Ax Erik Hartman, Jonas Wallin, Johan Malmstr\"om, Jimmy Olsson 27d ago

Controllable protein design with particle-based Feynman-Kac steering

Feynman-Kac framework for guiding diffusion-based generative models toward proteins with specified properties and tailored structures.

Ax Wei-Kai Chang, Rajiv Khanna 27d ago

A Unified Stability Analysis of SAM vs SGD: Role of Data Coherence and Emergence of Simplicity Bias

Unified stability analysis comparing SAM and SGD optimization algorithms showing role of data coherence and simplicity bias in generalization.

Ax Yaw Osei Adjei (Kwame Nkrumah University of Science,Technology, Kumasi, Ghana), Frederick Ayivor (Independent Researcher, Fishers, Indiana, USA) 27d ago

Semantic Superiority vs. Forensic Efficiency: A Comparative Analysis of Deep Learning and Psycholinguistics for Business Email Compromise Detection

Comparative analysis of transformer models (DistilBERT) versus psycholinguistic features for detecting business email compromise attacks.

Ax Yifan Song, Fenglin Yu, Yihong Luo, Xingjian Tao, Siya Qiu, Kai Han, Jing Tang 27d ago

Mitigating Structural Overfitting: A Distribution-Aware Rectification Framework for Missing Feature Imputation

Framework addressing structural overfitting in graph neural networks for missing feature imputation using distribution-aware rectification.

Ax Xun Li, Qiong Wu, Pingyi Fan, Kezhi Wang, Wen Chen, Cui Zhang 27d ago

Personalized Federated Distillation Assisted Vehicle Edge Caching Strategy

Federated learning approach for vehicle edge caching using personalized distillation to predict user content preferences while preserving privacy.

Ax Stefano Goria, Levent A. Meng\"ut\"urk, Murat C. Meng\"ut\"urk, Berkan Sesen 27d ago

Random-Bridges as Stochastic Transports for Generative Models

Random-bridges framework for generative models using stochastic processes conditioned on target distributions for flexible transport between distributions.

Ax Fangzhou Lin, Guoshun He, Zhenyu Guo, Zhe Huang, Jinsong Tao 27d ago

GRAFT: Grid-Aware Load Forecasting with Multi-Source Textual Alignment and Fusion

Electric load forecasting model integrating multi-source textual data (news, social media, policies) with temporal grid-aware predictions.

Ax Additi Pandey, Liang Wei, Hessam Babaee, George Em Karniadakis 27d ago

Kinetic-Mamba: Mamba-Assisted Predictions of Stiff Chemical Kinetics

Mamba-based neural operator framework for accurate chemical kinetics modeling in combustion simulations using efficient temporal modeling.

Ax Haoye Lu, Yaoliang Yu, Darren Lo 27d ago

SFBD-OMNI: Bridge models for lossy measurement restoration with limited clean samples

Distribution restoration method using noisy samples and optimal transport to recover fully observed data from partial corrupted observations.

Ax Zihua Yang, Xin Liao, Yiqun Zhang, Yiu-ming Cheung 27d ago

Bridging the Semantic Gap for Categorical Data Clustering via Large Language Models

Method using large language models to measure semantic similarity in categorical data clustering by bridging gap in attribute distance representation.

Ax Jiacheng Lyu, Bihua Bao, Shiyun Yan 27d ago

ASSS: A Differentiable Adversarial Framework for Task-Aware Data Reduction

Differentiable adversarial framework for task-aware data reduction using learnable selector and minimax optimization to identify informative samples.

Ax Kaiyuan Deng, Hangyu Zheng, Minghai Qing, Kunxiong Zhu, Gen Li, Yang Xiao, Lan Emily Zhang, Linke Guo, Bo Hui, Yanzhi Wang, Geng Yuan, Gagan Agrawal, Wei Niu, Xiaolong Ma 27d ago

From Bits to Chips: An LLM-based Hardware-Aware Quantization Agent for Streamlined Deployment of LLMs

LLM-based hardware-aware quantization agent automating model quantization for efficient LLM deployment on resource-constrained hardware.

Ax Nicola Aladrah, Emanuele Ballarin, Matteo Biagetti, Alessio Ansuini, Alberto d'Onofrio, Fabio Anselmi 27d ago

Understanding and inverse design of implicit bias in stochastic learning: a geometric perspective

Theoretical analysis of implicit bias in stochastic learning using geometric perspective to explain solution selection in overparameterized models.

Ax Aakriti Lnu, Zhe Li, Dandan Liang, Chao Huang, Rui Li, Haibo Yang 27d ago

HOSL: Hybrid-Order Split Learning for Memory-Constrained Edge Training

Split learning optimization method reducing memory overhead for LLM training on edge devices using hybrid-order optimization instead of first-order approaches.

Ax Weinuo Ou 27d ago

Auxiliary-predicted Compress Memory Model(ApCM Model): A Neural Memory Storage Model Based on Invertible Compression and Learnable Prediction

Neural memory storage architecture for LLMs with invertible compression and learnable prediction for runtime memory.

Ax Lv Tang, Tianyi Zheng, Bo Li, Xingyu Li 27d ago

InfoTok: Information-Theoretic Regularization for Capacity-Constrained Shared Visual Tokenization in Unified MLLMs

Information-theoretic approach for designing shared visual tokenizers in unified multimodal LLMs.

Ax Jiacheng Liang, Yuhui Wang, Tanqiu Jiang, Ting Wang 27d ago

RASA: Routing-Aware Safety Alignment for Mixture-of-Experts Models

Safety alignment framework addressing unique challenges of sparse routing in Mixture-of-Experts language models.

Ax Rong Fu, WeiZhi Tang, Ziming Wang, Jia Yee Tan, Zijian Zhang, Zhaolu Kang, Muge Qi, Shuning Zhang, Simon Fong 27d ago

ModalImmune: Immunity Driven Unlearning via Self Destructive Training

Training framework for multimodal systems to maintain performance when input channels are lost at deployment.

Ax Yongsheng Chen, Yong Chen, Wei Guo, Xinghui Zhong 27d ago

Unlearning Noise in PINNs: A Selective Pruning Framework for PDE Inverse Problems

Pruning framework for physics-informed neural networks to improve robustness to noise in PDE inverse problems.

Ax Dongik Park, Hyunwoo Ryu, Suahn Bae, Keondo Park, Hyung-Sin Kim 27d ago

T1: One-to-One Channel-Head Binding for Multivariate Time-Series Imputation

Time series imputation method using channel-head binding for handling diverse missing patterns.

Ax Zonglin Yang, Lidong Bing 27d ago

MOOSE-Star: Unlocking Tractable Training for Scientific Discovery by Breaking the Complexity Barrier

Training method for LLMs to directly model generative reasoning process in scientific discovery applications.

Ax Micky C Nnamdi, Wenqi Shi, Cheng Wan, J. Ben Tamo, Benjamin M Smith, Chad A Purnell, May D Wang 27d ago

KindSleep: Knowledge-Informed Diagnosis of Obstructive Sleep Apnea from Oximetry

Deep learning framework for diagnosing obstructive sleep apnea from oximetry data with clinical knowledge integration.

Ax Addison Kalanther, Sanika Bharvirkar, Shankar Sastry, Chinmay Maheshwari 27d ago

NePPO: Near-Potential Policy Optimization for General-Sum Multi-Agent Reinforcement Learning

Multi-agent reinforcement learning algorithm for general-sum games with convergence guarantees in heterogeneous agent settings.

Ax Ganzhao Yuan 27d ago

OptEMA: Adaptive Exponential Moving Average for Stochastic Optimization with Zero-Noise Optimality

Optimization algorithm extending exponential moving average with adaptive rates and zero-noise optimality guarantees.

Ax Simon Roth 27d ago

A Grammar of Machine Learning Workflows

Formal grammar framework preventing data leakage in ML workflows through structural constraints and assessment gates.

Ax Yuning Wu, Ke Wang, Devin Chen, Kai Wei 27d ago

Hindsight-Anchored Policy Optimization: Turning Failure into Feedback in Sparse Reward Settings

Reinforcement learning method for post-training reasoning models using hindsight feedback in sparse reward environments.

Ax Ninghui Li, Kaiyuan Zhang, Kyle Polley, Jerry Ma 27d ago

Security Considerations for Artificial Intelligence Agents

Security considerations and recommendations for AI agents from Perplexity based on operating agentic systems in production environments.

Ax Angelika Romanou, Mark Ibrahim, Candace Ross, Chantal Shaib, Kerem Oktar, Samuel J. Bell, Anaelia Ovalle, Jesse Dodge, Antoine Bosselut, Koustuv Sinha, Adina Williams 27d ago

Brittlebench: Quantifying LLM robustness via prompt sensitivity

Framework for measuring LLM robustness to prompt variations, typos, and alternative phrasings in real-world inputs.

Ax Kushal Khemani (Independent Researcher, India), Anjum Nazir Qureshi (Rajiv Gandhi College of Engineering Research,Technology) 27d ago

AI-Driven Predictive Maintenance with Environmental Context Integration for Connected Vehicles: Simulation, Benchmarking, and Field Validation

Predictive maintenance framework for connected vehicles integrating sensor and environmental data with ML models.

Ax Yanghao Li, Changxin Liu, Yuhao Yi 27d ago

Accelerating Byzantine-Robust Distributed Learning with Compressed Communication via Double Momentum and Variance Reduction

Distributed learning algorithm combining Byzantine robustness with communication compression for collaborative ML systems.

Ax Zijin Gu, Tatiana Likhomanenko, Vimal Thilak, Jason Ramapuram, Navdeep Jaitly 27d ago

Path-Constrained Mixture-of-Experts

Research on sparse Mixture-of-Experts architectures proposing expert path perspective to understand token routing patterns across layers.

Ax Amir Asiaee, Samhita Pal 27d ago

Improving RCT-Based CATE Estimation Under Covariate Mismatch via Calibrated Alignment

CALM: method for heterogeneous treatment effect estimation combining RCT and observational study data with covariate mismatch.

Ax Luca Ambrogioni 27d ago

How Out-of-Equilibrium Phase Transitions can Seed Pattern Formation in Trained Diffusion Models

Theoretical analysis of pattern formation in diffusion models explained via out-of-equilibrium phase transitions.

Ax Anqi Dong, Yongxin Chen, Karl H. Johansson, Johan Karlsson 27d ago

Learning Sampled-data Control for Swarms via MeanFlow

MeanFlow-based learning approach for controlling large-scale swarms with limited sampled-data updates.

Ax Amirmohammad Ziaei Bideh, Jonathan Gryak 27d ago

LLM-ODE: Data-driven Discovery of Dynamical Systems with Large Language Models

LLM-ODE: uses LLMs to discover governing equations of dynamical systems from data, improving on genetic programming approaches.

Ax Foo Hui-Mean, Yuan-chin I Chang 27d ago

ALMAB-DC: Active Learning, Multi-Armed Bandits, and Distributed Computing for Sequential Experimental Design and Black-Box Optimization

ALMAB-DC: sequential experimental design framework combining active learning, multi-armed bandits and distributed computing for black-box optimization.

Ax Dip Roy, Rajiv Misra, Sanjay Kumar Singh, Anisha Roy 27d ago

Posterior-Calibrated Causal Circuits in Variational Autoencoders: Why Image-Domain Interpretability Fails on Tabular Data

Investigates interpretability of VAEs across modalities, showing image-domain causal circuits fail to generalize to tabular data.

Ax Dongxia Wu, Yuhui Zhang, Serena Yeung-Levy, Emma Lundberg, Emily B. Fox 27d ago

Uncertainty Quantification for Distribution-to-Distribution Flow Matching in Scientific Imaging

Uncertainty quantification methods for distribution-to-distribution flow matching models in scientific imaging applications.

Ax Dongxia Wu, Shiye Su, Yuhui Zhang, Elaine Sui, Emma Lundberg, Emily B. Fox, Serena Yeung-Levy 27d ago

CellFluxRL: Biologically-Constrained Virtual Cell Modeling via Reinforcement Learning

CellFluxRL: reinforcement learning post-training approach for virtual cell models with biologically-constrained generative models.

Ax Panayiotis Panayiotou, \"Ozg\"ur \c{S}im\c{s}ek 27d ago

Causal Discovery in Action: Learning Chain-Reaction Mechanisms from Interventions

Causal discovery method for chain-reaction systems using interventional data on cascade-structured dynamical systems.

Ax Rustem Islamov, Grigory Malinovsky, Alexander Gaponov, Aurelien Lucchi, Peter Richt\'arik, Eduard Gorbunov 27d ago

Byzantine-Robust and Differentially Private Federated Optimization under Weaker Assumptions

Federated learning approach combining Byzantine robustness and differential privacy for distributed training.

Ax Dogan Urgun, Gokhan Gungor 27d ago

Large Language Model Guided Incentive Aware Reward Design for Cooperative Multi-Agent Reinforcement Learning

Framework using LLMs to automatically design auxiliary reward programs for cooperative multi-agent reinforcement learning systems.

Ax Fabio Ferreira, Lucca Wobbe, Arjun Krishnakumar, Frank Hutter, Arber Zela 27d ago

Can LLMs Beat Classical Hyperparameter Optimization Algorithms? A Study on autoresearch

Compares LLM agents against classical hyperparameter optimization algorithms using autoresearch testbed for tuning small language models.

Ax Haishan Ye 27d ago

Optimal High-Probability Regret for Online Convex Optimization with Two-Point Bandit Feedback

Theoretical analysis of online convex optimization with two-point bandit feedback achieving tight regret bounds.

Ax Christopher Cruz 27d ago

ATLAS-RTC: Closing the Loop on LLM Agent Output with Token-Level Runtime Control

ATLAS-RTC: runtime control system for LLM agents enforcing structured output via token-level monitoring, biasing, masking and rollback.

Ax Yufei Xu, Fanxu Meng, Fan Jiang, Yuxuan Wang, Ruijie Zhou, Zhaohui Wang, Jiexi Wu, Zhixin Pan, Xiaojuan Tang, Wenjie Pei, Tongxuan Liu, Di Yin, Xing Sun, Muhan Zhang 27d ago

HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention

HISA: hierarchical indexing system for efficient sparse attention in LLMs, reducing indexer bottleneck in token-level sparse mechanisms.

Ax Ya Zhou, Tianxiang Hao, Ziyi Cai, Haojie Zhu, Kejun He, Jia Liu, Xiaohan Fan, Jing Yuan 27d ago

Detecting low left ventricular ejection fraction from ECG using an interpretable and scalable predictor-driven framework

Develops interpretable ML framework for detecting low left ventricular ejection fraction from ECG data.

Ax Ikechukwu Uchendu, Swati Goel, Karly Hou, Ebrahim Songhori, Kuang-Huei Lee, Joe Wenjie Jiang, Vijay Janapa Reddi, Vincent Zhuang 27d ago

See it to Place it: Evolving Macro Placements with Vision-Language Models

Applies Vision-Language Models to chip floorplanning macro placement optimization tasks.

Ax Liliang Ren, Yang Liu, Yelong Shen, Weizhu Chen 27d ago

Rethinking Language Model Scaling under Transferable Hypersphere Optimization

Introduces HyperP, hypersphere parameterization for LLM scaling with improved stability and hyperparameter transfer.

Ax Ivan Pasichnyk 27d ago

Beta-Scheduling: Momentum from Critical Damping as a Diagnostic and Correction Tool for Neural Network Training

Proposes time-varying momentum schedule derived from critically damped harmonic oscillator for neural network training optimization.