Ax Fateme Jamshidi, Mohammad Shahverdikondori, Negar Kiyavash 4/2/2026

Graph-Dependent Regret Bounds in Multi-Armed Bandits with Interference

Multi-armed bandit algorithm using local graph structure to minimize regret under network interference.

Ax Leo Henry, Thomas Neele, Mohammad Reza Mousavi, Matteo Sammartino 4/2/2026

A Detailed Account of Compositional Automata Learning through Alphabet Refinement

Compositional automata learning technique for inferring models of concurrent systems through alphabet refinement.

Ax Stepan Tretiakov, Xingjian Li, Krishna Kumar 4/2/2026

SetONet: A Set-Based Operator Network for Solving PDEs with Variable-Input Sampling

SetONet neural operator for solving PDEs with variable sensor layouts by treating inputs as unordered sets.

Ax Carlos Rodriguez-Pardo, Leonardo Chiani, Emanuele Borgonovo, Massimo Tavoni 4/2/2026

Neural Conditional Transport Maps

Neural framework for learning conditional optimal transport maps using hypernetworks to generate adaptive transport parameters.

Ax Leon Eshuijs, Archie Chaudhury, Alan McBeth, Ethan Nguyen 4/2/2026

But what is your honest answer? Aiding LLM-judges with honest alternatives using steering vectors

JUSSA framework uses steering vectors to improve LLM-as-a-judge reliability, detecting and mitigating sycophancy through honesty-promoting alternatives.

Ax Rafael Sojo, Javier D\'iaz-Rozo, Concha Bielza, Pedro Larra\~naga 4/2/2026

Binned semiparametric Bayesian networks for efficient kernel density estimation

Binned semiparametric Bayesian networks for efficient kernel density estimation using data binning to reduce computational cost.

Ax Hanlin Dong, Arian Prabowo, Hao Xue, Ao Shuang, Tianyi Zhou, Flora D. Salim 4/2/2026

Double-Diffusion: ODE-Prior Accelerated Diffusion Models for Spatio-Temporal Graph Forecasting

Double-Diffusion integrates ODE-prior with denoising diffusion models for spatio-temporal graph forecasting, balancing deterministic and stochastic components.

Ax Zhenpeng Su, Leiyu Pan, Xue Bai, Dening Liu, Guanting Dong, Jiaming Huang, Minxuan Lv, Wenping Hu, Fuzheng Zhang, Kun Gai, Guorui Zhou 4/2/2026

Klear-Reasoner: Advancing Reasoning Capability via Gradient-Preserving Clipping Policy Optimization

Klear-Reasoner model with long reasoning capabilities using gradient-preserving clipping policy optimization, with detailed training disclosures.

Ax Muntasir Hoq, Griffin Pitts, Tirth Bhatt, Aum Pandya, Andrew Lan, Peter Brusilovsky, Bita Akram 4/2/2026

Pattern-based Knowledge Component Extraction from Student Code Using Representation Learning

Knowledge component discovery in programming using representation learning on student code for personalized instruction systems.

Ax Mohammad Taha Shah, Sabrina Khurshid, Gourab Ghatak 4/2/2026

Order Optimal Regret Bounds for Sharpe Ratio Optimization under Thompson Sampling

Thompson sampling analysis for Sharpe ratio optimization in multi-armed bandit setting, addressing fractional objective with dependent mean-variance.

Ax Sima Najafzadehkhoei, George Vega Yon, Bernardo Modenesi, Derek S. Meyer 4/2/2026

Machine Generalize Learning in Agent-Based Models: Going Beyond Surrogate Models for Calibration in ABMs

LSTM-based machine learning calibrator for agent-based epidemic models, learning inverse mapping from time series to SIR parameters.

Ax Robiul Islam, Dmitry I. Ignatov, Karl Kaberg, Roman Nabatchikov 4/2/2026

Exploring the Relationship between Brain Hemisphere States and Frequency Bands through Classical Machine Learning and Deep Learning Optimization Techniques with Neurofeedback

EEG classification study comparing neural network architectures and optimizers across brain hemisphere frequency bands using TensorFlow/PyTorch.

Ax Zelong Bi, Pierre Lafaye de Micheaux 4/2/2026

A Survey and Comparative Evaluation of Intrinsic Dimension Estimators under the Manifold Hypothesis

Comprehensive survey of intrinsic dimension estimators under manifold hypothesis, reviewing theoretical foundations and comparing eight methods.

Ax David Arbour, Harsh Parikh, Bijan Niknam, Elizabeth Stuart, Kara Rudolph, Avi Feller 4/2/2026

Regularizing Extrapolation in Causal Inference

Analysis of weight constraints in linear smoothers for causal inference, balancing feature imbalance against parametric modeling assumptions.

Ax Jubayer Ibn Hamid, Ifdita Hasan Orney, Ellen Xu, Chelsea Finn, Dorsa Sadigh 4/2/2026

Polychromic Objectives for Reinforcement Learning

Polychromic objectives approach to prevent mode collapse in reinforcement learning fine-tuning, preserving policy diversity during exploration.

Ax Aleksandar Armacki, Ali H. Sayed 4/2/2026

High-probability Convergence Guarantees of Decentralized SGD

Convergence analysis for decentralized SGD with high-probability guarantees, removing restrictive assumptions on gradient bounds and noise.

Ax Jacek Karwowski, Raymond Douglas 4/2/2026

Incoherence in Goal-Conditioned Autoregressive Models

Mathematical analysis of incoherence in goal-conditioned autoregressive models, studying policy improvement through fine-tuning with online RL.

Ax S Sairam, Sara Girdhar, Shivam Soni 4/2/2026

The Final-Stage Bottleneck: A Systematic Dissection of the R-Learner for Network Causal Inference

Empirical study examining the R-Learner framework limitations for network causal inference with graph-dependent heterogeneous treatment effects.

Ax Giovanni Conforti, Alain Durmus, Le-Tuyet-Nhi Pham, Gael Raoul 4/2/2026

Non-Asymptotic Convergence of Discrete Diffusion Models: Masked and Random Walk dynamics

Theoretical analysis of diffusion models on discrete state spaces, establishing convergence guarantees for masked and random walk dynamics.

Ax Takuya Kanazawa 4/2/2026

Multivariate Uncertainty Quantification with Tomographic Quantile Forests

Tomographic Quantile Forests (TQF) for nonparametric uncertainty quantification in multivariate regression tasks.

Ax Kevin Zhang, Yixin Wang 4/2/2026

Meta-probabilistic Modeling

Meta-probabilistic modeling framework for discovering latent structure across collections of related datasets using probabilistic graphical models.

Ax Anderson de Andrade, Alon Harell, Ivan V. Baji\'c 4/2/2026

Lossy Common Information in a Learnable Gray-Wyner Network

Research on learnable Gray-Wyner networks for disentangling common and task-specific information in computer vision.

Ax Yuze Wang, Yujia Tong, Xuan Liu, Junhao Dong 4/2/2026

SAU: Sparsity-Aware Unlearning for LLMs via Gradient Masking and Importance Redistribution

SAU method for machine unlearning in sparse LLMs via gradient masking and importance redistribution for privacy.

Ax Sohan Venkatesh, Ashish Mahendran Kurapath 4/2/2026

On the Non-Identifiability of Steering Vectors in Large Language Models

Research showing activation steering vectors in LLMs are fundamentally non-identifiable with large equivalence classes.

Ax Isaac Han, Sangyeon Park, Seungwon Oh, Donghu Kim, Hojoon Lee, Kyung-Joong Kim 4/2/2026

FIRE: Frobenius-Isometry Reinitialization for Balancing the Stability-Plasticity Tradeoff

FIRE method for reinitialization in continual learning that balances stability and plasticity in neural networks.

Ax Deyi Kong, Zaiwei Chen, Shuzhong Zhang, Shancong Mou 4/2/2026

Natural Hypergradient Descent: Algorithm Design, Convergence Analysis, and Parallel Implementation

Research on Natural Hypergradient Descent for bilevel optimization using Fisher information matrix as Hessian surrogate.

Ax Tatsuya Sagawa, Ryosuke Kojima 4/2/2026

How Well Do Large-Scale Chemical Language Models Transfer to Downstream Tasks?

Evaluation of scaling laws for Chemical Language Models on downstream molecular property prediction tasks.

Ax Adrian Garcia-Casta\~neda, Jon Irureta, Jon Imaz, Aizea Lojo 4/2/2026

Grow, Assess, Compress: Adaptive Backbone Scaling for Memory-Efficient Class Incremental Learning

Introduces adaptive backbone scaling framework for class incremental learning to balance plasticity and stability while reducing memory overhead.

Ax Savannah L. Ferretti, Jerry Lin, Sara Shamekh, Jane W. Baldwin, Michael S. Pritchard, Tom Beucler 4/2/2026

Data-Driven Integration Kernels for Interpretable Nonlocal Operator Learning

Framework for learning interpretable nonlocal operator kernels from data for climate process modeling.

Ax Mansoor Ahmed, Nadeem Taj, Imdad Ullah Khan, Hemanth Venkateswara, Murray Patterson 4/2/2026

CHIMERA-Bench: A Benchmark Dataset for Epitope-Specific Antibody Design

Standardized benchmark dataset for epitope-specific antibody design with unified evaluation metrics for generative methods.

Ax Shenyang Deng, Zhuoli Ouyang, Tianyu Pang, Zihang Liu, Ruochen Jin, Shuhua Yu, Yaoqing Yang 4/2/2026

RMNP: Row-Momentum Normalized Preconditioning for Scalable Matrix-Based Optimization

Preconditioned optimization method using row-momentum normalization for scalable matrix-based neural network training.

Ax Shinsaku Sakaue 4/2/2026

Simple Projection-Free Algorithm for Contextual Recommendation with Logarithmic Regret and Robustness

Projection-free algorithm for contextual bandits achieving logarithmic regret with improved efficiency over Online Newton Step.

Ax YanZhao Zheng, ZhenTao Zhang, Chao Ma, YuanQiang Yu, JiHuai Zhu, Yong Wu, Tianze Xu, Baohua Dong, Hangcheng Zhu, Ruohui Huang, Gang Yu 4/2/2026

SkillRouter: Skill Routing for LLM Agents at Scale

Skill routing system for LLM agents that identifies relevant skills from large ecosystems before planning or execution.

Ax Dogan Urgun, Gokhan Gungor 4/2/2026

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

Framework using LLMs to automatically design reward programs for cooperative multi-agent RL systems with sparse task feedback.

Ax Pengxuan Yang, Yupeng Zheng, Deheng Qian, Zebin Xing, Qichao Zhang, Linbo Wang, Yichen Zhang, Shaoyu Guo, Zhongpu Xia, Qiang Chen, Junyu Han, Lingyun Xu, Yifeng Pan, Dongbin Zhao 4/2/2026

DreamerAD: Efficient Reinforcement Learning via Latent World Model for Autonomous Driving

DreamerAD uses latent world models for efficient RL in autonomous driving, compressing diffusion sampling 80x with visual interpretability.

Ax Marc-Antoine Allard, Arnaud Teinturier, Victor Xing, Gautier Viaud 4/2/2026

Experiential Reflective Learning for Self-Improving LLM Agents

ERL framework enabling LLM agents to self-improve through experiential learning from past interactions and reflective adaptation.

Ax Devashish Gaikwad, Wil M. P. van der Aalst, Gyunam Park 4/2/2026

Neuro-Symbolic Process Anomaly Detection

Neuro-symbolic method for process anomaly detection combining neural networks with domain knowledge from process mining.

Ax Shoujin Wang, Mingze Ni, Wei Liu, Victor W. Chu, Bryan Zheng, Ayush Kanwal, Roy Jing Yang, Kenneth Sabir, Fang Chen 4/2/2026

Neural Federated Learning for Livestock Growth Prediction

Federated learning approach for livestock growth prediction addressing privacy concerns and limited datasets in agricultural applications.

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 4/2/2026

HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention

Hierarchical indexing system for efficient fine-grained sparse attention in transformers, removing bottleneck from key selection.

Ax Tushar Dhananjay Pathak 4/2/2026

ARCS: Autoregressive Circuit Synthesis with Topology-Aware Graph Attention and Spec Conditioning

Autoregressive system for generating complete analog circuit designs with topology and component values using graph VAE and flow-matching.

Ax Shafayeth Jamil, Rehan Kapadia 4/2/2026

Lie Generator Networks for Nonlinear Partial Differential Equations

Neural operator learning nonlinear PDEs by lifting dynamics into linear latent space via Koopman generator decomposition.

Ax Max Hennick, Guillaume Corlouer 4/2/2026

From Density Matrices to Phase Transitions in Deep Learning: Spectral Early Warnings and Interpretability

Uses 2-datapoint reduced density matrix from quantum chemistry to predict and understand phase transitions during neural network training.

Ax Chinmay Savadikar, Michelle Dai, Tianfu Wu 4/2/2026

CHEEM: Continual Learning by Reuse, New, Adapt and Skip -- A Hierarchical Exploration-Exploitation Approach

Continual learning framework using hierarchical exploration-exploitation to acquire knowledge from task streams without catastrophic forgetting.

Ax Anders Sj\"oberg, Jakob Lindqvist, Magnus \"Onnheim, Mats Jirstrand, Lennart Svensson 4/2/2026

MCMC-Correction of Score-Based Diffusion Models for Model Composition

Combines MCMC correction with score-based diffusion models using Metropolis-Hastings steps for improved sampling in model composition.

Ax Kwangho Kim, Jisu Kim, Edward H. Kennedy 4/2/2026

Causal K-Means Clustering

Novel k-means clustering approach incorporating causal inference to identify heterogeneous treatment effects across unknown subgroups.

Ax Antonio Di Noia, Iuri Macocco, Aldo Glielmo, Alessandro Laio, Antonietta Mira 4/2/2026

Scale-adaptive and robust intrinsic dimension estimation via optimal neighbourhood identification

Method for estimating intrinsic dimensionality of datasets accounting for scale-dependent effects and measurement noise in unsupervised learning.

Ax Bhrij Patel, Souradip Chakraborty, Mengdi Wang, Dinesh Manocha, Amrit Singh Bedi 4/2/2026

Code Comprehension then Auditing for Unsupervised LLM Evaluation

LLM-based approach for unsupervised code correctness evaluation that separates code comprehension from auditing to improve accuracy without reference implementations.

Ax Vincent Guan, Joseph Janssen, Hossein Rahmani, Andrew Warren, Stephen Zhang, Elina Robeva, Geoffrey Schiebinger 4/2/2026

Identifying Drift, Diffusion, and Causal Structure from Temporal Snapshots

Method for learning stochastic differential equations from temporal snapshots without observable trajectories, applied to gene networks and financial markets.

Ax Johnny Chan, Yuming Li 4/2/2026

Enhancing Team Diversity with Generative AI: A Novel Project Management Framework

Project management framework using GenAI agents to optimize team composition by matching personality roles.

Ax Yuchen Fang, Javad Lavaei, Sen Na 4/2/2026

High Probability Complexity Bounds of Trust-Region Stochastic Sequential Quadratic Programming with Heavy-Tailed Noise

Trust-region stochastic SQP algorithm for nonlinear optimization with complexity bounds under heavy-tailed noise.