Search: “research”

Plans for Evaluating Structured Generative Search Summaries

arXiv:2605.26400v1 Announce Type: cross Abstract: We propose a framework for evaluating structured generative search summaries that are placed atop organic web search results. A structured summary, ge

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PlayClass: Automated Play Behaviour Classification in Poultry

DGX agent

arXiv:2605.27304v1 Announce Type: new Abstract: Automated monitoring of animal welfare has largely targeted negative indicators, leaving positive welfare behaviours such as play underexplored. To addr

researcharxiv-cs-cv

27 May 2026

Pop-Up Distractions Reveal Bag-of-Events Behavior in Video Large Language Models

arXiv:2605.27101v1 Announce Type: cross Abstract: A key capability for video understanding is reliably linking subjects to events across time, yet whether Video Large Language Models (VideoLLMs) actua

Probabilistic Recurrent Intention Switching Model

arXiv:2605.26998v1 Announce Type: new Abstract: Inverse reinforcement learning (IRL) recovers reward functions from observed behavior, yet traditional methods assume a single stationary reward that ca

Probabilistic Smoothing with Ratio-Monotone Transforms for Global Optimization

arXiv:2605.27316v1 Announce Type: new Abstract: Probabilistic smoothing is a standard tool for global optimization, but existing methods rely on Gaussian kernels and specific transforms, often resulti

Probing Minimalist Phase Structure in LLMs: What Universal Dependencies Cannot Represent

arXiv:2605.26431v1 Announce Type: new Abstract: Structural probes train on Universal Dependencies (UD), which does not encode formal-syntactic abstractions such as phase boundaries or phase-internal c

Prospective evaluation of multimodal respiratory failure prediction: Do chest X-rays improve performance beyond EHR signals?

arXiv:2605.26255v1 Announce Type: cross Abstract: Early prediction of respiratory failure is critical for timely clinical intervention in intensive care units. Existing electronic health record (EHR)-

Q-GeoMem: Question-Guided Geometric Memory for Video Spatial Reasoning

arXiv:2605.27318v1 Announce Type: new Abstract: Video spatial reasoning requires accumulating viewpoint-dependent evidence over time while retaining information useful to the question being asked. Exi

QAM-W: Joint 2D Codebook Quantization for LLM Weights via Hadamard Rotation and Activation-Aware Scaling

arXiv:2605.26339v1 Announce Type: cross Abstract: Scalar post-training quantizers discard pairwise coordinate structure within weight rows. We introduce QAM-W (Quadrature Amplitude Modulation for Weig

Quadratic Term Correction on Heaps' Law

arXiv:2511.14683v2 Announce Type: replace Abstract: Heaps' or Herdan's law characterizes the word-type vs. word-token relation by a power-law function, which is concave in linear-linear scale but a st

Quality Without Usefulness: LLM-Generated XAI Narratives as Trust Heuristics Rather Than Decision Aids

arXiv:2605.26770v1 Announce Type: new Abstract: Prior work shows that Large Language Models (LLMs) can transform Explainable AI (XAI) outputs into Natural Language Explanations (NLEs) that score highl

Querying and Repairing Inconsistent Prioritized Knowledge Bases: Complexity Analysis and Links with Abstract Argumentation

arXiv:2003.05746v4 Announce Type: replace-cross Abstract: In this paper, we explore the issue of inconsistency handling over prioritized knowledge bases (KBs), which consist of an ontology, a set of f

R^3: 3D Reconstruction via Relative Regression

arXiv:2605.26519v1 Announce Type: new Abstract: Recent feed-forward geometry foundation models have demonstrated impressive generalization by recovering depth and poses in a single forward pass. Howev

RadarSim: Simulating Single-Chip Radar via Multimodal Neural Fields

arXiv:2605.26328v1 Announce Type: new Abstract: Radars are an ideal complement to cameras: both are inexpensive, solid-state sensors, with cameras offering fine angular resolution, while radars provid

Rank-Learner: Orthogonal Ranking of Treatment Effects

arXiv:2602.03517v2 Announce Type: replace Abstract: Many decision-making problems require ranking individuals by their treatment effects rather than estimating the exact effect magnitudes. Examples in

Rapid online deep artifact suppression for real-time spiral bSSFP CMR with blipped-CAIPI simultaneous multi-slice imaging at 1.5 T

arXiv:2605.26127v1 Announce Type: cross Abstract: Purpose: Real-time (RT) bSSFP MRI enables fast free-breathing cardiovascular imaging but requires 10-16 slices for functional assessment, resulting in

RAPNet: Accelerating Algebraic Multigrid with Learned Sparse Corrections

arXiv:2605.26854v1 Announce Type: new Abstract: The scalable solution of large sparse linear systems is a bottleneck in scientific computing and graph analysis. While algebraic multigrid (AMG) offers

Re-M3Dr: Rebalanced MultiModal Mean Deviation Regression

arXiv:2605.26513v1 Announce Type: new Abstract: Mean Deviation (MD) is a critical metric for assessing visual field loss in ophthalmology. While previous work has focused solely on predicting MD from

ReCA: Multi-Shot Long Video Extrapolation via Recursive Context Allocation

arXiv:2605.26525v1 Announce Type: cross Abstract: Minute-scale cinematic video generation is a central challenge for generative video models. Existing paradigms address only fragments of this challeng

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade

arXiv:2512.01572v3 Announce Type: replace-cross Abstract: Extreme sensor sparsity makes full-field reconstruction a fundamentally ill-posed problem in scientific sensing,where the goal is to infer phy

Recursive Flow Matching

arXiv:2605.26535v1 Announce Type: cross Abstract: Generative models have emerged as a powerful paradigm for solving physics systems and modeling complex spatiotemporal dynamics. However, achieving hig

Reformulation of RBM to Unify Linear and Nonlinear Dimensionality Reduction

arXiv:1909.08210v4 Announce Type: replace Abstract: A restricted Boltzmann machine (RBM) is a two-layer neural network with shared weights and has been extensively studied for dimensionality reduction

Reparametrizing Shampoo and SOAP for Subspace Basis Updates and BFloat16 Storage

arXiv:2605.26327v1 Announce Type: new Abstract: Shampoo-based methods, such as KL-Shampoo and SOAP, have demonstrated strong performance in training neural networks and rely on QR decomposition. Becau

RepoMirage: Probing Repository Context Reasoning in Code Agents with Perturbations

arXiv:2605.26177v1 Announce Type: cross Abstract: Code agents are currently having skillful performance on repository-level software engineering benchmarks, but it remains unclear whether success on e

Respecting Modality Gap in Post-hoc Out-of-distribution Detection with Pre-trained Vision-Language Models

arXiv:2605.26661v1 Announce Type: cross Abstract: Out-of-distribution (OOD) detection has emerged as a popular technique to enhance the reliability of machine learning models by identifying unexpected

Revealing the core dimensions underlying representations in brains, behavior and AI

arXiv:2605.26921v1 Announce Type: new Abstract: The study of representations is widespread across fields, including neuroscience, psychology, and artificial intelligence. While representations are oft

Rotation-Invariant Spherical Watermarking via Third-Order SO(3) Representation Coupling

arXiv:2605.26702v1 Announce Type: cross Abstract: Reliable watermarking of panoramic imagery is fundamentally challenged by arbitrary 3D rotations. As panoramas are defined on the sphere, they natural

Route Recommendations for Traffic Management Under Learned Partial Driver Compliance

arXiv:2504.02993v2 Announce Type: replace-cross Abstract: In this paper, we aim to mitigate congestion in traffic management systems by guiding travelers along system-optimal (SO) routes. However, we

Sampling Data with Chains of Forward-Backward Diffusion Steps

arXiv:2605.27006v1 Announce Type: new Abstract: Sampling from learned high-dimensional distributions is a foundational computational problem. We introduce U-turn chains: Markov chains obtained by iter

Scalable GANs with Transformers

arXiv:2509.24935v2 Announce Type: replace-cross Abstract: Scalability has driven recent advances in generative modeling, yet its principles remain underexplored for adversarial learning. We investigat

Searching the Internet for Challenging Benchmarks at Scale

arXiv:2509.26619v3 Announce Type: replace-cross Abstract: Many static benchmarks are beginning to saturate: as models rapidly improve, they achieve near-perfect scores on fixed test sets, leaving litt

Self-Cascaded Diffusion Models for Arbitrary-Scale Image Super-Resolution

arXiv:2506.07813v2 Announce Type: replace-cross Abstract: Arbitrary-scale image super-resolution aims to upsample images to any desired resolution, offering greater flexibility than traditional fixed-

Self-Intersection-Aware 3D Human Motion Generation Using an Efficient Human Sphere Proxy

arXiv:2605.26744v1 Announce Type: new Abstract: Human motion generation has made tremendous progress in recent years, with state-of-the-art approaches surpassing ground truth data in leading evaluatio

Shadow Unlearning: A Neuro-Semantic Approach to Fidelity-Preserving Faceless Forgetting in LLMs

arXiv:2601.04275v2 Announce Type: replace-cross Abstract: Machine unlearning aims to selectively remove the influence of specific training samples to satisfy privacy regulations such as the GDPR's 'Ri

Sleep-stage efficient classification using a lightweight self-supervised model

arXiv:2605.26295v1 Announce Type: new Abstract: Accurate classification of sleep stages is crucial for diagnosing sleep disorders and automating this process can significantly enhance clinical assessm

Slide Deck Q&A Quality Assurance App: A Multi-Stage Pipeline for Pedagogical Question Generation

arXiv:2605.26428v1 Announce Type: new Abstract: Generating high-quality, pedagogically useful questions from lecture slide decks is difficult because important instructional content is distributed acr

Small Object Detection in Industrial Recycling: A New Dataset and YOLO Performance Evaluation

arXiv:2605.26884v1 Announce Type: new Abstract: In this paper, we address the problem of detecting small, dense, and overlapping objects, a major challenge in computer vision. Our focus is on reviewin

SoftCap: Soft-Budget Control for Diffusion Transformer Acceleration

arXiv:2605.27075v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) achieve strong visual quality, but their iterative denoising process requires many costly Transformer evaluations. Trainin

Sparse-LiDAR Prompting of Monocular Geometry Foundations: An Empirical Study Toward Long-Range Driving Depth

arXiv:2605.26456v1 Announce Type: new Abstract: Sparse-LiDAR-prompted depth foundation models (PromptDA, Prior Depth Anything, DMD3C) have shown strong results on indoor scenes or within KITTI's stand

SPHERE-JEPA: Spherical Prediction with Homogeneous Embeddings

arXiv:2605.26900v1 Announce Type: new Abstract: A fundamental open question in self-supervised learning (SSL) is the explicit characterization of the optimal geometry of the learned representations. R

Stabilizing Recurrent Dynamics for Test-Time Scalable Latent Reasoning in Looped Language Models

arXiv:2605.26733v1 Announce Type: cross Abstract: Looped Language Models (LoopLMs) enable efficient latent reasoning through depth recurrence, yet exhibit unreliable test-time scaling behavior: perfor

Step-Size Stability in Stochastic Optimization: A Theoretical Perspective

arXiv:2602.09842v2 Announce Type: replace-cross Abstract: We present a theoretical analysis of stochastic optimization methods in terms of their sensitivity with respect to the step size. We identify

Structure-Adaptive Conformal Inference for Large-Scale Out-of-Distribution Testing

arXiv:2605.26429v1 Announce Type: cross Abstract: This paper addresses structured out-of-distribution (OOD) testing in high-stakes machine learning applications. Traditional conformal methods rely on

Stylistic Evolution and LLM Neutrality in Singlish Language

arXiv:2601.06580v2 Announce Type: replace Abstract: Singlish is a creole rooted in Singapore's multilingual environment that continues to evolve alongside social and technological change. We examine d

SWAP: Towards Copyright Auditing of Soft Prompts via Sequential Watermarking

arXiv:2511.04711v2 Announce Type: replace-cross Abstract: Large-scale vision-language models, especially CLIP, have demonstrated remarkable performance across diverse downstream tasks. Soft prompts, a

Symbolic Regression via Latent Iterative Refinement

arXiv:2605.27245v1 Announce Type: new Abstract: Symbolic regression (SR) seeks closed-form mathematical expressions that fit observed data. Neural SR methods amortize the search by training an encoder

TAG: Tangential Amplifying Guidance for Hallucination-Resistant Sampling

arXiv:2510.04533v2 Announce Type: replace Abstract: Diffusion models achieve state-of-the-art image generation but often produce semantic inconsistencies, or hallucinations. Existing inference-time gu

Tail-Aware HiFloat4: W4A4 Post-Training Quantization for Wan2.2

arXiv:2605.26628v1 Announce Type: new Abstract: This report describes Tail-Aware HiFloat4, our submission to the low-bit text-to-video generation quantization challenge. Our method adapts the public V