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A Dual-Positive Monotone Parameterization for Multi-Segment Bids and a Validity Assessment Framework for Reinforcement Learning Agent-based Simulation of Electricity Markets

arXiv:2604.10252v1 Announce Type: new Abstract: Reinforcement learning agent-based simulation (RL-ABS) has become an important tool for electricity market mechanism analysis and evaluation. In the mod

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Research

A Faster Path to Continual Learning

DGX agent

arXiv:2604.11064v1 Announce Type: cross Abstract: Continual Learning (CL) aims to train neural networks on a dynamic stream of tasks without forgetting previously learned knowledge. Among optimization

researcharxiv-cs-cv

14 Apr 2026

A Full Compression Pipeline for Green Federated Learning in Communication-Constrained Environments

arXiv:2604.11146v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, thereby preserving privacy. However, F

local-aiarxiv-cs-lg

Applications

A Heavy-Load-Enhanced and Changeable-Periodicity-Perceived Workload Prediction Network

arXiv:2308.01917v3 Announce Type: replace-cross Abstract: Cloud providers can greatly benefit from accurate workload prediction. However, the workload of cloud servers is highly variable, with occasio

applicationsarxiv-cs-lg

A Hessian-Free Actor-Critic Algorithm for Bi-Level Reinforcement Learning with Applications to LLM Fine-Tuning

arXiv:2601.16399v5 Announce Type: replace Abstract: We study a structured bi-level optimization problem where the upper-level objective is a smooth function and the lower-level problem is policy optim

safetyarxiv-cs-lg

A Hybrid Intelligent Framework for Uncertainty-Aware Condition Monitoring of Industrial Systems

model-releasesarxiv-cs-ai

arXiv:2604.09932v1 Announce Type: cross Abstract: Hybrid approaches that combine data-driven learning with physics-based insight have shown promise for improving the reliability of industrial conditio

A-IO: Adaptive Inference Orchestration for Memory-Bound NPUs

arXiv:2604.09752v1 Announce Type: cross Abstract: During the deployment of Large Language Models (LLMs), the autoregressive decoding phase on heterogeneous NPU platforms (e.g., Ascend 910B) faces seve

A Mamba-Based Multimodal Network for Multiscale Blast-Induced Rapid Structural Damage Assessment

arXiv:2604.11709v1 Announce Type: new Abstract: Accurate and rapid structural damage assessment (SDA) is crucial for post-disaster management, helping responders prioritise resources, plan rescues, an

A Mathematical Explanation of Transformers

arXiv:2510.03989v2 Announce Type: replace-cross Abstract: The Transformer architecture has revolutionized the field of sequence modeling and underpins the recent breakthroughs in large language models

A mathematical theory of evolution for self-designing AIs

arXiv:2604.05142v2 Announce Type: replace Abstract: As artificial intelligence systems (AIs) become increasingly produced by recursive self-improvement, a form of evolution may emerge, with the traits

A Mechanistic Analysis of Looped Reasoning Language Models

arXiv:2604.11791v1 Announce Type: cross Abstract: Reasoning has become a central capability in large language models. Recent research has shown that reasoning performance can be improved by looping an

tutorialsarxiv-cs-ai

A Metamorphic Testing Perspective on Knowledge Distillation for Language Models of Code: Does the Student Deeply Mimic the Teacher?

arXiv:2511.05476v4 Announce Type: replace-cross Abstract: Transformer-based language models of code have achieved state-of-the-art performance across a wide range of software analytics tasks, but thei

A Minimal Mathematical Model for Conducting Patterns

model-releasesarxiv-cs-ro

arXiv:2604.10356v1 Announce Type: cross Abstract: We present a minimal mathematical model for conducting patterns that separates geometric trajectory from temporal parametrization. The model is based

A Minimal Model of Representation Collapse: Frustration, Stop-Gradient, and Dynamics

arXiv:2604.09979v1 Announce Type: cross Abstract: Self-supervised representation learning is central to modern machine learning because it extracts structured latent features from unlabeled data and e

A Modular Zero-Shot Pipeline for Accident Detection, Localization, and Classification in Traffic Surveillance Video

arXiv:2604.09685v1 Announce Type: new Abstract: We describe a zero-shot pipeline developed for the ACCIDENT @ CVPR 2026 challenge. The challenge requires predicting when, where, and what type of traff

local-aiarxiv-cs-cv

A Modularized Framework for Piecewise-Stationary Restless Bandits

arXiv:2604.10177v1 Announce Type: cross Abstract: We study the piecewise-stationary restless multi-armed bandit (PS-RMAB) problem, where each arm evolves as a Markov chain but mean rewards may change

A molecular clock for writing systems reveals the quantitative impact of imperial power on cultural evolution

arXiv:2604.10957v1 Announce Type: cross Abstract: Writing systems are cultural replicators whose evolution has never been studied quantitatively at global scale. We compile the Global Script Database

A Multi-head Attention Fusion Network for Industrial Prognostics under Discrete Operational Conditions

arXiv:2604.10248v1 Announce Type: new Abstract: Complex systems such as aircraft engines, turbines, and industrial machinery often operate under dynamically changing conditions. These varying operatin

A Multilingual Dataset and Empirical Validation for the Mutual Reinforcement Effect in Information Extraction

arXiv:2407.10953v5 Announce Type: replace Abstract: The Mutual Reinforcement Effect (MRE) describes a phenomenon in information extraction where word-level and sentence-level tasks can mutually improv

safetyarxiv-cs-cl

Applications

A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis

arXiv:2412.20495v2 Announce Type: replace-cross Abstract: The proliferation of real-world health data enables multi-institutional survival studies, yet privacy constraints preclude centralizing sensit

applicationsarxiv-cs-ai

A Progressive Training Strategy for Vision-Language Models to Counteract Spatio-Temporal Hallucinations in Embodied Reasoning

arXiv:2604.10506v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have made significant strides in static image understanding but continue to face critical hurdles in spatiotemporal reason

A Proposed Biomedical Data Policy Framework to Reduce Fragmentation, Improve Quality, and Incentivize Sharing in Indian Healthcare in the era of Artificial Intelligence and Digital Health

arXiv:2604.11125v1 Announce Type: new Abstract: India generates vast biomedical data through postgraduate research, government hospital services and audits, government schemes, private hospitals and t

A Quantitative Definition of Intelligence

arXiv:2604.10873v1 Announce Type: new Abstract: We propose an operational, quantitative definition of intelligence for arbitrary physical systems. The intelligence density of a system is the ratio of

A Queueing-Theoretic Framework for Dynamic Attack Surfaces: Data-Integrated Risk Analysis and Adaptive Defense

arXiv:2604.10427v1 Announce Type: cross Abstract: We develop a queueing-theoretic framework to model the temporal evolution of cyber-attack surfaces, where the number of active vulnerabilities is repr

A Ray Intersection Algorithm for Fast Growth Distance Computation Between Convex Sets

model-releasesarxiv-cs-ro

arXiv:2604.10058v1 Announce Type: new Abstract: In this paper, we discuss an efficient algorithm for computing the growth distance between two compact convex sets with representable support functions.

A robust and adaptive MPC formulation for Gaussian process models

arXiv:2507.02098v2 Announce Type: replace-cross Abstract: In this paper, we present a robust and adaptive model predictive control (MPC) framework for uncertain nonlinear systems affected by bounded d

tutorialsarxiv-cs-lg

A Structured Clustering Approach for Inducing Media Narratives

arXiv:2604.10368v1 Announce Type: new Abstract: Media narratives wield tremendous power in shaping public opinion, yet computational approaches struggle to capture the nuanced storytelling structures

researcharxiv-cs-cl

A Survey of Inductive Reasoning for Large Language Models

arXiv:2510.10182v2 Announce Type: replace-cross Abstract: Reasoning is an important task for large language models (LLMs). Among all the reasoning paradigms, inductive reasoning is one of the fundamen

A Survey on 3D Gaussian Splatting Applications: Segmentation, Editing, and Generation

arXiv:2508.09977v4 Announce Type: replace Abstract: In the context of novel view synthesis, 3D Gaussian Splatting (3DGS) has recently emerged as an efficient and competitive counterpart to Neural Radi

researcharxiv-cs-cv

Agents

A Survey on Deep Learning Techniques for Action Anticipation

arXiv:2309.17257v2 Announce Type: replace Abstract: The ability to anticipate possible future human actions is essential for a wide range of applications, including autonomous driving and human-robot

agentsarxiv-cs-cv

A Systematic Analysis of the Impact of Persona Steering on LLM Capabilities

arXiv:2604.11048v1 Announce Type: cross Abstract: Imbuing Large Language Models (LLMs) with specific personas is prevalent for tailoring interaction styles, yet the impact on underlying cognitive capa

A Tale of Two Temperatures: Simple, Efficient, and Diverse Sampling from Diffusion Language Models

arXiv:2604.09921v1 Announce Type: new Abstract: Much work has been done on designing fast and accurate sampling for diffusion language models (dLLMs). However, these efforts have largely focused on th

tutorialsarxiv-cs-lg

A Temporally Augmented Graph Attention Network for Affordance Classification

arXiv:2604.10149v1 Announce Type: cross Abstract: Graph attention networks (GATs) provide one of the best frameworks for learning node representations in relational data; but, existing variants such a

A Triadic Suffix Tokenization Scheme for Numerical Reasoning

arXiv:2604.11582v1 Announce Type: cross Abstract: Standard subword tokenization methods fragment numbers inconsistently, causing large language models (LLMs) to lose positional and decimal structure -

A Two-Stage Dual-Modality Model for Facial Emotional Expression Recognition

arXiv:2603.12221v2 Announce Type: replace Abstract: This paper addresses the expression (EXPR) recognition challenge in the 10th Affective Behavior Analysis in-the-Wild (ABAW) workshop and competition

local-aiarxiv-cs-cv

A Unified Theory of Sparse Dictionary Learning in Mechanistic Interpretability: Piecewise Biconvexity and Spurious Minima

arXiv:2512.05534v4 Announce Type: replace-cross Abstract: As AI models achieve remarkable capabilities across diverse domains, understanding what representations they learn and how they encode concept

tutorialsarxiv-cs-ai

A Weak Penalty Neural ODE for Learning Chaotic Dynamics from Noisy Time Series

model-releasesarxiv-cs-lg

arXiv:2511.06609v3 Announce Type: replace Abstract: The accurate forecasting of complex, high-dimensional dynamical systems from observational data is a fundamental task across numerous scientific and

A3-FPN: Asymptotic Content-Aware Pyramid Attention Network for Dense Visual Prediction

arXiv:2604.10210v1 Announce Type: new Abstract: Learning multi-scale representations is the common strategy to tackle object scale variation in dense prediction tasks. Although existing feature pyrami

researcharxiv-cs-cv

AbLWR:A Context-Aware Listwise Ranking Framework for Antibody-Antigen Binding Affinity Prediction via Positive-Unlabeled Learning

arXiv:2604.11272v1 Announce Type: cross Abstract: Accurate prediction of antibody-antigen binding affinity is fundamental to therapeutic design, yet remains constrained by severe label sparsity and th

tutorialsarxiv-cs-ai

ABot-Claw: A Foundation for Persistent, Cooperative, and Self-Evolving Robotic Agents

arXiv:2604.10096v1 Announce Type: new Abstract: Current embodied intelligent systems still face a substantial gap between high-level reasoning and low-level physical execution in open-world environmen

local-aiarxiv-cs-cv

Absorption and Inertness in Coarse-Grained Arithmetic: A Heuristic Application to the St. Petersburg Paradox

arXiv:2507.12475v2 Announce Type: replace-cross Abstract: The St. Petersburg paradox presents a longstanding challenge in decision theory: its classical expected value diverges, yet no correspondingly

AC-MIL: Weakly Supervised Atrial LGE-MRI Quality Assessment via Adversarial Concept Disentanglement

model-releasesarxiv-cs-cv

arXiv:2604.10303v1 Announce Type: new Abstract: High-quality Late Gadolinium Enhancement (LGE) MRI can be helpful for atrial fibrillation management, yet scan quality is frequently compromised by pati

Accelerated Dopant Screening in Oxide Semiconductors via Multi-Fidelity Contextual Bandits and a Three-Tier DFT Validation Funnel

model-releasesarxiv-cs-lg

arXiv:2604.10157v1 Announce Type: cross Abstract: Band gap engineering of oxide semiconductors through doping is critical for photocatalysis and optoelectronics, yet the combinatorial space of dopant

ACCIDENT: A Benchmark Dataset for Vehicle Accident Detection from Traffic Surveillance Videos

model-releasesarxiv-cs-ai

arXiv:2604.09819v1 Announce Type: cross Abstract: We introduce ACCIDENT, a benchmark dataset for traffic accident detection in CCTV footage, designed to evaluate models in supervised (IID and OOD) and

Agents

AccidentSim: Generating Vehicle Collision Videos with Physically Realistic Collision Trajectories from Real-World Accident Reports

arXiv:2503.20654v4 Announce Type: replace-cross Abstract: Collecting real-world vehicle accident videos for autonomous driving research is challenging due to their rarity and complexity. While existin

agentsarxiv-cs-ai

ACE-Bench: A Lightweight Benchmark for Evaluating Azure SDK Usage Correctness

model-releasesarxiv-cs-ai

arXiv:2604.09564v1 Announce Type: cross Abstract: We present ACE-Bench (Azure SDK Coding Evaluation Benchmark), an execution-free benchmark that provides fast, reproducible pass or fail signals for wh

Agents

ACE-TA: An Agentic Teaching Assistant for Grounded Q&A, Quiz Generation, and Code Tutoring

arXiv:2604.09572v1 Announce Type: cross Abstract: We introduce ACE-TA, the Agentic Coding and Explanations Teaching Assistant framework, that autonomously routes conceptual queries drawn from programm

agentsarxiv-cs-ai

Achieving Skilled and Reliable Daily Probabilistic Forecasts of Wind Power at Subseasonal-to-Seasonal Timescales over France

arXiv:2511.16164v2 Announce Type: replace Abstract: In a growing renewable based energy system, accurate and reliable wind power forecasts are crucial for grid stability, balancing supply and demand a