Ax Mani Rash Ahmadi 9d ago

The Phase Is the Gradient: Equilibrium Propagation for Frequency Learning in Kuramoto Networks

Theoretical analysis proving phase displacement in Kuramoto oscillator networks equals gradient of loss for frequency learning.

Ax Jie Shi, Siamak Mehrkanoon 9d ago

A Diffusion-Contrastive Graph Neural Network with Virtual Nodes for Wind Nowcasting in Unobserved Regions

Graph neural network with diffusion-contrastive learning for wind nowcasting in regions lacking dense observation networks.

Ax Adil Derrazi, Javad Pourmostafa Roshan Sharami 9d ago

Integrating SAINT with Tree-Based Models: A Case Study in Employee Attrition Prediction

Combines SAINT attention mechanism with tree-based models like XGBoost for improved employee attrition prediction on tabular HR data.

Ax Jiaqi Wen, Pingbo Tang, Shaolei Ren, Jianyi Yang 9d ago

WaterAdmin: Orchestrating Community Water Distribution Optimization via AI Agents

AI agents for optimizing community water distribution systems by scheduling pumps and valves to meet demands while minimizing energy in dynamic real-world environments.

Ax Muhammad Imran Hossain, Md Fazley Rafy, Sarika Khushlani Solanki, Anurag K. Srivastava 9d ago

Battery health prognosis using Physics-informed neural network with Quantum Feature mapping

Combines physics-informed neural networks with quantum feature mapping for battery state-of-health estimation across chemistries.

Ax Rui Chen, Jinsong Wu 9d ago

Structural Gating and Effect-aligned Lag-resolved Temporal Causal Discovery Framework with Application to Heat-Pollution Extremes

Proposes SGED-TCD framework for lag-resolved causal discovery in multivariate time series with applications to environmental data.

Ax Zhe Ye, Aidan Z. H. Yang, Huangyuan Su, Zhenyu Liao, Samuel Tenka, Zhizhen Qin, Udaya Ghai, Dawn Song, Soonho Kong 9d ago

Intent-aligned Formal Specification Synthesis via Traceable Refinement

Presents VeriSpecGen for automatic formal specification synthesis from natural language using LLMs with traceability for code verification.

Ax Eric Easley, Sebastian Farquhar 9d ago

Latent Instruction Representation Alignment: defending against jailbreaks, backdoors and undesired knowledge in LLMs

Introduces LIRA method to defend LLMs against jailbreaks, backdoors, and unlearning by training models to align instruction representation.

Ax Elahe Khatibi, Ziyu Wang, Ankita Sharma, Krishnendu Chakrabarty, Sanaz Rahimi Moosavi, Farshad Firouzi, Amir Rahmani 9d ago

CARE-ECG: Causal Agent-based Reasoning for Explainable and Counterfactual ECG Interpretation

Proposes CARE-ECG, causal agent-based reasoning framework for explainable ECG interpretation combining LLMs with physiological structure.

Ax Ziyu Wang, Elahe Khatibi, Ankita Sharma, Krishnendu Chakrabarty, Sanaz Rahimi Moosavi, Farshad Firouzi, Amir Rahmani 9d ago

Membership Inference Attacks Expose Participation Privacy in ECG Foundation Encoders

Demonstrates membership inference attacks on ECG foundation encoders, exposing participation privacy risks in self-supervised pretraining.

Ax Naichuan Zheng, Hailun Xia, Zepeng Sun, Weiyi Li, Yinze Zhou 9d ago

Towards Green Wearable Computing: A Physics-Aware Spiking Neural Network for Energy-Efficient IMU-based Human Activity Recognition

Proposes physics-aware spiking neural networks for energy-efficient wearable IMU-based human activity recognition on edge devices.

Ax Candi Zheng, Yuan Lan 9d ago

Rethinking the Diffusion Model from a Langevin Perspective

Organizes diffusion model fundamentals from Langevin perspective, offering simplified mathematical framework for beginners.

Ax Ye Su, Mingrui Ye, Yining Wang, Jipeng Guo, Yong Liu 9d ago

Exact Finite-Sample Variance Decomposition of Subagging: A Spectral Filtering Perspective

Derives exact finite-sample variance decomposition for subagging ensembles, providing mathematical characterization of resampling ratios.

Ax Xiangyang Yin, Xingyu Liu, Tianhua Xia, Bo Bao, Vithursan Thangarasa, Valavan Manohararajah, Eric Sather, Sai Qian Zhang 9d ago

CodeQuant: Unified Clustering and Quantization for Enhanced Outlier Smoothing in Low-Precision Mixture-of-Experts

Proposes CodeQuant for quantizing mixture-of-experts models by combining clustering and quantization to handle outlier-induced errors.

Ax Jiahui Zhang, Rouyi Wang, Kuangqi Zhou, Tianshu Xiao, Lingyan Zhu, Yaosen Min, Yang Wang 9d ago

PepBenchmark: A Standardized Benchmark for Peptide Machine Learning

Introduces PepBenchmark, standardized benchmark with datasets and protocols for peptide drug discovery machine learning.

Ax Yuzhen Mao, Qitong Wang, Martin Ester, Ke Li 9d ago

IceCache: Memory-efficient KV-cache Management for Long-Sequence LLMs

Presents IceCache for memory-efficient KV-cache management in long-sequence LLMs via CPU offloading and selective GPU retention.

Ax Shunyu Wu, Jiawei Huang, Weibin Feng, Boxin Li, Xiao Zhang, Erli Meng, Dan Li, Jian Lou, See-Kiong Ng 9d ago

WaveMoE: A Wavelet-Enhanced Mixture-of-Experts Foundation Model for Time Series Forecasting

Proposes WaveMoE, a mixture-of-experts foundation model for time series forecasting using wavelet-enhanced frequency-domain information.

Ax Nikodem Tomczak 9d ago

Heterogeneous Connectivity in Sparse Networks: Fan-in Profiles, Gradient Hierarchy, and Topological Equilibria

Proposes Profiled Sparse Networks with heterogeneous connectivity patterns, benchmarked on vision and tabular classification tasks.

Ax Kewei Zhu, Cameron Wilson, Bartosz Mazur, Yi Li, Ashleigh M. Chester, Peyman Z. Moghadam 9d ago

ReadMOF: Structure-Free Semantic Embeddings from Systematic MOF Nomenclature for Machine Learning

Introduces ReadMOF framework using chemical nomenclature and pretrained language models for metal-organic framework property prediction.

Ax Subramanyam Sahoo 9d ago

Calibration Collapse Under Sycophancy Fine-Tuning: How Reward Hacking Breaks Uncertainty Quantification in LLMs

Studies how reward hacking during RLHF fine-tuning degrades LLM calibration and uncertainty quantification despite improving helpfulness.

Ax Giacomo Cignoni, Simone Magistri, Andrew D. Bagdanov, Antonio Carta 9d ago

Preventing Latent Rehearsal Decay in Online Continual SSL with SOLAR

Explores online continual self-supervised learning with focus on stability-plasticity trade-off in models learning from unlabeled streaming data.

Ax Luis Balderas, Miguel Lastra, Jos\'e M. Ben\'itez 9d ago

MoEITS: A Green AI approach for simplifying MoE-LLMs

MoEITS: green AI approach for reducing computational burden of Mixture-of-Experts LLMs through simplification.

Ax Aviraj Newatia, Michael Cooper, Viet Nguyen, Rahul G. Krishnan 9d ago

Mitigating Privacy Risk via Forget Set-Free Unlearning

Machine unlearning method for removing training data influence without direct access to forget sets.

Ax Rajveer Singh 9d ago

SpectralLoRA: Is Low-Frequency Structure Sufficient for LoRA Adaptation? A Spectral Analysis of Weight Updates

Spectral analysis of LoRA weight updates showing low-frequency dominance enables efficient parameter-efficient fine-tuning.

Ax Haihui Xie, Wenkun Wen, Shuwu Chen, Zhaogang Shu, Minghua Xia 9d ago

Energy-Efficient Federated Edge Learning For Small-Scale Datasets in Large IoT Networks

Federated learning framework for IoT networks with energy efficiency optimization for small-scale datasets.

Ax Hao Wang, Guozhi Wang, Han Xiao, Yufeng Zhou, Yue Pan, Jichao Wang, Ke Xu, Yafei Wen, Xiaohu Ruan, Xiaoxin Chen, Honggang Qi 9d ago

Skill-SD: Skill-Conditioned Self-Distillation for Multi-turn LLM Agents

Self-distillation method for multi-turn LLM agents using skill-conditioning to improve sample efficiency in reinforcement learning.

Ax Binbin Zheng, Xing Ma, Yiheng Liang, Jingqing Ruan, Xiaoliang Fu, Kepeng Lin, Benchang Zhu, Ke Zeng, Xunliang Cai 9d ago

SCOPE: Signal-Calibrated On-Policy Distillation Enhancement with Dual-Path Adaptive Weighting

On-policy distillation method for LLM alignment with adaptive weighting based on signal quality and credit assignment.

Ax Xun Qian, Alexander Gaponov, Grigory Malinovsky, Peter Richt\'arik 9d ago

Communication-Efficient Gluon in Federated Learning

Communication-efficient optimization method extending Muon for federated learning of large language models.

Ax Zikang Shan, Han Zhong, Liwei Wang, Li Zhao 9d ago

Bringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning

Revisits value modeling in LLM reinforcement learning using generative critics for improved credit assignment.

Ax Giansalvo Cirrincione 9d ago

INCRT: An Incremental Transformer That Determines Its Own Architecture

Transformer architecture that dynamically determines its own depth and width during training by pruning redundant heads.

Ax Dheeraj Mudireddy, Sai Patibandla 9d ago

PokeRL: Reinforcement Learning for Pokemon Red

Reinforcement learning benchmark for Pokemon Red game with long horizons, sparse rewards, and complex control mechanics.

Ax Yijin Ni, Xiaoming Huo 9d ago

Online Covariance Estimation in Averaged SGD: Improved Batch-Mean Rates and Minimax Optimality via Trajectory Regression

Improved online covariance estimation for averaged SGD with minimax-optimal convergence rates via trajectory regression.

Ax Francesco D'Angelo, Nicolas Flammarion 9d ago

Transformers Learn Latent Mixture Models In-Context via Mirror Descent

Theoretical framework explaining how transformers learn in-context via mirror descent over mixture of transition distributions.

Ax Cristiano Mafuz, Rodrigo Silva 9d ago

Task2vec Readiness: Diagnostics for Federated Learning from Pre-Training Embeddings

Proposes readiness indices based on Task2Vec embeddings to predict federated learning performance before training.

Ax Zhiyang Xun, Eric Price 9d ago

Query Lower Bounds for Diffusion Sampling

Establishes first information-theoretic lower bounds for score query complexity in diffusion model sampling.

Ax Yang Yan, Qiuyan Wang, Tianjin Huang, Qiudong Yu, Kexin Zhang 9d ago

DIB-OD: Preserving the Invariant Core for Robust Heterogeneous Graph Adaptation via Decoupled Information Bottleneck and Online Distillation

Graph neural network domain adaptation method using information bottleneck and online distillation for robustness to distribution shifts.

Ax Zhen Qin, Jiachen Jiang, Zhihui Zhu 9d ago

Learning to Adapt: In-Context Learning Beyond Stationarity

Theoretical analysis of in-context learning in transformers beyond stationary settings, explaining how models adapt without parameter updates.

Ax Prateek Chanda, Prayas Agrawal, Karthik S. Gurumoorthy, Ganesh Ramakrishnan, Bamdev Mishra, Pratik Jawanpuria 9d ago

UniPROT: Uniform Prototype Selection via Partial Optimal Transport with Submodular Guarantees

Subset selection framework using optimal transport for prototype selection with better handling of minority classes.

Ax Zhiheng Zhou, Mengyao Zhou, Xixun Lin, Xingqin Qi, Guiying Yan 9d ago

Hypergraph Neural Diffusion: A PDE-Inspired Framework for Hypergraph Message Passing

Novel framework for hypergraph neural networks using PDE-inspired diffusion equations to address oversmoothing and improve message passing.

Ax Erhan Bayraktar, Bingyan Han, Ziqing Zhang 9d ago

Continuous-time Online Learning via Mean-Field Neural Networks: Regret Analysis in Diffusion Environments

Theoretical analysis of continuous-time online learning with two-layer neural networks in diffusion environments, establishing regret bounds.

Ax Minxing Zheng, Zewei Deng, Liyan Xie, Shixiang Zhu 9d ago

Learning to Test: Physics-Informed Representation for Dynamical Instability Detection

ML approach using physics-informed representations to detect dynamical instability in safety-critical systems described by differential equations.

Ax Mintae Kim, Koushil Sreenath 9d ago

Robust Adversarial Policy Optimization Under Dynamics Uncertainty

Dual formulation approach for robust reinforcement learning under distribution shift, addressing instability in adversarial RL methods.

Ax Zhuolun Dong, Junyu Cao 9d ago

Flow-Controlled Scheduling for LLM Inference with Provable Stability Guarantees

Scheduling algorithm for LLM inference with provable stability when decode lengths are unknown, addressing memory overflow challenges in production systems.

Ax Jon-Paul Cacioli 9d ago

K-Way Energy Probes for Metacognition Reduce to Softmax in Discriminative Predictive Coding Networks

Theoretical result showing K-way energy probes in predictive coding networks reduce to softmax, explaining apparent richness of per-hypothesis energy signals.

Ax Jialu Pan, Yufeng Zhang, Nan Hu, Keqin Li 9d ago

Optimal Stability of KL Divergence under Gaussian Perturbations

Theoretical analysis of KL divergence stability under Gaussian perturbations for non-Gaussian distributions, applicable to OOD detection with flow-based generative models.

Ax Tao Wang, Suhang Zheng, Xiaoxiao Xu 9d ago

RTMC: Step-Level Credit Assignment via Rollout Trees

Rollout tree-based credit assignment method for multi-step agentic RL, leveraging implicit state overlap between group rollouts to avoid uniform advantage assignment.

Ax Yuhang He, Haodong Wu, Siyi Liu, Hongyu Ge, Hange Zhou, Keyi Wu, Zhuo Zheng, Qihong Lin, Zixin Zhong, Yongqi Zhang 9d ago

Rethinking Token-Level Credit Assignment in RLVR: A Polarity-Entropy Analysis

Analysis of credit assignment in reinforcement learning with verifiable rewards using polarity-entropy decomposition to diagnose token update patterns in LLM reasoning.

Ax Ziqian Zhong, Aashiq Muhamed, Mona T. Diab, Virginia Smith, Aditi Raghunathan 9d ago

Pando: Do Interpretability Methods Work When Models Won't Explain Themselves?

Benchmark evaluating mechanistic interpretability methods under conditions where model explanations are absent, controlling for elicitation confounding effects.

Ax Wei Li, Hangjie Yuan, Zixiang Zhao, Borui Kang, Ziwei Liu, Tao Feng 9d ago

A Faster Path to Continual Learning

Optimization technique for continual learning reducing computational overhead of C-Flat while maintaining ability to balance new and old task performance.

Ax Linggang Kong, Lei Wu, Yunlong Zhang, Xiaofeng Zhong, Zhen Wang, Yongjie Wang, Yao Pan 9d ago

CausalGaze: Unveiling Hallucinations via Counterfactual Graph Intervention in Large Language Models

Method for detecting LLM hallucinations using counterfactual graph intervention to identify causal mechanisms, moving beyond passive signal-based classification approaches.