Search: “models”

Bayesian X-Learner: Calibrated Posterior Inference for Heterogeneous Treatment Effects under Heavy-Tailed Outcomes

arXiv:2604.27394v1 Announce Type: cross Abstract: Conditional Average Treatment Effect (CATE) estimation in practice demands three properties simultaneously: heterogeneous effects au(x), calibrated un

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Safety

ClipTBP: Clip-Pair based Temporal Boundary Prediction with Boundary-Aware Learning for Moment Retrieval

DGX agent

arXiv:2604.27591v1 Announce Type: cross Abstract: Video moment retrieval is the task of retrieving specific segments of a video corresponding to a given text query. Recent studies have been conducted

safetyarxiv-cs-ai

1 May 2026

Tutorials

Constraint-Aware Flow Matching via Randomized Exploration

arXiv:2508.13316v2 Announce Type: replace Abstract: We consider the problem of designing constraint-aware flow matching (FM) models that address the issue of constraint violations commonly observed in

tutorialsarxiv-cs-lg

Contextual Agentic Memory is a Memo, Not True Memory

arXiv:2604.27707v1 Announce Type: new Abstract: Current agentic memory systems (vector stores, retrieval-augmented generation, scratchpads, and context-window management) do not implement memory: they

Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing

arXiv:2604.27883v1 Announce Type: cross Abstract: In modern parametric model training, full-batch gradient descent (and its variants) suffers due to progressively stronger biasing towards the exact re

Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards

arXiv:2603.09117v2 Announce Type: replace-cross Abstract: Reinforcement Learning from Verifiable Rewards (RLVR) significantly enhances large language models (LLMs) reasoning but severely suffers from

EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures

arXiv:2604.27004v1 Announce Type: cross Abstract: We propose EdgeSpike, a co-designed spiking neural network (SNN) framework for autonomous low-power sensing in edge Internet of Things (IoT) architect

Evaluating Epistemic Guardrails in AI Reading Assistants: A Behavioral Audit of a Minimal Prototype

arXiv:2604.27275v1 Announce Type: cross Abstract: Large language model (LLM) reading assistants are increasingly used in settings that require interpretation rather than simple retrieval. In these con

Evaluating TabPFN for Mild Cognitive Impairment to Alzheimer's Disease Conversion in Data Limited Settings

arXiv:2604.27195v1 Announce Type: new Abstract: Accurate prediction of conversion from Mild Cognitive Impairment (MCI) to Alzheimers Diseases (AD) is essential for early intervention, however, develop

Fake3DGS: A Benchmark for 3D Manipulation Detection in Neural Rendering

arXiv:2604.27590v1 Announce Type: new Abstract: Recent advances in 3D reconstruction and neural rendering,particularly 3D Gaussian Splatting, make it feasible and simple to edit 3D scenes and re-rende

Applications

FiLMMeD: Feature-wise Linear Modulation for Cross-Problem Multi-Depot Vehicle Routing

arXiv:2604.28102v1 Announce Type: new Abstract: Solving practical multi-depot vehicle routing problems (MDVRP) is a challenging optimization task central to modern logistics, increasingly driven by e-

applicationsarxiv-cs-lg

Gait Recognition via Deep Residual Networks and Multi-Branch Feature Fusion

arXiv:2604.27353v1 Announce Type: new Abstract: Gait recognition has emerged as a compelling biometric modality for surveillance and security applications, offering inherent advantages such as non-int

Generalizable Sparse-View 3D Reconstruction from Unconstrained Images

arXiv:2604.28193v1 Announce Type: new Abstract: Reconstructing 3D scenes from sparse, unposed images remains challenging under real-world conditions with varying illumination and transient occlusions.

Generate Your Talking Avatar from Video Reference

arXiv:2604.27918v1 Announce Type: new Abstract: Existing talking avatar methods typically adopt an image-to-video pipeline conditioned on a static reference image within the same scene as the target g

Hardware

GraphMend: Code Transformations for Fixing Graph Breaks in PyTorch 2

arXiv:2509.16248v3 Announce Type: replace-cross Abstract: This paper presents GRAPHMEND, a high-level compiler technique that eliminates FX graph breaks in PyTorch 2 programs. Although PyTorch 2 intro

hardwarearxiv-cs-lg

HiMix: Hierarchical Artifact-aware Mixup for Generalized Synthetic Image Detection

arXiv:2604.27903v1 Announce Type: new Abstract: The rapid evolution of generative models has enabled the creation of highly realistic and diverse synthetic images, posing significant challenges to rel

researcharxiv-cs-cv

How Generative AI Disrupts Search: An Empirical Study of Google Search, Gemini, and AI Overviews

arXiv:2604.27790v1 Announce Type: cross Abstract: Generative AI is being increasingly integrated into web search for the convenience it provides users. In this work, we aim to understand how generativ

Agents

Imitation Game for Adversarial Disillusion with Chain-of-Thought Reasoning in Generative AI

arXiv:2501.19143v2 Announce Type: replace Abstract: As the cornerstone of artificial intelligence, machine perception confronts a fundamental threat posed by adversarial illusions. These adversarial a

agentsarxiv-cs-ai

In-Context Examples Suppress Scientific Knowledge Recall in LLMs

arXiv:2604.27540v1 Announce Type: new Abstract: Scientific reasoning rarely stops at what is directly observable; it often requires uncovering hidden structure from data. From estimating reaction cons

Agents

In-Context Prompting Obsoletes Agent Orchestration for Procedural Tasks

arXiv:2604.27891v1 Announce Type: new Abstract: Agent orchestration frameworks -- LangGraph, CrewAI, Google ADK, OpenAI Agents SDK, and others -- place an external orchestrator above the LLM, tracking

agentsarxiv-cs-ai

K2MUSE: A human lower-limb multimodal walking dataset spanning task and acquisition variability for rehabilitation robotics

arXiv:2504.14602v2 Announce Type: replace-cross Abstract: The natural interaction and control performance of lower limb rehabilitation robots are closely linked to biomechanical information from vario

Learning from Disagreement: Clinician Overrides as Implicit Preference Signals for Clinical AI in Value-Based Care

arXiv:2604.28010v1 Announce Type: cross Abstract: We reframe clinician overrides of clinical AI recommendations as implicit preference data - the same signal structure exploited by reinforcement learn

Learning Rate Engineering: From Coarse Single Parameter to Layered Evolution

arXiv:2604.27295v1 Announce Type: new Abstract: Learning rate scheduling has evolved from the single global fixed rate of early SGD to sophisticated layer-wise adaptive strategies. We systematize this

Learning to Forget: Continual Learning with Adaptive Weight Decay

arXiv:2604.27063v1 Announce Type: new Abstract: Continual learning agents with finite capacity must balance acquiring new knowledge with retaining the old. This requires controlled forgetting of knowl

MAEO: Multiobjective Animorphic Ensemble Optimization for Scalable Large-scale Engineering Applications

arXiv:2604.26973v1 Announce Type: cross Abstract: Multiobjective optimization remains challenging for many scientific and engineering problems due to the need to balance convergence, diversity, and co

Mapping how LLMs debate societal issues when shadowing human personality traits, sociodemographics and social media behavior

arXiv:2604.27624v1 Announce Type: cross Abstract: Large Language Models (LLMs) can strongly shape social discourse, yet datasets investigating how LLM outputs vary across controlled social and context

Monitoring Neural Training with Topology: A Footprint-Predictable Collapse Index

arXiv:2604.26984v1 Announce Type: new Abstract: Representational collapse, where embeddings become anisotropic and lose multi-scale structure, can erode downstream performance long before performance

Tutorials

NORACL: Neurogenesis for Oracle-free Resource-Adaptive Continual Learning

arXiv:2604.27031v1 Announce Type: cross Abstract: In a continual learning setting, we require a model to be plastic enough to learn a new task and stable enough to not disturb previously learned capab

tutorialsarxiv-cs-ai

One Pass, Any Order: Position-Invariant Listwise Reranking for LLM-Based Recommendation

arXiv:2604.27599v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for recommendation reranking, but their listwise predictions can depend on the order in which candi

Parameter-Efficient Architectural Modifications for Translation-Invariant CNNs

arXiv:2604.27870v1 Announce Type: new Abstract: Convolutional Neural Networks (CNNs) are widely assumed to be translation-invariant, yet standard architectures exhibit a startling fragility: even a si

People-Centred Medical Image Analysis

arXiv:2604.26991v1 Announce Type: cross Abstract: Recent advances in data-centric medical AI have produced highly accurate diagnostic systems, but the emphasis on data curation and performance metrics

Preserving Temporal Dynamics in Time Series Generation

arXiv:2604.27182v1 Announce Type: cross Abstract: Time-series data augmentation plays a crucial role in regression-oriented forecasting tasks, where limited data restricts the performance of deep lear

PROMISE-AD: Progression-aware Multi-horizon Survival Estimation for Alzheimer's Disease Progression and Dynamic Tracking

arXiv:2604.28055v1 Announce Type: cross Abstract: Individualized Alzheimer's disease (AD) progression prediction requires models that use irregular visits, account for censoring, avoid diagnostic leak

Applications

PRTS: A Primitive Reasoning and Tasking System via Contrastive Representations

arXiv:2604.27472v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models advance robotic control via strong visual-linguistic priors. However, existing VLAs predominantly frame pretraining

applicationsarxiv-cs-ai

Local Ai

RAY-TOLD: Ray-Based Latent Dynamics for Dense Dynamic Obstacle Avoidance with TDMPC

arXiv:2604.27450v1 Announce Type: cross Abstract: Dense, dynamic crowds pose a persistent challenge for autonomous mobile robots. Purely reactive planning methods, such as Model Predictive Path Integr

local-aiarxiv-cs-ai

Applications

Reliable Answers for Recurring Questions: Boosting Text-to-SQL Accuracy with Template Constrained Decoding

arXiv:2604.28028v1 Announce Type: cross Abstract: Large language models (LLMs) have revolutionized Text-to-SQL generation, allowing users to query structured data using natural language with growing e

applicationsarxiv-cs-ai

Remaining Useful Life Estimation for Turbofan Engines: A Comparative Study of Classical, CNN, and LSTM Approaches

arXiv:2604.27234v1 Announce Type: new Abstract: Remaining Useful Life (RUL) estimation is a critical component of Prognostics and Health Management (PHM), enabling proactive maintenance scheduling and

Representative Spectral Correlation Network for Multi-source Remote Sensing Image Classification

arXiv:2604.27323v1 Announce Type: cross Abstract: Hyperspectral image (HSI) and SAR/LiDAR data offer complementary spectral and structural information for land-cover classification. However, their eff

REVIVE 3D: Refinement via Encoded Voluminous Inflated prior for Volume Enhancement

arXiv:2604.27504v1 Announce Type: new Abstract: Recent generative models have shown strong performance in generating diverse 3D assets from 2D images, a fundamental research topic in computer vision a

researcharxiv-cs-cv

Sampling two-dimensional spin systems with transformers

arXiv:2604.27738v1 Announce Type: cross Abstract: Autoregressive Neural Networks based on dense or convolutional layers have recently been shown to be a viable strategy for generating classical spin s

SCOPE-FE: Structured Control of Operator and Pairwise Exploration for Feature Engineering

arXiv:2604.27025v1 Announce Type: cross Abstract: Automatic feature engineering is an effective approach for improving predictive performance in tabular learning. However, expand-and-reduce methods, s

SECOS: Semantic Capture for Rigorous Classification in Open-World Semi-Supervised Learning

arXiv:2604.27596v1 Announce Type: new Abstract: In open-world semi-supervised learning (OWSSL), a model learns from labeled data and unlabeled data containing both known and novel classes. In practica

researcharxiv-cs-cv

Agents

Security Attack and Defense Strategies for Autonomous Agent Frameworks: A Layered Review with OpenClaw as a Case Study

arXiv:2604.27464v1 Announce Type: cross Abstract: Autonomous agent frameworks built upon large language models (LLMs) are evolving into complex, tool-integrated, and continuously operating systems, in

agentsarxiv-cs-ai

Signature Kernel Scoring Rule: A Spatio-Temporal Diagnostic for Probabilistic Weather Forecasting

arXiv:2510.19110v2 Announce Type: replace-cross Abstract: Modern weather forecasting has increasingly transitioned from numerical weather prediction (NWP) to data-driven machine learning forecasting t

Softmax-GS: Generalized Gaussians Learning When to Blend or Bound

arXiv:2604.27437v1 Announce Type: new Abstract: 3D Gaussian Splatting (3D GS) is widely adopted for novel view synthesis due to its high training and rendering efficiency. However, its efficiency reli

Stable but Wrong: An Inference Limit in Galactic Archaeology

arXiv:2604.27368v1 Announce Type: new Abstract: Statistical inference in observational science typically relies on a fundamental assumption: as sample size increases and uncertainties decrease, the in

State-Dependent Lyapunov Method for Rank-1 Matrix Factorization

arXiv:2604.26993v1 Announce Type: cross Abstract: We study gradient descent for rank-1 matrix factorization through a certificate-based viewpoint. The central object is a parameterized quadratic certi

Supercharging Agenda Setting Research: The ParlaCAP Dataset of 28 European Parliaments and a Scalable Multilingual LLM-Based Classification

arXiv:2602.16516v2 Announce Type: replace Abstract: This paper introduces ParlaCAP, a large-scale dataset for analyzing parliamentary agenda setting across Europe, and proposes a cost-effective method

safetyarxiv-cs-cl