Ax David P. Morton, Oscar Dowson, Bernardo K. Pagnoncelli 4/9/2026

MDP modeling for multi-stage stochastic programs

MDP modeling framework extending policy graphs for multi-stage stochastic programs with decision-dependent uncertainty and statistical learning.

Ax Xi Wang, James McInerney, Lequn Wang, Nathan Kallus 4/9/2026

Entropy After </Think> for reasoning model early exiting

Technique for detecting when reasoning LLMs overthink by analyzing entropy after chain-of-thought to enable early exiting.

Ax Yuezhu Xu, S. Sivaranjani 4/9/2026

ECLipsE-Gen-Local: Efficient Compositional Local Lipschitz Estimates for Deep Neural Networks

Method for efficiently computing Lipschitz constant estimates for neural networks using local information to improve robustness certification.

Ax Max Hopkins, Russell Impagliazzo, Christopher Ye 4/9/2026

Approximate Replicability in Learning

Approximate replicability framework for machine learning algorithms that remain stable under input resampling.

Ax Iv\'an Ojeda-Ruiz, Young Ju Lee, Malcolm Dickens, Leonardo Cambisaca 4/9/2026

Alternatives to the Laplacian for Scalable Spectral Clustering with Group Fairness Constraints

Spectral clustering alternatives to Laplacian with group fairness constraints for equitable cluster representation.

Ax Zhichao Wang 4/9/2026

GIFT: Group-Relative Implicit Fine-Tuning Integrates GRPO with DPO and UNA

GIFT unifies GRPO, DPO, and UNA in reinforcement learning framework for LLM alignment combining group-relative sampling with implicit preference learning.

Ax Qingyue Zhang, Chang Chu, Tianren Peng, Qi Li, Xiangyang Luo, Zhihao Jiang, Shao-Lun Huang 4/9/2026

LoRA-DA: Data-Aware Initialization for Low-Rank Adaptation via Asymptotic Analysis

LoRA-DA provides data-aware initialization for low-rank adaptation via theoretical framework and asymptotic analysis for parameter-efficient fine-tuning.

Ax Yuhua Jiang, Shuang Cheng, Yihao Liu, Ermo Hua, Che Jiang, Weigao Sun, Yu Cheng, Feifei Gao, Biqing Qi, Bowen Zhou 4/9/2026

Nirvana: A Specialized Generalist Model With Task-Aware Memory Mechanism

Nirvana specialized generalist model with task-aware memory mechanism for domain adaptation while preserving broad LLM capabilities.

Ax Junyi Wu, Dan Li 4/9/2026

Tensor-Efficient High-Dimensional Q-learning

Tensor-based Q-learning approach to handle high-dimensional reinforcement learning by exploiting problem structure without neural networks.

Ax Omri Ben-Dov, Luiz F. O. Chamon 4/9/2026

Adaptive Symmetrization of the KL Divergence

Adaptive symmetrization of KL divergence for learning probability distributions with normalizing flows and energy-based models.

Ax Zhixiong Zhao, Fangxin Liu, Junjie Wang, Chenyang Guan, Zongwu Wang, Li Jiang, Haibing Guan 4/9/2026

SpecQuant: Spectral Decomposition and Adaptive Truncation for Ultra-Low-Bit LLMs Quantization

SpecQuant framework for ultra-low-bit LLM quantization using spectral decomposition and adaptive truncation for efficient device deployment.

Ax Thomas Norrenbrock, Timo Kaiser, Sovan Biswas, Neslihan Kose, Ramesh Manuvinakurike, Bodo Rosenhahn 4/9/2026

CHiQPM: Calibrated Hierarchical Interpretable Image Classification

CHiQPM provides global and local interpretability for image classification in safety-critical domains with hierarchical explanations.

Ax Chihyeon Song, Jaewoo Lee, Jinkyoo Park 4/9/2026

Adaptive Replay Buffer for Offline-to-Online Reinforcement Learning

Adaptive Replay Buffer (ARB) dynamically prioritizes data sampling in offline-to-online reinforcement learning to balance stability and asymptotic performance.

Ax Carla Crivoi, Radu Tudor Ionescu 4/9/2026

Machine Unlearning in the Era of Quantum Machine Learning: An Empirical Study

First empirical study of machine unlearning in hybrid quantum-classical neural networks and variational quantum circuits.

Ax Pritthijit Nath, Sebastian Schemm, Henry Moss, Peter Haynes, Emily Shuckburgh, Mark J. Webb 4/9/2026

Replacing Tunable Parameters in Weather and Climate Models with State-Dependent Functions using Reinforcement Learning

Reinforcement learning framework to learn weather/climate model parametrization schemes as state-dependent functions online instead of using fixed coefficients.

Ax James O'Neill, Robert Clancy, Mariia Matskevichus, Fergal Reid 4/9/2026

Low-Rank Key Value Attention

Low-Rank Key-Value (LRKV) attention reduces transformer KV cache memory by exploiting redundancy across attention heads with low-rank residuals.

Ax Md Nabi Newaz Khan, Abdullah Arafat Miah, Yu Bi 4/9/2026

BadImplant: Injection-based Multi-Targeted Graph Backdoor Attack

BadImplant introduces multi-targeted backdoor attacks against graph neural networks with injection-based mechanisms.

Ax Annemarie Jutte, Uraz Odyurt 4/9/2026

Explainable AI to Improve Machine Learning Reliability for Industrial Cyber-Physical Systems

Explainable AI methods to improve ML reliability and prevent unexpected behavior in industrial cyber-physical systems.

Ax Powei Chang, Jinpeng Zhang, Bowen Chen, Chenyu Wang, Chenlu Guo, Yixing Zhang, Yukang Gao, JianXiang Xiang, Yue Gao, Chaoqun Sun, Yiyi Chen, Dongying Kong 4/9/2026

SPICE: Submodular Penalized Information-Conflict Selection for Efficient Large Language Model Training

SPICE uses submodular optimization and Fisher information to select training data for efficient LLM instruction tuning while addressing gradient conflicts.

Ax J Rosser, Robert Kirk, Edward Grefenstette, Jakob Foerster, Laura Ruis 4/9/2026

Infusion: Shaping Model Behavior by Editing Training Data via Influence Functions

Infusion framework uses influence functions to craft training data perturbations that induce targeted model behavior changes, evaluated on vision and language tasks.

Ax Alex Morehead, Miruna Cretu, Antonia Panescu, Rishabh Anand, Maurice Weiler, Tynan Perez, Samuel Blau, Steven Farrell, Wahid Bhimji, Anubhav Jain, Hrushikesh Sahasrabuddhe, Pietro Lio, Tommi Jaakkola, Rafael Gomez-Bombarelli, Rex Ying, N. Benjamin Erichson, Michael W. Mahoney 4/9/2026

Zatom-1: A Multimodal Flow Foundation Model for 3D Molecules and Materials

Open-source foundation model for 3D molecular and materials modeling with both generative and predictive capabilities.

Ax Dennis Thumm, Ying Chen 4/9/2026

Interventional Time Series Priors for Causal Foundation Models

Interventional time series data generator for training causal foundation models on time series, extending prior-data fitted networks to temporal domains.

Ax Nicolas Deutschmann, Constance Ferragu, Jonathan D. Ziegler, Shayan Aziznejad, Eli Bixby 4/9/2026

EvoFlows: Evolutionary Edit-Based Flow-Matching for Protein Engineering

EvoFlows: variable-length protein sequence model using flow matching for protein engineering with native support for insertions, deletions, and mutations.

Ax Philip Bechtle, Lucie Flek, Philipp Alexander Jung, Akbar Karimi, Timo Saala, Alexander Schmidt, Matthias Schott, Philipp Soldin, Christopher Wiebusch, Ulrich Willemsen 4/9/2026

Shapes are not enough: CONSERVAttack and its use for finding vulnerabilities and uncertainties in machine learning applications

CONSERVAttack method for identifying vulnerabilities and systematic uncertainties in ML models applied to high-energy physics data analysis.

Ax Xianyong Xu, Yuanjun Zuo, Zhihong Huang, Yihan Qin, Haoxian Xu, Leilei Du, Haotian Wang 4/9/2026

MR-ImagenTime: Multi-Resolution Time Series Generation through Dual Image Representations

MR-CDM: multi-resolution conditional diffusion framework for variable-length time series forecasting with hierarchical decomposition and adaptive embeddings.

Ax Chin-Chia Michael Yeh 4/9/2026

Matrix Profile for Time-Series Anomaly Detection: A Reproducible Open-Source Benchmark on TSB-AD

Open-source benchmark and reproducible implementation of Matrix Profile methods for univariate and multivariate time-series anomaly detection.

Ax Chenxu Yang, Chuanyu Qin, Qingyi Si, Minghui Chen, Naibin Gu, Dingyu Yao, Zheng Lin, Weiping Wang, Jiaqi Wang, Nan Duan 4/9/2026

Self-Distilled RLVR

On-policy self-distillation approach for LLM training combining dense teacher signals with sparse verifiable rewards from environment feedback.

Ax Maharshi Savdhariya 4/9/2026

NativeTernary: A Self-Delimiting Binary Encoding with Unary Run-Length Hierarchy Markers for Ternary Neural Network Weights, Structured Data, and General Computing Infrastructure

NativeTernary: binary encoding format for ternary neural network weights achieving 2 bits per weight, 1.31x compression over GGUF for BitNet models.

Ax Jonas De Schouwer, Haitz S\'aez de Oc\'ariz Borde, Xiaowen Dong 4/9/2026

k-Maximum Inner Product Attention for Graph Transformers and the Expressive Power of GraphGPS

Proposes k-maximum inner product attention mechanism for graph transformers to reduce computational complexity while maintaining expressive power.

Ax Bohao Li, Tao Zou, Junchen Ye, Yan Gong, Bowen Du 4/9/2026

A Clinical Point Cloud Paradigm for In-Hospital Mortality Prediction from Multi-Level Incomplete Multimodal EHRs

Deep learning approach for clinical risk prediction from incomplete multimodal EHR data using point cloud paradigm to handle irregular sampling and missing modalities.

Ax James Hu, Mahdi Ghelichi 4/9/2026

Noise Immunity in In-Context Tabular Learning: An Empirical Robustness Analysis of TabPFN's Attention Mechanisms

Empirical robustness analysis of TabPFN's attention mechanisms for tabular in-context learning, examining noise immunity across heterogeneous datasets.

Ax Tijana Zrnic, Emmanuel J. Cand\`es 4/9/2026

Active Statistical Inference

Active inference methodology for ML-assisted data collection, using models to identify which points merit labeling under budget constraints for efficient learning.

Ax Tirthankar Mittra 4/9/2026

Exploring Natural Language-Based Strategies for Efficient Number Learning in Children through Reinforcement Learning

RL framework studying how children learn numbers using base-ten blocks, investigating numerical cognition through reinforcement learning and neural networks.

Ax Penghui Yang, Cunxiao Du, Fengzhuo Zhang, Haonan Wang, Tianyu Pang, Chao Du, Bo An 4/9/2026

LongSpec: Long-Context Lossless Speculative Decoding with Efficient Drafting and Verification

LongSpec accelerates LLM inference on long contexts via lossless speculative decoding with efficient drafting and verification, targeting agent-based applications.

Ax Timo Gierlich, Andreas Baumbach, Akos F. Kungl, Kevin Max, Mihai A. Petrovici 4/9/2026

Spike-based alignment learning solves the weight transport problem

Spike-based alignment learning resolves weight transport problem in neural networks, enabling local computation compatible with biological networks and neuromorphic hardware.

Ax Wenlun Zhang, Yunshan Zhong, Weiqi Yan, Shengchuan Zhang, Shimpei Ando, Kentaro Yoshioka 4/9/2026

AHCQ-SAM: Toward Accurate and Hardware-Compatible Post-Training Segment Anything Model Quantization

AHCQ-SAM addresses post-training quantization challenges for Segment Anything Model to enable efficient deployment on resource-constrained edge devices.

Ax Andrea Montanari, Viet Vu 4/9/2026

Computational bottlenecks for denoising diffusions

Analyzes computational bottlenecks in denoising diffusion models, examining efficiency of drift learning and sampling procedures for probability distribution approximation.

Ax Aabid Karim, Abdul Karim, Bhoomika Lohana, Matt Keon, Jaswinder Singh, Abdul Sattar 4/9/2026

Lost in Cultural Translation: Do LLMs Struggle with Math Across Cultural Contexts?

Study of 14 LLMs showing mathematical reasoning accuracy drops 0.3-5.9% when math problems are culturally contextualized, revealing model limitations beyond pure logic.

Ax Tim Schneider, Cristiana de Farias, Roberto Calandra, Liming Chen, Jan Peters 4/9/2026

Apple: Toward General Active Perception via Reinforcement Learning

Active Perception Learner (Apple) applies reinforcement learning to enable general active perception in robotic systems with sparse, local sensory information.

Ax Yuhao Wu, Yushi Bai, Zhiqiang Hu, Roy Ka-Wei Lee, Juanzi Li 4/9/2026

LongWriter-Zero: Mastering Ultra-Long Text Generation via Reinforcement Learning

LongWriter-Zero uses reinforcement learning to improve ultra-long text generation in LLMs, overcoming length limitations and quality degradation without relying on synthetic training data.

Ax Wangsong Yin, Daliang Xu, Mengwei Xu, Gang Huang, Xuanzhe Liu 4/9/2026

ShadowNPU: System and Algorithm Co-design for NPU-Centric On-Device LLM Inference

ShadowNPU optimizes on-device LLM inference by addressing quantization sensitivity in attention operators, enabling efficient NPU execution for privacy-preserving deployment.

Ax Jackson Eshbaugh, Chetan Tiwari, Jorge Silveyra 4/9/2026

Synthetic Homes: A Multimodal Generative AI Pipeline for Residential Building Data Generation under Data Scarcity

Generative AI pipeline for synthetic building data creation addressing scarcity in residential energy modeling datasets.

Ax Junsong Li, Jie Zhou, Bihao Zhan, Yutao Yang, Qianjun Pan, Shilian Chen, Tianyu Huai, Xin Li, Qin Chen, Liang He 4/9/2026

LifeAlign: Lifelong Alignment for Large Language Models with Memory-Augmented Focalized Preference Optimization

Framework enabling LLMs to maintain alignment across sequential preference updates without catastrophic forgetting using memory-augmented optimization.

Ax Zaid Khan, Archiki Prasad, Elias Stengel-Eskin, Jaemin Cho, Mohit Bansal 4/9/2026

One Life to Learn: Inferring Symbolic World Models for Stochastic Environments from Unguided Exploration

Approach for learning symbolic world models from single-episode exploration in stochastic environments without human guidance.

Ax Yongji Wu, Xueshen Liu, Haizhong Zheng, Juncheng Gu, Beidi Chen, Z. Morley Mao, Arvind Krishnamurthy, Ion Stoica 4/9/2026

RLBoost: Harvesting Preemptible Resources for Cost-Efficient Reinforcement Learning on LLMs

Method for cost-efficient reinforcement learning on LLMs using preemptible cloud resources, optimizing rollout and training stages separately.

Ax Zihan Zhao, Kaushik Pendiyala, Masood Mortazavi, Ning Yan 4/9/2026

PULSE: Privileged Knowledge Transfer from Rich to Deployable Sensors for Embodied Multi-Sensory Learning

Framework for transferring knowledge from rich sensor modalities to deployable sensors in embodied AI systems using multi-sensory learning.

Ax Mohammadreza Malekabbasi, Minghe Wang, David Bermbach 4/9/2026

DisCEdge: Distributed Context Management for Large Language Models at the Edge

DisCEdge manages distributed context for LLM services at edge nodes, enabling stateful deployments across geo-distributed infrastructure.

Ax Minjun Zhao, Xinyu Zhang, Shuai Zhang, Deyang Li, Ruifeng Shi 4/9/2026

ADOPT: Adaptive Dependency-Guided Joint Prompt Optimization for Multi-Step LLM Pipelines

ADOPT framework for joint prompt optimization across multi-step LLM pipelines using dependency analysis and error propagation.

Ax Mayank Sharma, Roy Pea, Hari Subramonyam 4/9/2026

ConvoLearn: A Dataset for Fine-Tuning Dialogic AI Tutors

ConvoLearn dataset of 2,134 tutor-student dialogues for fine-tuning educational AI systems aligned with dialogic learning principles.

Ax Tianhao Qian, Zhuoxuan Li, Jinde Cao, Xinli Shi, Leszek Rutkowski 4/9/2026

Resource-constrained Amazons chess decision framework integrating large language models and graph attention

Hybrid framework combining LLMs and graph attention networks for Amazons chess in resource-constrained environments.