vision-language models (VLMs) are evaluated on public benchmarks whose images and question-answer pairs have been freely downloadable for year

A Multimodal RGB and Events Dataset for Hand Detection in First-Person View

arXiv:2606.10790v1 Announce Type: new Abstract: Existing hand detection algorithms work on images and the detection rate is restricted by the frame rate of the camera. In hand detection applications f

A Sketch-and-Project Analysis of Subsampled Natural Gradient Algorithms

arXiv:2508.21022v3 Announce Type: replace Abstract: Subsampled natural gradient descent (SNG) has been used to enable high-precision scientific machine learning, but standard analyses based on stochas

A Spiking Neural Architecture for Coordinating Arm and Locomotor Control

arXiv:2606.11034v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) coupled with neuromorphic hardware offer energy-efficient solutions for humanoid robot control. However, existing SNN-bas

researcharxiv-cs-ro

A Systematic Approach for Selecting Trajectories for Data Augmentation

arXiv:2606.10938v1 Announce Type: new Abstract: Trajectory data augmentation is a promising approach to mitigate data scarcity in machine learning applications, but its utility has been limited by the

A Unified Adaptive Feature Composition Framework for Multi-Task Generalization in Wireless Foundation Models

arXiv:2606.10277v1 Announce Type: new Abstract: Though wireless foundation models (WFMs) have shown strong potential in learning universal channel representations, their adaptation to various downstre

A Unified Siamese Learning Framework for Zero-Day Anomaly Detection and Classification in Optical Networks

arXiv:2606.10827v1 Announce Type: cross Abstract: A multi-similarity Siamese neural network unifies zero-day anomaly detection and one-shot classification in optical networks, achieving over 99% accur

Accelerating NeurASP with vectorization and caching

arXiv:2606.10787v1 Announce Type: new Abstract: Neurosymbolic AI combines neural networks with symbolic programs to create robust and explainable predictions. One such framework is NeurASP, which trai

Accelerating SAV-based optimization via randomized low-rank Hessian approximation

arXiv:2606.10562v1 Announce Type: cross Abstract: We propose a new optimization method, the Nystrom-enhanced relaxed scalar auxiliary variable method (N-RSAV), which incorporates curvature information

Adaptive Sliding Mode Control for Vehicle Platoons with State-Dependent Friction Uncertainty

arXiv:2601.10724v3 Announce Type: replace Abstract: Multi-robot formation control has various applications in domains such as vehicle troops, platoons, payload transportation, and surveillance. Mainta

researcharxiv-cs-ro

Advancing Wood Identification in the Philippines: Utilizing the Xylorix Platform for Efficient AI Model Development and Deployment for Five Key Species

arXiv:2606.10876v1 Announce Type: new Abstract: Illegal logging and timber trade continue to pose significant challenges in the Philippines, where accurate wood species identification is essential for

AI Application Gives Users Real-Time Feedback on the Level of Peace in the Social Media Videos They Watch

arXiv:2601.05232v3 Announce Type: replace Abstract: Most people now get their news from videos on social media, such as YouTube and Facebook, rather than through curated journalism. 'We become what we

AI-Driven Analytics of Team-Teaching Talk: Acoustic Patterns across Experience, Cohorts and the Learning Design

arXiv:2606.09831v1 Announce Type: cross Abstract: As classroom cohorts expand, team teaching is increasingly used to integrate the expertise and pedagogical perspectives of multiple teachers. Yet, the

Algorithmic and Minimax Complexities in Kernel Bandits

arXiv:2606.11171v1 Announce Type: new Abstract: Gaussian-process upper confidence bound (GP-UCB) and decision-estimation-coefficient (DEC) methods may appear, at first sight, to belong to different th

Ambiguous Strategic Classification

arXiv:2606.10137v1 Announce Type: new Abstract: A common assumption in strategic classification is that the classifier is public knowledge. However, it remains unclear whether, and why, a system would

An (epsilon,elta)-accurate level set estimation with a stopping criterion

arXiv:2503.20272v2 Announce Type: replace-cross Abstract: The level set estimation problem seeks to identify regions within a set of candidate points where an unknown and costly to evaluate function's

An Uncertainty Estimation Framework for Dose Accumulation in Adaptive Radiotherapy: Application to CBCT-Guided Radiotherapy for Cervical Cancer

arXiv:2606.11012v1 Announce Type: new Abstract: Background and purpose: oART enables daily plan adaptation to interfraction anatomical variations, but cumulative dose estimation remains limited by DIR

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling

arXiv:2606.10233v1 Announce Type: cross Abstract: While speech quality is typically assessed on complete utterances, streaming and generative systems require incremental estimation from partial audio.

AnimeScore: A Preference-Based Dataset and Framework for Evaluating Anime-Like Speech Style

arXiv:2603.11482v2 Announce Type: replace-cross Abstract: Evaluating 'anime-like' voices currently relies on costly subjective judgments, yet no standardized objective metric exists. A key challenge i

Anthropic says the nerf only affects .03% of requests. That .03% is the people who change the world. @theemozilla and @Karan4d, co-founders …

Anthropic says the nerf only affects .03% of requests. That .03% is the people who change the world. @theemozilla and @Karan4d, co-founders of Nous Research: 'The priority is to hide the fact that the

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ArabiGEE: A Hierarchical Taxonomy for Arabic Grammatical Error Explanation

arXiv:2606.10765v1 Announce Type: new Abstract: We introduce ArabiGEE, the first comprehensive Arabic grammatical error explanation (GEE) taxonomy grounded in explicit error types. Unlike existing GEE

Are We Evaluating Knowledge or Phrasing? Mitigating MCQA Sensitivity with ParaEval

arXiv:2606.10657v1 Announce Type: new Abstract: Multiple-choice (MCQA) benchmarks are the standard for evaluating pretrained large language models, but their reliance on log-likelihood scoring makes t

Assessment of Personality Dimensions Across Situations in Dyadic Role-Play Scenarios

arXiv:2507.19137v2 Announce Type: replace-cross Abstract: Prior research indicates that users prefer assistive technologies whose personalities align with their own. This has sparked interest in autom

Attacks on Machine-Text Detectors Retain Stylistic Fingerprints

arXiv:2505.14608v3 Announce Type: replace-cross Abstract: Despite considerable progress in the development of machine-text detectors, the ease with which machine-text can be manipulated to evade detec

Attention-Discounted Adaptive Sampler for Masked Diffusion Language Models

arXiv:2606.10829v1 Announce Type: cross Abstract: Masked diffusion language models can reduce inference steps by revealing multiple tokens per denoising iteration, but this parallelism is fragile: pos

Audio-Visual Exchange-Aware Token Pruning for Efficient Audio-Visual Captioning

arXiv:2606.10533v1 Announce Type: new Abstract: Audio-visual captioning generates natural language descriptions from video and audio content. Multimodal LLMs have advanced this task, but both modaliti

AuRA: Internalizing Audio Understanding into LLMs as LoRA

arXiv:2606.11033v1 Announce Type: cross Abstract: Recent efforts to extend large language models (LLMs) to speech inputs typically rely on cascaded ASR-LLM pipelines, end-to-end speech-language models

Automated Pronunciation Evaluation for Korean Toddler Speech using Speech Diarization and Self-Supervised Learning

arXiv:2606.10213v1 Announce Type: cross Abstract: Speech sound disorders affect approximately 44% of Korean pediatric communication disorder cases, yet automated assessment tools for Korean toddler sp

Belief Acquisition as Stochastic Filtering

arXiv:2206.02178v3 Announce Type: replace Abstract: This paper studies how belief acquisition can be accomplished using stochastic filtering. First, a theoretical foundation for empirical beliefs is o

Belief-Space Control for Personalized Cancer Treatment via Active Inference

arXiv:2606.10376v1 Announce Type: new Abstract: Cancer treatment is at the core a sequential decision-making problem with partial observability, latent patient heterogeneity, and explicit constraints

Between Amnesia and Chaos: A Memory Stability Expressivity Trilemma for Trainable Dissipative Oscillator Networks

arXiv:2606.09929v1 Announce Type: cross Abstract: Physical reservoir computing harnesses nonlinear mechanical dynamics but, by convention, freezes the substrate and trains only a linear readout, presu

Beyond Explaining Predictions: Logic-Based Explanations for Confidence in Machine Learning Models

arXiv:2606.10347v1 Announce Type: new Abstract: Machine learning is increasingly used in critical domains, where both predictions and their associated confidence levels influence important decisions.

Blind denoising diffusion models and the blessings of dimensionality

arXiv:2602.09639v2 Announce Type: replace Abstract: Denoising diffusion models (DDMs) are state-of-the-art methods for learning densities from data across numerous domains, yet many aspects of the tra

Blurry Window Attention

arXiv:2606.09862v1 Announce Type: cross Abstract: The Softmax Attention operation in Transformer language models has a quadratic complexity in the sequence length and a growing state size in the form

Building Change Detection in Earthquake: A Multi-Scale Interaction Network and A Change Detection Dataset

arXiv:2606.10329v1 Announce Type: cross Abstract: As one of the most destructive natural disasters, earthquakes have struck many countries around the world in recent years, causing serious economic lo

Calibrating Overconfidence Without Sacrificing Confidence: Probe-Conditioned Head Intervention for LLMs

arXiv:2606.09876v1 Announce Type: new Abstract: Large language models often express high confidence in answers that are wrong. Standard calibration remedies typically act globally or at the score leve

Can we trust our models? Epistemic calibration in second-order classification

arXiv:2606.10777v1 Announce Type: new Abstract: Uncertainty estimation is critical for deploying machine learning models in high-stakes settings. However, classical calibration only assesses the relia

CAST: Counterfactual Labels Improve Instruction Following in Vision-Language-Action Models

arXiv:2508.13446v2 Announce Type: replace Abstract: Generalist robots should be able to understand and follow user instructions. Despite providing a powerful architecture for mapping open-vocabulary l

researcharxiv-cs-ro