Isolater - Feed

Ax Ying Shen, Tianrong Chen, Yuan Gao, Yizhe Zhang, Yuyang Wang, Miguel \'Angel Bautista, Shuangfei Zhai, Joshua M. Susskind, Jiatao Gu 5/11/2026

STARFlow2: Bridging Language Models and Normalizing Flows for Unified Multimodal Generation

STARFlow2 unifying language models and normalizing flows for multimodal text-image generation with autoregressive normalizing flows.

Ax R\"uveyda Yilmaz, Yuli Wu, Johannes Stegmaier, Volkmar Schulz 5/11/2026

PET-Adapter: Test-Time Domain Adaptation for Full and Limited-Angle PET Image Reconstruction

PET-Adapter framework for test-time domain adaptation in medical image reconstruction handling Poisson noise and limited-angle acquisitions.

Ax Houssam Zenati, Arthur Gretton 5/11/2026

Semiparametric Efficient Test for Interpretable Distributional Treatment Effects

DR-ME test for interpretable distributional treatment effects, first semiparametrically efficient finite-location test for detecting distributional shifts.

Ax Julie Kallini, Artidoro Pagnoni, Tomasz Limisiewicz, Gargi Ghosh, Luke Zettlemoyer, Christopher Potts, Xiaochuang Han, Srinivasan Iyer 5/11/2026

Fast Byte Latent Transformer

Byte Latent Transformer (BLT) addressing slow byte-level autoregressive generation with diffusion-based training and generation techniques.

Ax Jane H. Lee, Anay Mehrotra, Manolis Zampetakis 5/11/2026

A Note on Non-Negative $L_1$-Approximating Polynomials

Mathematical study of non-negative L1-approximating polynomials under Gaussian distributions with applications to computational learning theory.

Ax Jiatao Gu, Tianrong Chen, Ying Shen, David Berthelot, Shuangfei Zhai, Josh Susskind 5/11/2026

Normalizing Trajectory Models

Normalizing Trajectory Models (NTM) for efficient diffusion-based generation with few steps while preserving likelihood framework.

Ax Bhavesh Kalisetti, Vincent Wang, Gaurav R. Ghosal, Maryam Bijanzadeh, Reza Abbasi-Asl 5/11/2026

Multi-Stage Prototype Learning for Interpretable Time Series Classification

Multi-stage prototype learning framework for interpretable multivariate time series classification identifying predictive temporal patterns.

Ax Hongyuan Zhang, Yanchen Xu, Sida Huang, Xuelong Li 5/11/2026

Data Augmentation of Contrastive Learning is Estimating Positive-incentive Noise

Theoretical analysis connecting contrastive learning data augmentation to positive-incentive noise estimation via information theory.

Ax Zhichao Wang, Bin Bi, Can Huang, Shiva Kumar Pentyala, Zixu James Zhu, Sitaram Asur, Na Claire Cheng, Cheng Wan, Dong Nie, Lingzi Hong 5/11/2026

UNA: A Unified Supervised Framework for Efficient LLM Alignment Across Feedback Types

UNA framework unifying diverse feedback types (preferences, scores, scalars) for efficient LLM alignment across RLHF and DPO methods.

Ax Surbhi Goel, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan 5/11/2026

Testing Noise Assumptions of Learning Algorithms

Algorithm for testing whether training data satisfies noise model assumptions in computational learning theory.

Ax Andrzej Cichocki 5/11/2026

Generalized Euler Logarithm and its Applications in Machine Learning: Natural Gradient, Backpropagation, Generalized EG, Mirror Descent and OLPS

Theoretical analysis of generalized Euler logarithm properties with applications to natural gradient, backpropagation and optimization.

Ax Mohammad Ali Vahedifar, Qi Zhang 5/11/2026

No Forgetting Learning: Buffer-free Continual Learning Classification

Buffer-free continual learning framework exploiting network redundancy for class and task-incremental learning without replay memory.

Ax Vaneet Aggarwal, Shweta Jain, Subham Pokhriyal, Christopher John Quinn 5/11/2026

A Resilience Framework for Bi-Criteria Combinatorial Optimization with Bandit Feedback

Framework for bi-criteria combinatorial optimization with noisy evaluations and bandit feedback.

Ax Adam Izdebski, Jan Olszewski, Pankhil Gawade, Krzysztof Koras, Serra Korkmaz, Valentin Rauscher, Jakub M. Tomczak, Ewa Szczurek 5/11/2026

Synergistic Benefits of Joint Molecule Generation and Property Prediction

Hyformer transformer model jointly optimizing molecule generation and property prediction with synergistic benefits.

Ax Cecilia Casolo, S\"oren Becker, Niki Kilbertus 5/11/2026

Identifiability Challenges in Sparse Linear Ordinary Differential Equations

Research on identifiability challenges in learning sparse linear differential equation models from data.

Ax Wei Li, Zhe Xie, Yuxuan Liang, Xinli Hao, Yunyao Cheng, Dan Pei, Xiaofeng Meng 5/11/2026

From Time Series Analysis to Question Answering: A Survey in the LLM Era

Survey of LLM applications to time series analysis tasks including forecasting, anomaly detection, interpretation and captioning.

Ax Xingyue Huang, Mikhail Galkin, Michael M. Bronstein, \.Ismail \.Ilkan Ceylan 5/11/2026

HYPER: A Foundation Model for Inductive Link Prediction with Knowledge Hypergraphs

Foundation model for inductive link prediction on knowledge hypergraphs with novel entities and relation types using hypergraph embeddings.

Ax Yuta Sato, Kazuhiko Kawamoto, Hiroshi Kera 5/11/2026

Discovering Learning-Friendly Generation Orders for Sequential Computation

Method for automatically discovering learning-friendly generation orders in autoregressive models by identifying orders with faster early-stage loss drops.

Ax Guangchen Lan, Sipeng Zhang, Tianle Wang, Yuwei Zhang, Daoan Zhang, Xinpeng Wei, Xiaoman Pan, Hongming Zhang, Dong-Jun Han, Christopher G. Brinton 5/11/2026

MaPPO: Maximum a Posteriori Preference Optimization with Prior Knowledge

MaPPO: preference optimization for LLM alignment incorporating prior reward knowledge into Direct Preference Optimization framework.

Ax Jiaqi Lin, Malyaban Bal, Abhronil Sengupta 5/11/2026

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs

Equilibrium Propagation with intermediate error signals for biologically-inspired local learning in convolutional recurrent neural networks. Reduces BPTT computational cost.

Ax Kota Fukuzawa, Atsushi Suzuki, Kenji Yamanishi 5/11/2026

Normalized Maximum Likelihood Code-Length on Riemannian Data Spaces

Normalized Maximum Likelihood code-length formulation for Riemannian data spaces including hyperbolic geometry for hierarchical graph structures.

Ax Mikael Henaff, Scott Fujimoto, Michael Matthews, Michael Rabbat 5/11/2026

Scalable Option Learning in High-Throughput Environments

Scalable Option Learning: hierarchical RL algorithm achieving 35x speedup in high-throughput environments for long-horizon decision-making.

Ax Towhidul Islam, Md Sumon Ali 5/11/2026

Ensemble Learning for Healthcare: A Comparative Analysis of Hybrid Voting and Ensemble Stacking in Obesity Risk Prediction

Comparative study of ensemble voting and stacking methods for obesity risk prediction using machine learning. Healthcare application with limited novelty.

Ax Yuqi Pan, Yupeng Feng, Jinghao Zhuang, Siyu Ding, Han Xu, Zehao Liu, Bohan Sun, Yuhong Chou, Xuerui Qiu, Anlin Deng, Anjie Hu, Shurong Wang, Peng Zhou, Man Yao, Jibin Wu, Jian Yang, Guoliang Sun, Bo Xu, Guoqi Li 5/11/2026

SpikingBrain: Spiking Brain-inspired Large Models

SpikingBrain: spiking neural network-based large models addressing quadratic training and linear inference complexity bottlenecks in Transformers for long-context.

Ax Lucas Fenaux, Zheng Wang, Jacob Yan, Nathan Chung, Florian Kerschbaum 5/11/2026

Hammer and Anvil: Toward a Theory of Backdoors in Federated Learning

Hammer and Anvil: theoretical framework categorizing backdoor attacks in federated learning and identifying fundamental defenses against adaptive adversaries.

Ax Dikshant Sagar, Kaiwen Yu, Alejandro Yankelevich, Jianming Bian, Pierre Baldi 5/11/2026

Adapting Vision-Language Models for Neutrino Event Classification in High-Energy Physics

Fine-tuned LLaMA 3.2 vision-language model applied to neutrino event classification in high-energy physics detector data.

Ax Lars van der Laan, Nathan Kallus, Aurelien Bibaut 5/11/2026

Inverse Reinforcement Learning with Just Classification and a Few Regressions

Inverse reinforcement learning method using classification and regression instead of specialized architectures. Addresses reward identifiability in maximum-entropy models.

Ax Feng Yu, Jia Hu, Geyong Min 5/11/2026

BoHA: Blockwise Hadamard Product Adaptation for Parameter-Efficient Fine-Tuning

BoHA: blockwise Hadamard adaptation for parameter-efficient fine-tuning of LLMs. Addresses sequential adaptation and task retention vs. single-task accuracy.

Ax Zhijian Xu, Wanxu Cai, Xilin Dai, Zhaorong Deng, Qiang Xu 5/11/2026

Fidel-TS: A High-Fidelity Multimodal Benchmark for Time Series Forecasting

Fidelity benchmark for multimodal time series forecasting addressing data contamination and leakage issues in existing datasets.

Ax Seohyun Lee, Wenzhi Fang, Dong-Jun Han, Seyyedali Hosseinalipour, Christopher G. Brinton 5/11/2026

TAP: Two-Stage Adaptive Personalization of Multi-Task and Multi-Modal Foundation Models in Federated Learning

Two-stage adaptive personalization framework for foundation models in federated learning with heterogeneous tasks and modalities. Original research on PEFT.

Ax Akshat Ramachandran, Marina Neseem, Charbel Sakr, Rangharajan Venkatesan, Brucek Khailany, Tushar Krishna 5/11/2026

ThinKV: Thought-Adaptive KV Cache Compression for Efficient Reasoning Models

ThinKV: adaptive KV cache compression framework for reasoning models using thought-type detection and hybrid quantization.

Ax Jinwoo Kim, Xingyue Huang, Krzysztof Olejniczak, Kyungbin Min, Michael Bronstein, Seunghoon Hong, \.Ismail \.Ilkan Ceylan 5/11/2026

Flock: A Knowledge Graph Foundation Model via Learning on Random Walks

Flock: knowledge graph foundation model using random walk learning for zero-shot link prediction on novel entities and relations.

Ax Ali Yavari, Alireza Mohamadi, Elham Beydaghi, Philipp Seeb\"ock, Rainer A. Leitgeb 5/11/2026

Frequency-Aware Model Parameter Explorer: A new attribution method for improving explainability

Frequency-Aware attribution method for neural networks using selective high/low-frequency perturbations for improved explainability.

Ax Alexandre Galashov, Natha\"el Da Costa, Liyuan Xu, Philipp Hennig, Arthur Gretton 5/11/2026

Closed-Form Last Layer Optimization

Closed-form optimization method for neural network last layers using known linear solution during training.

Ax Tingyang Wei, Jiao Liu, Abhishek Gupta, Chin Chun Ooi, Puay Siew Tan, Yew-Soon Ong 5/11/2026

Amortized Multi-Objective Optimization Across Tasks with Generative Solution Modeling

Amortized multi-objective optimization across task families using generative solution modeling for expensive multi-objective problems.

Ax Jinying Xiao, Bin Ji, Shasha Li, Xiaodong Liu, Ma Jun, Chao Wang, Wei Li, Ye Zhong, Xuan Xie, Nyima Tashi, Jie Yu 5/11/2026

Outlier Smoothing with Closed-Form Rotations for W4A4 Large Language Model Quantization

W4A4 LLM quantization method using closed-form rotations on Stiefel manifolds to address convergence issues in ultra-low-bit quantization.

Ax Alessandro De Palma, Greta Dolcetti, Caterina Urban 5/11/2026

Faster Verified Explanations for Neural Networks

FaVeX: algorithm for computing verified explanations of neural networks faster by dynamically combining verification techniques.

Ax Juan Diego Toscano, Daniel T. Chen, George Em Karniadakis 5/11/2026

ATHENA: Agentic Team for Hierarchical Evolutionary Numerical Algorithms

ATHENA: agentic framework for autonomous scientific computing and ML research. Hierarchical evolutionary algorithms loop for end-to-end computational lifecycle management.

Ax Muhammad Bilal Shahid, Zhanhong Jiang, Prajwal Koirala, Soumik Sarkar, Cody Fleming 5/11/2026

Neural CDEs as Correctors for Learned Time Series Models

Predictor-Corrector framework using neural controlled differential equations to correct forecast errors in learned time-series models.

Ax Jingdi Lei, Di Zhang, Soujanya Poria 5/11/2026

Exact Flow Linear Attention: Exact Solution from Continuous-Time Dynamics

Exact Flow Linear Attention: novel attention mechanism using continuous-time dynamics and closed-form solutions for improved efficiency in transformers.

Ax Nick Leenders, Thomas Quadt, Boris Cule, Roy Lindelauf, Herman Monsuur, Joost van Oijen, Mark Voskuijl 5/11/2026

DT-PBO: an Interpretable Tree-based Surrogate Model for Preferential Bayesian Optimization

DT-PBO: interpretable tree-based surrogate model for Bayesian optimization with preference learning. Addresses interpretability in high-stakes domains.

Ax Seong Ho Pahng, Guoye Guan, Benjamin Fefferman, Sahand Hormoz 5/11/2026

DiffeoMorph: Learning to Morph 3D Shapes Using Differentiable Agent-Based Simulations

DiffeoMorph: differentiable framework for learning 3D shape morphing using agent-based distributed control. Application to developmental biology and multi-agent systems.

Ax John Cartmell, Mihaela Cardei, Ionut Cardei 5/11/2026

Bloom Filter Encoding for Machine Learning

Bloom filter-based data encoding method for ML that compresses features into fixed-length bit arrays with optional keyed hashing for obfuscation.

Ax Jingyang You, Hanna Kurniawati 5/11/2026

Generalised Linear Models in Deep Bayesian RL with Learnable Basis Functions

Deep Bayesian RL using generalised linear models with learnable basis functions for meta-RL task adaptation.

Ax Dominik Wagner, Ankit Kanwar, Luke Ong 5/11/2026

SB-TRPO: Towards Safe Reinforcement Learning with Hard Constraints

SB-TRPO algorithm for safe reinforcement learning satisfying hard zero-cost safety constraints while optimizing rewards.

Ax Nalin Dhiman 5/11/2026

FANoS-v2: Feedback-Controlled Momentum with Thermostat Damping for Lightweight Neural Optimization

FANoS-v2 PyTorch optimizer augmenting RMS-preconditioned momentum with feedback controller and thermostat damping.

Ax Bostan Khan, Masoud Daneshtalab 5/11/2026

DeepFedNAS: Efficient Hardware-Aware Architecture Adaptation for Heterogeneous IoT Federations via Pareto-Guided Supernet Training

DeepFedNAS framework for efficient hardware-aware neural architecture search across heterogeneous IoT device federations.

Ax Yilie Huang, Wenpin Tang, Xunyu Zhou 5/11/2026