Ax Yi\u{g}it Berkay Uslu, Samar Hadou, Sergio Rozada, Shirin Saeedi Bidokhti, Alejandro Ribeiro 7/9/2026

Generative Diffusion Models of Stochastic Graph Signals

Generative diffusion models for sampling stochastic signals on graphs, applied to recommender systems and financial forecasting.

Ax Tolgay Atinc Uzun, Waleed Khalid, Saif U Din, Sai Revanth Mulukuledu, Akashdeep Singh, Chandini Vysyaraju, Raghuvir Duvvuri, Avi Goyal, Yashkumar Rajeshbhai Lukhi, Muhammad A. Hussain, Krunal Jesani, Usha Shrestha, Yash Mittal, Roman Kochnev, Pritam Kadam, Mohsin Ikram, Harsh R. Moradiya, Alice Arslanian, Dmitry Ignatov, Radu Timofte 7/9/2026

LEMUR 2: Unlocking Neural Network Diversity for AI

LEMUR 2: Large-scale extensible NAS benchmark with 14,000+ distinct architectures and 750,000+ training records for cross-domain neural architecture evaluation.

Ax Nima Kelidari, Mohammadsaeed Haghi, Mahdi Salmani 7/9/2026

A Gold-Standard Study of What Makes a Lightweight Game-Playing Agent Strong

Empirical study using rule-based expert as benchmark to evaluate lightweight RL agents for imperfect-information card games across 100+ experiments.

Ax Josip Juki\'c, Ivan Titov 7/9/2026

Geometric Self-Distillation for Reasoning Generalization

On-policy self-distillation method for LLMs using geometric approaches where teacher model has access to solution hints to improve student model reasoning.

Ax Tianyi Ma, Hanzhang Qin, Ruihao Zhu, Jierui Zuo 7/9/2026

Best-Arm Identification with Generative Proxy

Best-arm identification algorithm that pairs costly reward observations with cheap proxy scores from LLMs to improve data-driven decision-making efficiency.

Ax Canlin Zhang, Xiuwen Liu 7/9/2026

Converge to Surprise: Evolutionary Self-supervised Image Clustering

Self-supervised image clustering framework using evolutionary algorithms instead of gradient descent, eliminating need for predefined loss targets.

Ax Shuo Huai, Di Liu, Hao Kong, Weichen Liu, Ravi Subramaniam, Christian Makaya, Qian Lin 7/9/2026

Latency-Constrained DNN Architecture Learning for Edge Systems using Zerorized Batch Normalization

DNN architecture learning for edge devices using zeroed batch normalization to meet strict latency constraints in real-time applications.

Ax Zhenghuang Wu, Yuyao Zhu, Songlin Xu 7/9/2026

Physical activities enable scalable foundation modelling for broad-spectrum health prediction

Wearable foundation model using physical activity data for scalable broad-spectrum health prediction.

Ax Dhruv Garg, Neha Lakhani, Debopam Sanyal, Myungjin Lee, Alexey Tumanov, Ada Gavrilovska 7/9/2026

Robust Federated Learning Under Real-World Client Churn

Federated learning approach for rapid model adaptation under real-world client churn in recommendation systems.

Ax Chongyu Fan, Pengfei Liu, Jingjia Huang, Sijia Liu, Yi Lin 7/9/2026

UP: Unbounded Positive Asymmetric Optimization for Breaking the Exploration-Stability Dilemma

Unbounded Positive optimization for RL addressing exploration-stability dilemma in LLM reasoning via importance sampling.

Ax Anthony Baez, Sheer Karny, Pat Pataranutaporn 7/9/2026

Dissociating the Internal Representations of Sycophancy in LLMs

Mechanistic analysis dissecting sycophancy in LLMs into factual and opinion subtypes using internal representations.

Ax Aoxiong Zeng, Yuxin Yang, Xiangquan Yang 7/9/2026

Online Data Selection Is Implicit Alignment

Study showing online data selection during fine-tuning acts as implicit alignment mechanism for LLM behavioral preferences.

Ax Meihua Dang, Stefano Ermon 7/9/2026

Constrained Decoding for Diffusion Language Models via Efficient Inference over Finite Automata

Constrained decoding for diffusion language models via finite automata enabling structured outputs like JSON schemas.

Ax Dennis Gross, Quentin Mazouni, Helge Spieker, Arnaud Gotlieb 7/9/2026

Gimitest: A Comprehensive Tool for Testing Reinforcement Learning Policies

Gimitest: Open-source comprehensive testing framework for single and multi-agent RL policies across varying conditions.

Ax Srikumar Krishnamoorthy 7/9/2026

Complexity-Budgeted, Interaction-Aware Interpretable Model for Tabular Data

Interpretable ML framework for tabular data addressing feature interactions through sparse rules and patterns.

Ax Alan Gany, Bogdan Cautis, Silviu Maniu 7/9/2026

Structural Adversarial Attacks on Relational Deep Learning under Integrity Constraints

Studies adversarial robustness of relational deep learning on heterogeneous temporal graphs with integrity constraints.

Ax Heye Huang, Jingguang Li, Zhiyuan Zhou, Paul Liang, Mingyu Wu, Kitae Jang, Jianqiang Wang 7/9/2026

A knowledge-augmented dataset of high-risk driving scenarios with LLM annotations for autonomous driving

K-Risk dataset combining high-risk driving scenarios with LLM annotations and semantic labels for autonomous driving safety research.

Ax Maximilian S. Ernst (Max Planck School of Cognition, Center for Lifespan Psychology Max Planck Institute for Human Development, Machine Learning Group Technische Universit\"at Berlin), Lorenz Linhardt (Machine Learning Group Technische Universit\"at Berlin, Berlin Institute for the Foundations of Learning and Data), Aaron Peikert (Center for Lifespan Psychology Max Planck Institute for Human Development), Oliver Eberle (Machine Learning Group Technische Universit\"at Berlin, Berlin Institute for the Foundations of Learning and Data) 7/9/2026

Distributed Sparse Interventions in Language Models

Studies causal interventions in language model components to understand task behavior, extending beyond global activation-space steering.

Ax Vladimir Gusev 7/9/2026

Fractal KV-Cache Archives: Lossless Symbolic Storage with In-Place Retrieval for Long-Context LLM Inference

Proposes lossless symbolic storage for KV-cache using contractive iterated-map codes to reduce memory cost in long-context LLM inference.

Ax Zhang Gongyue, Liu Donghan, Ren Weihong, Sheng Yixuan, Wang Zhiyong, Liu Honghai 7/9/2026

Information Allocation Dynamics in Neural Network Optimization

Analyzes optimizer implicit bias through information allocation dynamics, explaining how training signals distribute between weights.

Ax Zetian Hu, Shunyu Liu, Junjie Zhang, Yongcheng Jing, Ting-En Lin, Yongbin Li, Dacheng Tao 7/9/2026

Entropy Pacing Policy Optimization for Multi-Task Agentic Reinforcement Learning

Studies multi-task agentic RL for LLM-based agents, identifying exploration-exploitation dynamics across different tasks.

Ax Marcus Williams, Hannah Sheahan, Cameron Raymond, Tomek Korbak, Deng Pan, Peilin Yang, Leon Maksin, Ningyi Xie, Phillip Guo, Ian Kivlichan, Micah Carroll 7/9/2026

Predicting LLM Safety Before Release by Simulating Deployment

Method for pre-deployment safety evaluation of LLMs by simulating realistic deployments from de-identified conversations to assess failure rates.

Ax Zavier Li 7/9/2026

Geometric--Nongeometric Optimizer Calculus: A Modular Language for Reachable Gradient Methods

Modular language for characterizing reachable gradient methods, auditing optimizer mechanisms and their interactions systematically.

Ax Jinbo Yang, Mingyue Yuan, Boyuan Zhang, Yoshifumi Kitamura, Shikai Jing 7/9/2026

HPG-Diff: Hierarchical physics-guided diffusion with differentiable connectivity constraints for topology optimization

Proposes HPG-Diff, physics-guided diffusion framework for topology optimization with differentiable connectivity constraints.

Ax Georg Sch\"afer, Jakob Rehrl, Stefan Huber, Simon Hirlaender 7/9/2026

Safe Reinforcement Learning using Ideas from Model Predictive Control

Combines reinforcement learning with model predictive control to enforce hard safety constraints during exploration in cyber-physical systems.

Ax Donato Cerciello, Leonardo Schiavo, Angel Panizo-LLedot, Javier Huertas Tato, David Camacho 7/9/2026

FMMVCC: Fuzzy Mamba-based Multi-View Contrastive Clustering for Univariate Time Series

Presents FMMVCC, a Mamba-based clustering method for unsupervised time series analysis using fuzzy logic and contrastive learning.

Ax Chongkai Li, Bang Zhang, Wenjian Luo 7/9/2026

FedCVESA: Taking Away Training Data in Federated Learning via Correlation Value Encoding and Segmented Aggregation

Analyzes memorization-based privacy attacks (TATD) in federated learning, studying how malicious training can exfiltrate data in distributed settings.

Ax Pranav Sawant, Jakub Krej\v{c}\'i 7/9/2026

Mechanistic Interpretability for Neural Networks: Circuits, Sparse Features and Symbolic Reasoning

Comprehensive overview of mechanistic interpretability for reverse-engineering neural network internals, including circuit analysis and symbolic reasoning approaches.

Ax Zhiheng Zhou, Mengyao Zhou, Dengyi Zhao, Xingqin Qi, Guiying Yan 7/9/2026

Hypergraph Neural Stochastic Diffusion: An SDE Framework for Uncertainty Estimation

Proposes SDE framework for uncertainty estimation in hypergraph neural networks, addressing uncertainty from higher-order relations and complex dependencies.

Ax Oliver Makins, Orazio Angelini, Zohreh Shams, Mary Phuong 7/9/2026

Multi-Agent AI Control: Distributed Attacks Hamper Per-Instance Monitors

Studies multi-agent AI control techniques to prevent coordinated attacks across distributed AI deployments, addressing risks like model-weight exfiltration and training poisoning.

Ax Chethan Krishnamurthy Ramanaik, Tobias Callies, Michael Hecht, Eirini Ntoutsi 7/9/2026

On Adversarial Vulnerability of Vision-Language Models through the Lens of Intermediate Spectral Subspaces

Research on adversarial vulnerability in vision-language models through spectral analysis of intermediate linear transformations.

Ax Raiff H. Santos, Amilcar R. Queiroz, Tharcisyo S. S. Duarte, K. E. L. de Farias, Rafael A. Batista 7/9/2026

Generalist Vision-Language Models for Fast Radio Burst detection: a zero-shot benchmark against a specialized detector

Research benchmark evaluating open-weight vision-language models for fast radio burst detection; zero-shot generalist approach vs specialized detectors.

Ax Lo\"ic Cabannes, Pierre-Emmanuel Mazar\'e, Gergely Szilvasy, Matthijs Douze, Maria Lomeli, Ilze Amanda Auzina, Justin Carpentier, Gabriel Synnaeve, Herv\'e J\'egou 7/9/2026

Sparse Delta Memory: Scaling the State of Linear RNNs through Sparsity

Research introducing Sparse Delta Memory architecture for scaling linear RNNs; improves long-context recall while reducing FLOPs.

Ax Zhiyuan Li 7/9/2026

The Optimal Sample Complexity of Learning Autoregressive Chain-of-Thought

Theoretical analysis of sample complexity for learning autoregressive chain-of-thought traces; proves bounds governed by local next-token classification.

Ax Bojie Li, Noah Shi 7/9/2026

RLVP: Penalize the Path, Reward the Outcome

Research on reinforcement learning for real-world agents with irreversible interactions; proposes penalizing unsafe paths while rewarding outcomes.

Ax Vin\'icius Gabriel Angelozzi, H\'eber H. Arcolezi 7/9/2026

Where to Intervene? Benchmarking Fairness-Aware Learning on Differentially Private Synthetic Tabular Data

Research benchmark studying interaction between differential privacy and fairness-aware learning on synthetic tabular data in high-stakes ML.

Ax Athanasios Zeris 7/9/2026

FourierQK: Spectral Preprocessing of Query-Key Projections Improves Transformer Attention

Research: FFT-based spectral preprocessing of query-key projections improves transformer attention; 79% validation loss reduction on TinyShakespeare.

Ax Florian Fuchs, Jessy Gosselin-Grant, Boris Skuin, Michele Petteni, Alessandro Sestini, Joakim Bergdahl, Amir Baghi, Linus Gissl\'en 7/9/2026

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26

RAID framework uses reward-adaptive RL for automated game testing, reducing retesting effort after behavior modifications in NHL26 development via iterative goalie AI exploit discovery.

Ax Jaris K\"uken, Shi Bin Hoo, Martin Mr\'az, Frank Hutter, Lennart Purucker 7/9/2026

TimEE: End-to-end Time Series Classification via In-Context Learning

TimEE applies in-context learning to end-to-end time series classification, replacing two-stage train-then-classify pipeline with unified learning from label demonstrations.

Ax Zhenyu Hou, Yujiang Li, Jie Tang, Yuxiao Dong 7/9/2026

Single-Rollout Asynchronous Optimization for Agentic Reinforcement Learning

Asynchronous single-rollout RL system for LLM post-training on long-horizon agentic tasks, improving efficiency and training stability over synchronous batch-interleaved approaches.

Ax Adam M. Oberman 7/9/2026

Fast Rates for Semi-Supervised Learning via Data-Augmentation Graph Regularization

Theoretical explanation for self-supervised learning efficiency: data augmentation induces graph structure enabling fast transductive rates O(1/n_L) with graph-Laplacian regularization.

Ax Maximilian Andreas Hoefler, Karsten Mueller, Wojciech Samek 7/9/2026

Collaborative Synthetic Data Generation for Knowledge Transfer in Federated Learning

Collaborative synthetic data generation for one-shot federated learning, enabling knowledge transfer across divergent client distributions in single communication round.

Ax Ana Schwengber Kelm, Christian Bockermann, J\"org Frochte 7/9/2026

Multi-Class vs. Multi-Label BERT for CVE-to-CWE Mapping: How Taxonomy Structure Shapes the Errors

Compares multi-class vs multi-label BERT formulations for CVE-to-CWE vulnerability mapping, analyzing how taxonomy structure shapes classification errors.

Ax C G Krishnanunni, Thomas Scott, Tan Bui-Thanh 7/9/2026

An optimal control approach for neural network architecture adaptation with a posteriori error estimation

Formulates neural network depth adaptation as optimal control problem with posteriori error estimation, enabling principled layer insertion based on approximation error distribution.

Ax Shiheng Zhang 7/9/2026

Guidance Breaks the Fitted Operator: A Terminal-Fitted Repair for Classifier-Free Guidance

Analyzes classifier-free guidance breakdown in diffusion models through numerical analysis, proposing terminal-fitted repair to stabilize sampling at high guidance scales.

Ax Xinyi Wu, Siyuan Liu, Ali Jadbabaie 7/9/2026

How Data Shapes RoPE Frequency Usage: From Positional Scale Matching to Length Generalization

Analyzes how RoPE frequency usage in transformers matches training data's relative-distance structure, with implications for length generalization and position embeddings.

Ax Xiangming Huang, Guannan Zhang, Lu Lu, Rapha\"el Pestourie 7/9/2026

Neural Operator-enabled Topology-informed Evolutionary Strategy for PDE-Constrained Optimization

NOTES integrates neural operators with evolutionary strategies for PDE-constrained inverse design optimization, combining robustness with high-dimensional search capability.

Ax Eric Zhu, Abhinav Shrivastava, Soumik Mukhopadhyay 7/9/2026

Selective Timestep Weighting and Advantage-Based Replay for Sample-Efficient Diffusion RLHF

Novel method combining selective timestep weighting and advantage-based replay to improve sample efficiency of RLHF applied to diffusion models, reducing feedback requirements.

Ax Lucas Pinto 7/9/2026

Calibration-Family Overfit: Why Trusted Sabotage Monitors Don't Transfer Across Lineages

Shows trusted monitoring models overfit to specific untrusted policy families and don't generalize across model lineages.

Ax Ya Wang, Hanwei Fan, Zhenguo Liu, Xiaofeng Zhou, Yangdi Lyu, Jiang Xu, Wei Zhang 7/9/2026

HiFuzz: Hierarchical Reinforcement Learning for Semantic-Aware and Adaptive CPU Fuzzing

HiFuzz uses hierarchical reinforcement learning with structured generation agents for CPU fuzzing and processor verification.