Search: “models”

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

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Model Releases

Learning to Forget: Continual Learning with Adaptive Weight Decay

DGX agent

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

model-releasesarxiv-cs-lg

1 May 2026

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

safetyarxiv-cs-ai

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

safetyarxiv-cs-ai

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

Tell-Tale Watermarks for Explanatory Reasoning in Synthetic Media Forensics

arXiv:2509.05753v2 Announce Type: replace-cross Abstract: The rise of synthetic media has blurred the boundary between reality and fabrication under the evolving power of artificial intelligence, fuel

To Build or Not to Build? Factors that Lead to Non-Development or Abandonment of AI Systems

arXiv:2604.28053v1 Announce Type: cross Abstract: Responsible AI research typically focuses on examining the use and impacts of deployed AI systems. Yet, there is currently limited visibility into the

Towards Accelerated SCF Workflows with Equivariant Density-Matrix Learning and Analytic Refinement

arXiv:2604.27256v1 Announce Type: cross Abstract: We present extsc{dm-PhiSNet}, a physically constrained extsc{PhiSNet}-based equivariant model that predicts one-electron reduced density matrices (1-R

Towards All-Day Perception for Off-Road Driving: A Large-Scale Multispectral Dataset and Comprehensive Benchmark

arXiv:2604.27499v1 Announce Type: new Abstract: Off-road nighttime autonomous driving suffers from unreliable visible-light perception, making infrared modality crucial for accurate freespace detectio

Training-Free Reward-Guided Image Editing via Trajectory Optimal Control

arXiv:2509.25845v3 Announce Type: replace-cross Abstract: Recent advancements in diffusion and flow-matching models have demonstrated remarkable capabilities in high-fidelity image synthesis. A promin

Tutorials

Transformer Semantic Genetic Programming for d-dimensional Symbolic Regression Problems

arXiv:2511.09416v2 Announce Type: replace Abstract: Transformer Semantic Genetic Programming (TSGP) is a semantic search approach that uses a pre-trained transformer model as a variation operator to g

tutorialsarxiv-cs-lg

TRUST: A Framework for Decentralized AI Service v.0.1

arXiv:2604.27132v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) and Multi-Agent Systems (MAS) in high-stakes domains demand reliable verification, yet centralized approaches suffer four

safetyarxiv-cs-ai

TypeBandit: Type-Level Context Allocation and Reweighting for Effective Attribute Completion in Heterogeneous Graph Neural Networks

arXiv:2604.27356v1 Announce Type: cross Abstract: Heterogeneous graphs are widely used to model multi-relational systems, but missing node attributes remain a major bottleneck for downstream learning.

Visual Analysis of Multi-outcome Causal Graphs

arXiv:2408.02679v3 Announce Type: replace Abstract: We introduce a visual analysis method for multiple causal graphs with different outcome variables, namely, multi-outcome causal graphs. Multi-outcom

WebMall -- A Multi-Shop Benchmark for Evaluating Web Agents

model-releasesarxiv-cs-cl

arXiv:2508.13024v3 Announce Type: replace Abstract: LLM-based web agents have the potential to automate long-running web tasks, such as searching for products in multiple e-shops and subsequently orde

Local Ai

When 2D Tasks Meet 1D Serialization: On Serialization Friction in Structured Tasks

arXiv:2604.27272v1 Announce Type: cross Abstract: Large language models (LLMs) conventionally process structured inputs as 1D token sequences. While natural for prose, such linearization may introduce

local-aiarxiv-cs-ai

Agents

When Agents Evolve, Institutions Follow

arXiv:2604.27691v1 Announce Type: new Abstract: Across millennia, complex societies have faced the same coordination problem of how to organize collective action among cognitively bounded and informat

agentsarxiv-cs-ai

WST-X Series: Wavelet Scattering Transform for Interpretable Speech Deepfake Detection

model-releasesarxiv-cs-cl

arXiv:2602.02980v2 Announce Type: replace-cross Abstract: In this work, we focus on front-end design for speech deepfake detectors, the component that determines the discriminative acoustic cues provi

A Multi-Dataset Benchmark of Multiple Instance Learning for 3D Neuroimage Classification

arXiv:2604.26807v1 Announce Type: new Abstract: Despite being resource-intensive to train, 3D convolutional neural networks (CNNs) have been the standard approach to classify CT and MRI scans. Recent

A Note on How to Remove the lnln T Term from the Squint Bound

arXiv:2604.26926v1 Announce Type: new Abstract: In Orabona and Pal [2016], we introduced the shifted KT potentials, to remove the ln ln T factor in the parameter-free learning with expert bound. In th

A self-evolving agent for explainable diagnosis of DFT-experiment band-gap mismatch

arXiv:2604.26703v1 Announce Type: cross Abstract: Standard density functional theory (DFT) routinely misclassifies the electronic ground state of correlated and structurally complex compounds, predict

Adaptive Scaling of Policy Constraints for Offline Reinforcement Learning

arXiv:2508.19900v2 Announce Type: replace Abstract: Offline reinforcement learning (RL) enables learning effective policies from fixed datasets without any environment interaction. Existing methods ty

Addressing Performance Saturation for LLM RL via Precise Entropy Curve Control

arXiv:2604.26326v1 Announce Type: cross Abstract: Reinforcement learning (RL) has unlocked complex reasoning abilities in large language models (LLMs). However, most RL algorithms suffer from performa

researcharxiv-cs-cl

Advancing multi-site emission control: A physics-informed transfer learning framework with mixture of experts for carbon-pollutant synergy

arXiv:2604.26571v1 Announce Type: new Abstract: Municipal solid waste incineration is increasingly central to urban waste management, yet its sustainability benefit depends on controlling carbon emiss

Agentic Search in the Wild: Intents and Trajectory Dynamics from 14M+ Real Search Requests

model-releasesarxiv-cs-cl

arXiv:2601.17617v3 Announce Type: replace-cross Abstract: LLM-powered search agents are increasingly being used for multi-step information seeking tasks, yet the IR community lacks empirical understan

Auditing Marketing Budget Allocation with Hindsight Regret

arXiv:2604.25977v1 Announce Type: cross Abstract: Organizations routinely make strategic budget allocations under operational constraints, but often lack a principled way to assess whether realized al

Auto-Relational Reasoning

arXiv:2604.26507v1 Announce Type: new Abstract: Background & Objectives: In the last decade, Machine learning research has grown rapidly, but large models are reaching their soft limits demonstrating