Ax Meng Wang, Haohan Zhao, Wenzhuo Liu, Lu Yang, Geng Liu, Haiyang Guo, Guo-Sen Xie, Gaofeng Meng, Hongbin Liu, Fei Zhu 9d ago

Denser $\neq$ Better: Limits of On-Policy Self-Distillation for Continual Post-Training

Analysis of self-distillation for continual post-training showing trade-offs between in-domain specialization and knowledge preservation.

Ax Marianne Arriola, Volodymyr Kuleshov 9d ago

Set Diffusion: Interpolating Token Orderings Between Autoregression and Diffusion for Fast and Flexible Decoding

Discrete diffusion model for language generation combining autoregressive and diffusion decoding with flexible token ordering.

Ax Jiaxing Wang, Kaitao Chen, Zhubin Han, Chenyu Hou, Bin Cao, Jing Fan, Ji Zhang 9d ago

EHHN: An Event-driven Heterogeneous Hypergraph Network for Object-Centric Next Activity Prediction

Event-driven hypergraph network for predicting next activity in object-centric business process logs.

Ax Ahin Lee, Sehyun Yun, Taesik Gong 9d ago

EPnG: Adaptive Expert Prune-and-Grow for Parameter-Efficient MoE Fine-tuning

Adaptive prune-and-grow framework for parameter-efficient fine-tuning of Mixture-of-Experts models using LoRA.

Ax Rowan Hussein, Mohamed Ouf 9d ago

Single-Channel EEG-Based Cognitive Load Assessment in Online Learning: A Hybrid Deep Learning Approach

Deep learning approach for assessing cognitive load from single-channel EEG data during online education.

Ax Rodrigo Mendoza-Smith 9d ago

Expander Sparse Autoencoders: Parameter-Efficient Dictionaries for Mechanistic Interpretability

Parameter-efficient sparse autoencoders for interpreting neural network activations using expander graphs.

Ax Jiatong Li, Weida Wang, Changmeng Zheng, Shufei Zhang, Yatao Bian, Xiao-yong Wei, Qing Li 9d ago

Do LLMs Truly Generalize in the Molecular Domain? A Perturbation-Based Analysis

Research on whether LLMs generalize in molecular discovery tasks beyond local neighborhoods of sequence representations.

Ax Nikil Roashan Selvam, Jay Baxter, Sophie Hilgard, Brad Miller, Keith Coleman, Ellen Vitercik, Sanmi Koyejo 9d ago

Gaming Consensus: Coordinated Manipulation in Crowdsourced Fact-Checking

Study of coordinated manipulation attacks on crowdsourced fact-checking systems used by social media platforms.

Ax Dazhi Fu, Jiuding Yang, Yiwen Guo, Jicong Fan 9d ago

Many Voices, One Reward: Multi-Role Rubric Generation for LLM Judging and Reward Modeling

Multi-role rubric generation for LLM evaluation addressing dimensional blind spots in preference-based reward modeling.

Ax Emmanuel C. Chukwu, Rianne M. Schouten, Monique Tabak, Mykola Pechenizkiy 9d ago

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data

Adaptive group-based counterfactual explanations for multivariate time-series classifiers in rehabilitation movement analysis.

Ax Yewon Kim, Apurva Gandhi, David Chung, Graham Neubig, Chris Donahue 9d ago

Decomposer: Learning to Decompile Symbolic Music to Programs

Decomposer: LLM post-training framework for symbolic music decompilation recovering executable music programs from MIDI.

Ax Jen-Yen Chang, Takayuki Osa, Tatsuya Harada 9d ago

Learning the Supports for Categorical Critic in Reinforcement Learning

Gaussian Histogram Loss for learning support distributions in distributional reinforcement learning value functions.

Ax Francis Bach (SIERRA) 9d ago

Regularized Variational and Spectral Log-Density-Ratio Estimation in the Gaussian Location Model

Theoretical study of ridge-regularized log-density-ratio estimation in Gaussian location models with spectral methods.

Ax Yuriy Maksyuta, George Bredis, Ruslan Rakhimov, Daniil Gavrilov 9d ago

Rank-Then-Act: Reward-Free Control from Frame-Order Progress

Rank-Then-Act: Reward-free policy learning from expert videos using vision-language models and ordinal scoring.

Ax Yidan Xu, Xiangmin Han, Rundong Xue, Huihui Ye 9d ago

SABER: A Semantic-Aligned Brain Network Analysis Framework via Multi-scale Hypergraphs

SABER: Brain network analysis framework integrating LLM semantics with multi-scale hypergraphs for disease diagnosis.

Ax Francisco Sede\~no, Francisco Chicano, Jamal Toutouh 9d ago

Population-Based Multi-Objective Training of Discriminators for Semi-Supervised GANs

Population-based evolutionary training for semi-supervised GANs formulated as multi-objective optimization problem.

Ax Zhiren Gong, Zihao Zeng, Chau Yuen, Wei Yang Bryan Lim 9d ago

Conditional Co-Ablation: Recovering Self-Repair Backups in Transformer Circuits

Mechanistic interpretability study of transformer self-repair mechanisms during ablation using conditional co-ablation analysis.

Ax Giacomo Cappiello, Filippo Caruso, Xing Liang, Dimitrios Makris 9d ago

Hybrid quantum-classical neural network for sentiment analysis

Hybrid quantum-classical neural network for sentiment analysis on COVID-19 tweets using TF-IDF vectorization.

Ax Koki Konishi, Masataka Ushiku, Yuta Saito 9d ago

A More Accurate Algorithm Comparison through A/B Testing using Offline Evaluation Methods

Offline evaluation methods for algorithm comparison offering safer alternative to A/B testing with improved accuracy analysis.

Ax Benedikt Kaas, Manuel Treutlein, Hannes Benedikt Gerber, Oliver Neumann, Cheewan Phatthanakhuha, Oliver Resch, Ralf Mikut, Veit Hagenmeyer 9d ago

Probabilistic Low-Voltage Peak Load Forecasting with Time Series Foundation Models Evaluated on Application-Oriented Metrics

Time series foundation models for low-voltage load forecasting with uncertainty estimation and application-oriented evaluation metrics.

Ax Tasnim Shahriar 9d ago

Do Newer Lightweight CNNs Perform Better Under Resource Constraints? A Controlled Multigenerational Study of Architecture, Initialization, Training Budget, and Efficiency

Controlled comparison of nine lightweight CNN architectures across CIFAR-10/100 and Tiny ImageNet under resource constraints.

Ax Weizhi Nie, Weijie Wang, Yuting Su 9d ago

Liquid Latent State Dynamics for Interpretable Turbofan Degradation Modeling

Liquid neural networks for turbofan degradation modeling with interpretable latent state dynamics on C-MAPSS benchmark.

Ax Emanuele Mele, Massimo Cafaro, Angelo Coluccia, Italo Epicoco 9d ago

Fast and Accurate Anomaly Detection in Time Series

Survey of anomaly detection methods for time series across cybersecurity, finance, healthcare, and IoT domains.

Ax Yuval Ran-Milo, Angelos Assos, Elad Hazan 9d ago

A Memory Efficient Unified Algorithm for Online Learning of Linear Dynamical Systems

Online learning algorithm for linear dynamical systems with memory efficiency and sublinear regret guarantees.

Ax Prathamesh Patil, Arpit Jain, Aswanth Krishnan 9d ago

Beyond the Performance Illusion: Structure-Aware Stratified Partitioning and Curriculum Distributionally Robust Optimization for Spatially Correlated Domains

Analysis of dataset split failures in spatiotemporally correlated domains, proposing stratified partitioning and curriculum robust optimization.

Ax Yang Li, Pan Hu, Yan Zhang, Wenfan Yang, Tao Wu, Lianbo Guo 9d ago

SA-HGNN: Sample-Adaptive Hyperbolic Graph Neural Network for EEG-Based Depression Recognition

SA-HGNN: Graph neural network for EEG-based depression recognition using hyperbolic geometry to capture brain network hierarchies.

Ax Mahmoud Abdelfattah, Hamid Nasiri, Peter Garraghan 9d ago

kNNGuard: Turning LLM Hidden Activations into a Training-Free Configurable Guardrail

kNNGuard: Training-free guardrail for LLMs using activation space and k-NN to detect unsafe/adversarial prompts without fine-tuning.

Ax Chelsea Maria John, Thibaut Lunet, Sebastian G\"otschel, Andreas Herten, Stefan Kesselheim, Daniel Ruprecht 9d ago

Fourier Neural Operators for Rayleigh-B\'enard Convection

Improved Fourier Neural Operator for modeling Rayleigh-Bénard convection with compact model predicting time increments instead of full solutions.

Ax Jian Xu, Delu Zeng, John Paisley, Qibin Zhao 9d ago

Ask the Right Comparison:Bias-Aware Bayesian Active Top-$k$ Ranking with LLM Judges

Bayesian active ranking method using LLM judges to identify top-k candidates while accounting for systematic biases and position effects.

Ax Varshith Roy Kotla 9d ago

Predictive Conformal Slip Monitoring: An Empirical Evaluation of Rolling Split Conformal Prediction for Pre-Incident Traction Loss Detection

Rolling Split Conformal Prediction applied to pre-incident traction loss detection in automotive systems using per-driver models.

Ax Yilie Huang, Wenpin Tang, Xun Yu Zhou 9d ago

ART for Diffusion Sampling: Continuous-Time Control and Actor-Critic Learning

ART: continuous-time control framework using actor-critic learning to optimize timestep allocation in score-based diffusion sampling.

Ax Anna Karnysheva, Dietrich Klakow, Ji-Ung Lee 9d ago

Probing Chemical Language Models: Effects of Pre-training and Fine-tuning

Systematic study probing chemical language models for molecular substructure encoding across pre-trained and fine-tuned variants.

Ax Debopriya Ghosh 9d ago

Predicting Early Stages Of Alzheimer's Disease And Identifying Key Biomarkers Using Deep Artificial Neural Network And Ensemble Of Machine Learning Methodologies

Deep neural network and ensemble methods for early Alzheimer's disease prediction from biomarkers.

Ax Di Wu, Huan Liu, Zhixiang Chi, Yuanhao Yu, Konstantinos N. Plataniotis, Yang Wang 9d ago

Dynamic Neural Graph Encoding of Inference Processes in Deep Weight Space

Neural graph encoding method for analyzing neural network weight spaces capturing sequential layer-by-layer inference processing.

Ax Jijie Zhang, Zhe Ren, Quan Zhang, Dandan Guo 9d ago

Bayesian Sparse Low-Rank Adaptation for Large Language Model Uncertainty Estimation

DALorRA: Bayesian sparse low-rank adaptation method for uncertainty quantification in fine-tuned LLMs to improve trustworthy deployment.

Ax Xavier Mart\'inez-Lua\~na, Alba Gude-Santos, Manuel Fern\'andez-Veiga, Rebeca P. D\'iaz-Redondo 9d ago

Privacy-Preserving and Verifiable Approximate Distributed Coded Computing

Privacy-preserving distributed coded computing framework addressing privacy leakage and malicious manipulation in federated and decentralized learning.

Ax Joseph Webb, Sadok Jerad, Coralia Cartis 9d ago

An Optimisation Framework for the Well-Conditioned Training of Physics-Informed Neural Networks

Optimization framework (DSGNAR) using second-order methods to improve ill-conditioned training of physics-informed neural networks.

Ax Jiawei Zhang 9d ago

Online Resource Allocation with Continuous Random Consumption: Regret under Degeneracy

Online resource allocation algorithm with continuous random consumption and degeneracy analysis for sequential request acceptance problems.

Ax Mojgan Alishiri, Amirhossein Arzani 9d ago

Self-explainable Operator Learning for Discovering Spatial Patterns in Functional Data

Self-explainable operator learning framework using functional linear models for interpretable modeling of complex physical systems.

Ax Ziyun Qiao, Yue Min, Ruining Chen, Yujun Li 9d ago

HERMES: A Multi-Granularity Labeling Substrate for Pre-training Data Mixtures

HERMES provides hierarchical multi-granularity labeling system for organizing pre-training data mixtures across different semantic axes.

Ax Max Weltevrede, Matthijs T. J. Spaan, Wendelin B\"ohmer 9d ago

Generalization in offline RL: The structure is more important than the amount of pessimism

Study of generalization in offline reinforcement learning showing structure of pessimism matters more than degree for contextual MDPs.

Ax Ruihang Li, Mengde Xu, Shuyang Gu, Leigang Qu, Fuli Feng, Han Hu, Wenjie Wang 9d ago

Optimizing Visual Generative Models via Distribution-wise Rewards

Framework for training visual generative models using distribution-wise rewards to prevent reward hacking and improve image diversity.

Ax Juan Agust\'in Duque, Sergio Garc\'ia Heredia, Vinicius Hernandes, Eli\v{s}ka Greplov\'a, Thomas Spriggs, Aaron Courville, Anna Dawid 9d ago

One More Time: Revisiting Neural Quantum States from a Reinforcement Learning Perspective

Neural quantum states optimization using reinforcement learning perspective for approximating quantum many-body wavefunctions.

Ax Dezheng Wang, Tong Chen, Wei Yuan, Congyan Chen, Shihua Li, Hongzhi Yin 9d ago

Self-Gating Attention for Efficient Time Series Forecasting

Efficient transformer architecture with self-gating attention reducing computational complexity for time series forecasting applications.

Ax Juliette Decugis, Fabian Gloeckle, Francis Bach, Taco Cohen, Gabriel Synnaeve 9d ago

DecompRL: Solving Harder Problems by Learning Modular Code Generation

DecompRL uses reinforcement learning to teach LLMs modular code generation for solving hard problems by decomposing into solvable subcomponents.

Ax Zhuowei Chen, Liwei Chen, Christian Schunn, Raquel Coelho, Xiang Lorraine Li 9d ago

Neuron-Aware Active Few-Shot Learning for LLMs

Active few-shot learning method for LLMs that identifies valuable unlabeled samples for annotation to reduce human labeling costs and improve domain-specific adaptation.

Ax Quoc Bao Phan, Tuy Tan Nguyen 9d ago

QFedAgent: Quantum-Enhanced Personalized Federated Learning for Multi-Agent Activity Recognition

Federated learning with quantum enhancement for multi-agent activity recognition in distributed robotic systems addressing non-IID heterogeneous sensor data.

Ax Sanjeev Shrestha, Hui Liu, Yifan Zhang 9d ago

Extreme Adaptive Transformer for Time Series Forecasting

Transformer-based time series forecasting model designed to handle rare extreme events in hydrologic data.

Ax Xuanyu Chen, Nan Yang, Shuai Wang, Dong Yuan 9d ago

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data

Theoretical analysis of distributed self-supervised learning robustness under non-IID data heterogeneity in decentralized settings.

Ax Zhuowei Chen, Xiang Lorraine Li 9d ago

Neuron-Aware Data Selection for Annotation-Free LLM Self-Distillation

Neuron-aware data selection method for annotation-free LLM self-distillation in specialized domains without human-labeled supervision.