🤖 Category

cs.AI

2393 papers

SwiftEmbed: Ultra-Fast Text Embeddings via Static Token Lookup for Real-Time Applications

SwiftEmbed is a production-oriented, Rust-based serving system that achieves ultra-low latency (1.12 ms p50) and high throughput (50,000 RPS) for real-time applications by utilizing static token lookup and mean pooling on the distilled Potion-base-8M model, delivering strong performance in duplicate detection and semantic similarity tasks while trading off accuracy on complex classification and retrieval workloads compared to full transformer inference.

Edouard Lansiaux, Antoine Simonet, Eric Wiel2026-03-10💬 cs.CL

Detecting AI-Generated Images via Diffusion Snap-Back Reconstruction: A Forensic Approach

This paper proposes a forensic method called "diffusion snap-back reconstruction," which detects AI-generated images by analyzing how perceptual similarity metrics change when an image is perturbed and reconstructed by a diffusion model, achieving high accuracy (AUROC of 0.993) and robustness against common distortions without relying on traditional pixel-level artifacts.

Mohd Ruhul Ameen, Akif Islam2026-03-10💻 cs

Balancing Interpretability and Performance in Motor Imagery EEG Classification: A Comparative Study of ANFIS-FBCSP-PSO and EEGNet

This study compares a transparent ANFIS-FBCSP-PSO model with the deep-learning benchmark EEGNet on motor imagery EEG data, revealing that the fuzzy-neural approach offers superior within-subject performance and interpretability while EEGNet demonstrates stronger cross-subject generalization, thereby providing practical guidance for selecting BCI systems based on specific design priorities.

Farjana Aktar, Mohd Ruhul Ameen, Akif Islam, Md Ekramul Hamid2026-03-10🤖 cs.LG

Towards Efficient Federated Learning of Networked Mixture-of-Experts for Mobile Edge Computing

This paper proposes a Networked Mixture-of-Experts (NMoE) system and a hybrid federated learning framework that enable collaborative inference and efficient, privacy-preserving training of large AI models on resource-constrained mobile edge devices by leveraging neighbor expertise and balancing personalization with generalization.

Song Gao, Songyang Zhang, Shusen Jing, Shuai Zhang, Xiangwei Zhou, Yue Wang, Zhipeng Cai2026-03-10🤖 cs.LG

FATE: A Formal Benchmark Series for Frontier Algebra of Multiple Difficulty Levels

The paper introduces FATE, a new formal algebra benchmark series spanning from undergraduate exercises to PhD-level research problems, which reveals that current state-of-the-art LLMs struggle significantly with formalizing advanced mathematical reasoning, achieving near-zero accuracy on the most difficult tasks despite stronger natural-language performance.

Jiedong Jiang, Wanyi He, Yuefeng Wang, Guoxiong Gao, Yongle Hu, Jingting Wang, Nailin Guan, Peihao Wu, Chunbo Dai, Liang Xiao, Bin Dong2026-03-10🤖 cs.LG

Jr. AI Scientist and Its Risk Report: Autonomous Scientific Exploration from a Baseline Paper

This paper introduces "Jr. AI Scientist," an autonomous system that mimics a novice researcher's workflow to generate novel, scientifically valuable papers building on real academic works, while simultaneously evaluating its performance through rigorous automated and human assessments to identify both its capabilities and the significant risks and limitations of current AI-driven scientific exploration.

Atsuyuki Miyai, Mashiro Toyooka, Takashi Otonari, Zaiying Zhao, Kiyoharu Aizawa2026-03-10🤖 cs.LG

Think, Speak, Decide: Language-Augmented Multi-Agent Reinforcement Learning for Economic Decision-Making

The paper proposes LAMP, a language-augmented multi-agent reinforcement learning framework that employs a "Think-Speak-Decide" pipeline to integrate unstructured language with numerical data, significantly outperforming existing baselines in economic decision-making through improved cumulative returns, robustness, and interpretability.

Heyang Ma, Qirui Mi, Qipeng Yang, Zijun Fan, Bo Li, Haifeng Zhang2026-03-10💻 cs

UnfoldLDM: Deep Unfolding-based Blind Image Restoration with Latent Diffusion Priors

The paper proposes UnfoldLDM, a deep unfolding framework that integrates a multi-granularity degradation-aware module for robust degradation estimation and a degradation-resistant latent diffusion model with an over-smoothing correction transformer to effectively address blind image restoration by overcoming degradation-specific dependencies and suppressing over-smoothing bias.

Chunming He, Rihan Zhang, Zheng Chen, Bowen Yang, Chengyu Fang, Yunlong Lin, Yulun Zhang, Fengyang Xiao, Sina Farsiu2026-03-10💻 cs

Yo'City: Personalized and Boundless 3D Realistic City Scene Generation via Self-Critic Expansion

This paper introduces Yo'City, an agentic framework that leverages large models for hierarchical planning and a self-critic expansion loop to generate personalized, boundless, and spatially coherent 3D realistic city scenes, outperforming existing state-of-the-art methods across multiple evaluation metrics.

Keyang Lu, Sifan Zhou, Hongbin Xu, Gang Xu, Zhifei Yang, Yikai Wang, Zhen Xiao, Jieyi Long, Ming Li2026-03-10💻 cs

ForamDeepSlice: A High-Accuracy Deep Learning Framework for Foraminifera Species Classification from 2D Micro-CT Slices

This study introduces ForamDeepSlice, a high-accuracy deep learning framework that combines an ensemble of ConvNeXt-Large and EfficientNetV2-Small models with a rigorous specimen-level split dataset to achieve 95.64% accuracy in classifying foraminifera species from 2D micro-CT slices, while also providing an interactive dashboard for real-time identification and 3D matching.

Abdelghafour Halimi, Ali Alibrahim, Didier Barradas-Bautista, Ronell Sicat, Abdulkader M. Afifi2026-03-10🤖 cs.LG

Integrating a Causal Foundation Model into a Prescriptive Maintenance Framework for Optimising Production-Line OEE

This paper proposes a prescriptive maintenance framework that integrates a pre-trained causal foundation model as a "what-if" simulator to identify root causes and recommend optimal interventions, thereby overcoming the limitations of purely predictive models to enhance production-line Overall Equipment Effectiveness (OEE).

Felix Saretzky, Lucas Andersen, Thomas Engel, Fazel Ansari2026-03-10💻 cs