Ax Zewen Liu 7/2/2026

EPC: A Standardized Protocol for Measuring Evaluator Preference Dynamics in LLM Agent Systems

EPC protocol standardizes measurement of evaluator preference coupling in LLM agent feedback loops.

Ax Zewen Liu 7/2/2026

Mapping the Evaluation Frontier: An Empirical Survey of the Bias-Reliability Tradeoff Across Eleven Evaluator-Agent Conditions

Empirical survey of 11 evaluator-agent conditions exploring bias-reliability tradeoff in LLM evaluation systems.

Ax John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Tom Goldstein 7/2/2026

Watermarking for Proprietary Dataset Protection

Uses output watermarking techniques to make training data membership inference more tractable for generative language models.

Ax Gil Pasternak 7/2/2026

K-Inverse-RFM: A Modified RFM that Bridges the Gap to Neural Networks for Data-Corrupted Mathematical Tasks

K-Inverse-RFM modifies recursive feature machines to improve performance on corrupted mathematical tasks compared to neural networks.

Ax Jongchan Park, Seungjun Oh, Seungho Baek, Yusung Kim 7/2/2026

Learning Generalizable Skill Policy with Data-Efficient Unsupervised RL

GenDa addresses non-stationary skill semantics and generalization in unsupervised RL for skill-conditioned policy pre-training.

Ax Konstantin Garbers 7/2/2026

Gauging, Measuring, and Controlling Critic Complexity in Actor-Critic Reinforcement Learning

Introduces spectral effective-rank entropy as diagnostic for critic complexity in actor-critic RL methods.

Ax Tong Xu, Xinzhe Cao, Zhihui Zhu, Keyan Ding, Huajun Chen 7/2/2026

MolSafeEval: A Benchmark for Uncovering Safety Risks in AI-Generated Molecules

Benchmark for evaluating safety risks in AI-generated molecules, addressing toxicity and hazard detection.

Ax Xiao Han, Jingjing Liu, Moxuan Zheng, Zhen Zhang, Chenyu Wu 7/2/2026

Interpretable vs Learned Encoders for High-Cardinality Fraud Detection

Comparison of seven categorical encoding methods for high-cardinality fraud detection on IEEE-CIS benchmark dataset.

Ax Peilin Liu, Ding-Xuan Zhou 7/2/2026

Ghost in the Kernel: In-Context Learning with Efficient Transformers via Domain Generalization

Linear transformers enable efficient in-context learning with reduced computational complexity while maintaining task generalization.

Ax Anindya Sarkar, Nasik Muhammad Nafi, Isaac Lyngaas, Muralikrishnan Gopalakrishnan Meena, Yevgeniy Vorobeychik 7/2/2026

PAPA: Online Personalized Active Preference Alignment

Diffusion models fine-tuned via RL for personalized recommender systems using interactive user feedback.

Ax Dan Ley, Giang Nguyen, Himabindu Lakkaraju, Julius Adebayo 7/2/2026

Prototype Language Models

arXiv paper introducing prototype language models that make training data influence explicit and traceable for interpretability.

Ax Xuefeng Liu, Mingxuan Cao, Qinan Huang, Thomas Brettin, Rick Stevens, Le Cong 7/2/2026

Active-GRPO: Adaptive Imitation and Self-Improving Reasoning for Molecular Optimization

arXiv paper combining adaptive imitation learning and RL for improving LLM reasoning in molecular optimization.

Ax Zhiqi Li, Wen Zhang, Bo Zhu 7/2/2026

Flow-Map GRPO: Reinforcement Learning for Few-Step Flow-Map Generators via Anchored Stochastic Composition

arXiv paper on RL post-training for few-step flow-map generators using anchored stochastic composition.

Ax Aiden Durrant, Rahul Baburajan, Georgios Leontidis 7/2/2026

Group-Equivariant Poincar\'e Convolutional Networks

arXiv paper on group-equivariant convolutional networks in hyperbolic space for visual representations.

Ax Haeun Jeon, Seunghoon Choi, Hyunglip Bae, Yongjae Lee, Woo Chang Kim 7/2/2026

Decision-focused Sparse Tangent Portfolio Optimization

arXiv paper on decision-focused learning for sparse portfolio optimization using end-to-end framework.

Ax Tejas Pradeep Shirodkar 7/2/2026

Measuring Dead Directions: Decomposing and Classifying Singular Structure off Canonical Alignment

arXiv paper measuring singular structure in neural networks through directional-Fisher rate analysis.

Ax Darshan Patil, Ekaterina Lobacheva, Razvan Pascanu, Sarath Chandar 7/2/2026

Loss Smoothing for Stable Adaptation Under Distribution Shift

arXiv paper on loss smoothing technique to stabilize neural network adaptation under distribution shift.

Ax Yifei Sun, Zemin Liu, Bryan Hooi, Yang Yang, Rizal Fathony, Jia Chen, Bingsheng He 7/2/2026

Multi-Label Node Classification with Label Influence Propagation

arXiv paper on multi-label node classification using label influence propagation on graphs.

Ax Bin Du, Chang Liu, Dingqi Zhu, Lintao Ye, Dengfeng Sun 7/2/2026

Distributed Online Bandit Submodular Maximization with Bounded Sampling Violations

arXiv paper on distributed online submodular maximization with bandit feedback across multiple agents.

Ax Seokhee Jin, Changhwan Sung, Sunung Mun, Hoyoung Kim, Jungseul Ok 7/2/2026

AdaBoosting Text Prompts for Vision-Language Models

arXiv paper using AdaBoosting for adapting text prompts in vision-language models with few labeled examples.

Ax Edouard R. Dufour, Pascal Fua 7/2/2026

Generative Refinement for Low-Budget Black-Box Optimization

arXiv paper on generative models for low-budget black-box optimization with noisy or expensive evaluations.

Ax Seung Hun Han, Hyeongwon Kang, Jinwoo Park, Pilsung Kang 7/2/2026

Detecting the Undetectable: Enhancing Unsupervised time series Anomaly Detection via Active Learning

arXiv paper combining active learning with unsupervised methods to detect anomalies in time series data.

Ax Hanning Yang, Meropi Karakioulaki, Lennart Purucker, Tim Litwin, Cristina Has, Moritz Hess 7/2/2026

LLM-Guided ODE Discovery and Parameter Inference from Small-Cohort Aggregate Data

arXiv paper using LLMs to guide ODE discovery and parameter inference from limited clinical data for rare diseases.

Ax Sheng Qiang, Ruiwei Chen, Yinpeng Wu, Jinyu Gu, Zhichao Hua, Yubin Xia, Binyu Zang, Haibo Chen 7/2/2026

MosaicKV: Serving Long-Context LLM with Dynamic Two-D KV Cache Compression

arXiv paper on MosaicKV, a dynamic 2D KV cache compression technique for serving long-context LLMs efficiently.

Ax Yu Yao, Huanjian Zhou, Andi Han, Wei Huang, Masashi Sugiyama 7/2/2026

Accelerating Discrete Diffusion Models with Parallel-In-Time Sampling

arXiv paper parallelizing discrete diffusion model sampling via τ-leaping algorithm in CTMC framework for faster generation.

Ax Jinwen Wang, Youfang Lin, Xiaobo Hu, Qian Xu, Shuo Wang, Zhuo Chen, Kai Lv 7/2/2026

Task-Relevant Representation Decoupling for Visual Reinforcement Learning Generalization

arXiv paper proposing task-relevant representation decoupling for visual RL to improve generalization across environments.

Ax Jinwen Wang, Youfang Lin, Xiaobo Hu, Shuo Wang, Kai Lv 7/2/2026

Local Motion Matters: A Deconstruct-Recompose Paradigm for Reinforcement Learning Pre-training from Videos

arXiv paper on RL pre-training from videos using local motion patterns for better transfer across different agent morphologies.

Ax Jinwen Wang, Youfang Lin, Xiaobo Hu, Siyu Yang, Sheng Han, Shuo Wang, Kai Lv 7/2/2026

From Pixels to Temporal Correlations: Learning Informative Representations for Reinforcement Learning Pre-training

Unsupervised pre-training method for RL using temporal correlations from large-scale video datasets to improve sample efficiency.

Ax Hauke Maathuis, Roeland De Breuker, Saullo Castro, Maike Osborne 7/2/2026

Constrained Bayesian Optimisation with Multiple Information Sources

Bayesian optimization method using multiple information sources for constrained design space exploration with small feasible regions.

Ax Fei Wang, Chao Xue, Taoran Liu, Li Shen, Ye Liu, ChangXing Ding 7/2/2026

Beyond Activation Alignment:The Alignment-Diversity Tradeoff in Task-Aware LLM Quantization

arXiv paper on mixed-precision LLM quantization identifying alignment-diversity tradeoff and perplexity illusion phenomenon.

Ax Christopher Lindenberg, Kashyap Chitta 7/2/2026

Valdi: Value Diffusion World Models

arXiv paper on Value Diffusion World Models combining diffusion models with model predictive control for latent planning.

Ax Midhun Parakkal Unni, Samuel Kaski 7/2/2026

Human-Machine Collaboration on Generative Meta-Learning: Model and Algorithm

arXiv paper proposing Generative Meta-Learning with Human Feedback (GMHF) framework for domain generalization.

Ax Martino Ciaperoni, Margherita Lalli, Simone Piaggesi, Martina Varisco, Francesco Carli, Riccardo Guidotti, Dino Pedreschi, Francesco Raimondi, Fosca Giannotti 7/2/2026

Explainable AI for Cancer Drug Response Prediction: Beyond Univariate Feature Attributions

arXiv paper on explainable AI for cancer drug response prediction using multivariate feature attribution methods.

Ax Ludwig Winkler, Andrew Leaver-Fay, Joseph Kleinhenz, Pan Kessel 7/2/2026

Diffeomorphic Optimization

arXiv paper on diffeomorphic optimization for solving objectives on low-dimensional manifolds using diffusion models.

Ax Alexander Chemeris, Ming Jin, Randall Balestriero 7/2/2026

LeNEPA: No-Augmentation Next-Latent Prediction for Time-Series Representation Learning

arXiv paper on LeNEPA self-supervised learning method for time-series representation without data augmentation.

Ax Chandni Nagda, Mayank Shrivastavam Gudrun Thorkelsdottir, Gan Zhang, Morteza Mardani, Arindam Banerjee 7/2/2026

Generative Model Proposal based Particle Filtering for Data Assimilation

arXiv paper on particle filtering for data assimilation using generative models as proposal distributions.

Ax Yahya Aalaila, Gerrit Gro{\ss}mann, Sebastian Vollmer 7/2/2026

Seahorse: A Unified Benchmarking Framework for Spatiotemporal Event Modeling

Seahorse: unified benchmarking framework for spatiotemporal point process models with standardized evaluation methodology.

Ax Andrzej Szablewski, Gabriel Konar-Steenberg, Raffaello Fornasiere, Nikita Menon, Stefan Heimersheim 7/2/2026

The Model Organism Lottery: Model Organism Interpretability Strongly Depends on Training Methodology

arXiv paper showing model organism interpretability depends strongly on training methodology, affecting white-box interpretability evaluation.

Ax Soosung Kim, Minjae Park, Eui-Young Chung, Jaeyong Chung 7/2/2026

GSRQ: Gain-Shape Residual Quantization for Sub-1-bit KV Cache

arXiv paper proposing GSRQ for sub-1-bit KV cache quantization in large language models via gain-shape residual quantization.

Ax Yuqi Huang, Vincent Y. F. Tan, Sharu Theresa Jose 7/2/2026

Balancing Expressivity and Learnability in Quantum Kernel Bandit Optimization

arXiv paper on Gaussian process bandit optimization using quantum kernels for NISQ-era quantum tasks.

Ax Yahya Aalaila, Mouad Elhamdi, Gerrit Gro{\ss}mann, Daniel Jenson, Elizaveta Semenova, Sebastian Vollmer 7/2/2026

When Context Compensates for Sparse Event History: AlphaEarth for Spatio-Temporal Point-Process Forecasting

arXiv paper on AlphaEarth for spatio-temporal point-process forecasting using spatial context embeddings.

Ax Jingwei Song, Haofeng Xu, Jie Xiao, Chengke Bao, Jingwei Shi, Pengbin Feng, Weixun Wang, Yuhang Han, Chuan Wu, Linfeng Zhang, Bill Shi 7/2/2026

Staleness-Learning Rate Scaling Laws for Asynchronous RLHF

arXiv paper studying staleness effects in asynchronous RLHF systems with scaling laws for policy optimization.

Ax Zinan Tang, Yukun Zhang, Shaomian Zheng, Zhuoshi Pan, Qizhi Pei, Dingnan Jin, Jun Zhou, Yujun Wang, Biqing Huang 7/2/2026

CausalMix: Data Mixture as Causal Inference for Language Model Training

arXiv paper on CausalMix for optimizing data mixture weights in LLM training using causal inference without retraining.

Ax Miruna Cretu, John Bradshaw, Patricia Suriana, Saeed Saremi, Omar Mahmood, Kirill Shmilovich, Kangway Chuang, Vishnu Sresht, Colin Grambow 7/2/2026

SynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore Profiles

arXiv paper on SynLaD latent diffusion framework for generating synthesizable drug molecules with pharmacophore constraints.

Ax Hao Huang 7/2/2026

Muon as a Residual Connection

arXiv paper proposing Muon optimizer as implicit residual connection during neural network training, explaining its effectiveness.

Ax Xun Dong, Yibo Xu, Naigang Wang, Xin Li, Penghang Yin, Zi Yang 7/2/2026

ZO-Act: Efficient Zeroth-Order Fine-Tuning via One-Shot Activation-Informed Low-Rank Subspaces

arXiv paper presenting ZO-Act for efficient zeroth-order fine-tuning of large language models using activation-informed low-rank subspaces.

Ax Meenakshi Krishnan, Pranav Pulijala, Ke Chen, Haizhao Yang, Ramani Duraiswami 7/2/2026

GAIA: Geometry-Adaptive Operator Learning for Forward and Inverse Problems

arXiv paper on GAIA, a geometry-adaptive neural operator learning method for PDEs including boundary value and inverse problems.

Ax Binglin Ji, Anindya Sarkar, Hengchang Lu, Jens Sj\"olund, Yevgeniy Vorobeychik 7/2/2026

Sequentially-Controlled Interactive Multi-Particle Flow-Maps for Online Feedback-Driven Search

arXiv paper proposing IMPF for reward alignment in generative models with sequential feedback-driven exploration.

Ax Siwon Kim 7/2/2026

A Lightweight Self-Supervised Learning Framework for Multivariate Time Series using Hierarchical-JEPA on ECG Data

ER-JEPA lightweight self-supervised learning framework using hierarchical joint-embedding predictive architecture for ECG signal analysis.

Ax Kornelius Raeth, Nicole Ludwig 7/2/2026

Decision-Aware Training for Sample-Based Generative Models

Decision-aware training framework for generative models in forecasting that optimizes for downstream decision maker costs instead of standard scoring rules.