Ax Andrew Lanpouthakoun, Aryaman Arora, Zhengxuan Wu, Dhruv Pai, Ben Keigwin, Dan Jurafsky, Christopher Potts 5/15/2026

PreFT: Prefill-only finetuning for efficient inference

Parameter-efficient finetuning method optimizing prefill-only updates to improve inference throughput for personalized LLMs.

Ax Tianle Zhong, Neiwen Ling, Yifan Pi, Zijun Wei, Tianshu Yu, Geoffrey Fox, Peng Wu, Xiao Yu 5/15/2026

Diagnosing Training Inference Mismatch in LLM Reinforcement Learning

Identifies and diagnoses training-inference mismatches in LLM reinforcement learning from implementation differences in token probabilities.

Ax Simranjeet Singh Dahia, Claudia Szabo 5/15/2026

Quantum Advantage in Multi Agent Reinforcement Learning

Empirical evaluation of quantum entanglement benefits in decentralized multi-agent reinforcement learning with variational quantum policies.

Ax Jerem\'ias Figueiredo Paschmann, Juan Kaplan, Francisco Nattero Santiago Mauricio Barron Bucolo, Juan Wisznia, Luciano del Corro 5/15/2026

Active Learners as Efficient PRP Rerankers

Active learning approach to improve pairwise ranking prompting reranking from LLMs with noisy and intransitive judgments.

Ax Andrii Shportko, Inessa Verbitsky 5/15/2026

Paraphrasing Attack Resilience of Various AI-Generated Text Detection Methods

Evaluation of AI-generated text detection methods' resilience to paraphrasing attacks across fine-tuned and classifier approaches.

Ax Kexin Chu, Dawei Xiang, Wei Zhang 5/15/2026

Latency-Quality Routing for Functionally Equivalent Tools in LLM Agents

Router for LLM agents selecting among functionally equivalent tool providers based on latency and quality tradeoffs.

Ax Zhiye Song, Kyungmi Lee, Eun Kyung Lee, Xin Zhang, Tamar Eilam, Anantha P. Chandrakasan 5/15/2026

EnergyLens: Predictive Energy-Aware Exploration for Multi-GPU LLM Inference Optimization

Framework for predicting and optimizing energy consumption during multi-GPU LLM inference without expensive profiling.

Ax Sibo Jia, Zihang Zhao, Kunrong Li 5/15/2026

Architecture-Aware Explanation Auditing for Industrial Visual Inspection

Auditing protocol to verify that deep neural network heatmap explanations faithfully reflect actual model decision drivers in industrial inspection.

Ax Jesseba Fernando, Grigori Guitchounts 5/15/2026

Dynamics of the Transformer Residual Stream: Coupling Spectral Geometry to Network Topology

Analysis of how computation propagates through transformer layers by studying residual stream dynamics and spectral geometry in LLMs.

Ax Weisen Jiang, Shuhao Chen, Sinno Jialin Pan 5/15/2026

MetaMoE: Diversity-Aware Proxy Selection for Privacy-Preserving Mixture-of-Experts Unification

MetaMoE unifies independently trained domain-specialized experts into privacy-preserving MoE using public proxy data for federated settings.

Ax Libo Sun, Po-wei Harn, Peixiong He, Xiao Qin 5/15/2026

Minimal-Intervention KV Retention: A Design-Space Study and a Diversity-Penalty Survivor

KV-cache compression study with diversity-penalty survivor method for efficient LLM inference on long-form reasoning tasks.

Ax Matias Alvo, Daniel Russo, Yash Kanoria 5/15/2026

Policy Optimization in Hybrid Discrete-Continuous Action Spaces via Mixed Gradients

Mixed gradient policy optimization for hybrid discrete-continuous action spaces in robotics and control problems.

Ax Qiyuan Chen, Jiayu Zhou, Raed Al Kontar 5/15/2026

Language-Induced Priors for Domain Adaptation

Domain adaptation framework leveraging expert textual descriptions as language-induced priors to prevent negative transfer in cold-start scenarios.

Ax Zuyuan Zhang, Carlee Joe-Wong, Tian Lan 5/15/2026

Matrix-Space Reinforcement Learning for Reusing Local Transition Geometry

Matrix-Space RL reuses local transition geometry through positive semidefinite matrix descriptors for compositional generalization.

Ax Yuchen Sun, Pei Fu, Shaojie Zhang, Anan Du, Xiuwen Xi, Ruoceng Zhang, Zhenbo Luo, Jian Luan, Chongyang Zhang 5/15/2026

Beyond Binary: Reframing GUI Critique as Continuous Semantic Alignment

Continuous semantic alignment framework for GUI critic models in test-time scaling for generalist AI agents beyond binary classification.

Ax Fangyuan Yu, Xin Su, Amir Abdullah 5/15/2026

Dynamic Latent Routing

Dynamic Latent Routing composes optimal sub-policies temporally for MDPs and proposes LLM post-training method based on General Dijkstra Search.

Ax Yerin Park, Sangseon Lee 5/15/2026

AIM-DDI: A Model-Agnostic Multimodal Integration Module for Drug-Drug Interaction Prediction

AIM-DDI predicts drug-drug interactions using model-agnostic multimodal integration with focus on unseen-drug generalization.

Ax Jessica Rumbelow 5/15/2026

Exemplar Partitioning for Mechanistic Interpretability

Exemplar Partitioning constructs interpretable feature dictionaries from LLM activations using Voronoi partitioning with 1000x fewer tokens than sparse autoencoders.

Ax Nicholas E. Corrado, Wenyuan Huang, Josiah P. Hanna 5/15/2026

Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling

Distributionally robust multi-task reinforcement learning addresses imbalanced learning across tasks via adaptive task sampling.

Ax Zhengjia Zhong, Shuyan Ke, Zaizhou Lin, Jiaqi Song, Hongyi Lan, Hui Li 5/15/2026

RQ-MoE: Residual Quantization via Mixture of Experts for Efficient Input-Dependent Vector Compression

RQ-MoE combines residual quantization with mixture-of-experts for efficient input-dependent vector compression of embeddings.

Ax Jiaqi Sun, Boyang Sun, Mohamad Rasmy, Xiangchen Song, Kun Zhang 5/15/2026

MoRe: Modular Representations for Principled Continual Representation Learning on Squantial Data

MoRe proposes modular representations for continual learning on sequential data with minimal catastrophic forgetting.

Ax Changryeol Choi, Hyewon Park, Yujin Kwon, Gowun Jeong 5/15/2026

LoMETab: Beyond Rank-1 Ensembles for Tabular Deep Learning

LoMETab extends rank-1 ensembles to rank-r multiplicative factorizations for improved tabular deep learning performance.

Ax Chen Liang, Xiatao Sun, Qian Wang, Daniel Rakita 5/15/2026

Turning Stale Gradients into Stable Gradients: Coherent Coordinate Descent with Implicit Landscape Smoothing for Lightweight Zeroth-Order Optimization

Coherent Coordinate Descent optimizes zeroth-order optimization for memory-constrained on-device learning without backpropagation.

Ax Young-Chae Hong, Yangho Chen 5/15/2026

Optimal Pattern Detection Tree for Symbolic Rule-Based Classification

Optimal Pattern Detection Tree introduces interpretable rule-based classification model for pattern discovery in healthcare and maintenance domains.

Ax JB Lanier, Nathan Monette, Pierre Baldi, Roy Fox 5/15/2026

Data-Augmented Game Starts for Accelerating Self-Play Exploration in Imperfect Information Games

Multi-agent exploration strategy for imperfect-information games like StarCraft using data-augmented game starts to accelerate policy gradient learning.

Ax Qazi Mamunur Rashid, Xuan Yang, Zhengzhe Yang, Yanzhou Pan, Erin van Liemt, Darlene Neal, Kshitij Pancholi, Jamila Smith-Loud 5/15/2026

NodeSynth: Socially Aligned Synthetic Data for AI Evaluation

NodeSynth generates socially aligned synthetic data for AI model evaluation using a fine-tuned taxonomy generator anchored in real-world evidence.

Ax Donghwan Kim, Hyunsoo Yoon 5/15/2026

MahaVar: OOD Detection via Class-wise Mahalanobis Distance Variance under Neural Collapse

Novel OOD detection method using class-wise Mahalanobis distance variance for neural networks in safety-critical applications.

Ax Shuqi Gu, Yongxiang Zhao, Baoyu Jing, Kan Ren 5/15/2026

What if Tomorrow is the World Cup Final? Counterfactual Time Series Forecasting with Textual Conditions

Counterfactual time series forecasting method incorporating textual conditions for future events influence.

Ax Leo Muxing Wang, Pengkun Yang, Lili Su 5/15/2026

Collaborative Yet Personalized Policy Training: Single-Timescale Federated Actor-Critic

Federated actor-critic framework for collaborative policy training with shared representations and personalized local policies.

Ax Runyuan He, Qiuyang Mang, Shang Zhou, Kaiyuan Liu, Hanchen Li, Huanzhi Mao, Qizheng Zhang, Zerui Li, Bo Peng, Lufeng Cheng, Tianfu Fu, Yichuan Wang, Wenhao Chai, Jingbo Shang, Alex Dimakis, Joseph E. Gonzalez, Alvin Cheung 5/15/2026

FrontierSmith: Synthesizing Open-Ended Coding Problems at Scale

FrontierSmith: Method for synthesizing open-ended coding problems at scale to train stronger LLM coders.

Ax Siyang Yao, Erhu Feng, Yubin Xia 5/15/2026

When Answers Stray from Questions: Hallucination Detection via Question-Answer Orthogonal Decomposition

QAOD: Single-pass white-box framework for hallucination detection in LLMs using question-answer orthogonal decomposition.

Ax Minbeom Kim, Lesly Miculicich, Bhavana Dalvi Mishra, Mihir Parmar, Phillip Wallis, Bharath Chandrasekhar, Kyomin Jung, Tomas Pfister, Long T. Le 5/15/2026

LiSA: Lifelong Safety Adaptation via Conservative Policy Induction

LiSA: lifelong safety adaptation framework for AI agents executing workflows, maintaining guardrails against contextual safety failures in tool use and data access.

Ax Elias Zavitsanos, Georgios Paliouras 5/15/2026

Focused PU learning from imbalanced data

Method for positive-unlabeled learning from highly imbalanced datasets, applicable to disease identification, fraud detection, and recommender systems.

Ax Weijia Xu, Alessandro Sordoni, Chandan Singh, Zelalem Gero, Michel Galley, Xingdi Yuan, Jianfeng Gao 5/15/2026

Test-Time Learning with an Evolving Library

EvoLib: test-time learning framework enabling LLMs to accumulate and evolve knowledge across problem instances via extracted modular skills without parameter updates.

Ax Letian Yang (Shanghai Jiao Tong University, Shanghai, China), Xu Liu (Shanghai Jiao Tong University, Shanghai, China), Yiqiang Lu (Ant Group, Shanghai, China), Jian Liu (Ant Group, Shanghai, China), Weiqiang Wang (Ant Group, Shanghai, China), Shuai Li (Shanghai Jiao Tong University, Shanghai, China) 5/15/2026

ROAD: Adaptive Data Mixing for Offline-to-Online Reinforcement Learning via Bi-Level Optimization

Offline-to-online reinforcement learning method using bi-level optimization for adaptive data mixing between datasets.

Ax Wenwen Li, Yuki Orimo, Nontawat Charoenphakdee 5/15/2026

Lang2MLIP: End-to-End Language-to-Machine Learning Interatomic Potential Development with Autonomous Agentic Workflows

Autonomous agentic workflow for end-to-end machine learning interatomic potential development with adaptive active learning.

Ax Stef De Sabbata, Rahul Baiju, Stefano Mizzaro, Kevin Roitero 5/15/2026

Exploring Geographic Relative Space in Large Language Models through Activation Patching

Mechanistic interpretability study using activation patching to examine how LLMs process relative geographic space.

Ax Shuhao Chen, Weisen Jiang, Changmiao Wang, Xiaoqing Wu, Xuanren Shi, Yu Zhang, James T. Kwok 5/15/2026

RxEval: A Prescription-Level Benchmark for Evaluating LLM Medication Recommendation

Benchmark for evaluating LLM medication recommendations at prescription level with per-timepoint predictions and information-rich inputs.

Ax Pengkai Wang, Pengwei Liu, Yuanyi Wang, Guanyu Chen, Xingyu Ren, Xiaolong Li, Zhongkai Hao, Yuting Kong, Qixin Zhang, Dong Ni 5/15/2026

Discovering Physical Directions in Weight Space: Composing Neural PDE Experts

Weight space analysis of neural PDE operators identifying reusable physical structure across multiple regimes in pretrained models.

Ax Donghao Li, Chengshuai Shi, Weijuan Ou, Cong Shen, Jing Yang 5/15/2026

Efficient Multi-objective Prompt Optimization via Pure-exploration Bandits

Multi-objective prompt optimization technique using pure-exploration bandits for efficient LLM prompt selection.

Ax Langzhou He, Junyou Zhu, Yue Zhou, Zhengyao Gu, Junhua Liu, Wei-Chieh Huang, Henry Peng Zou, David Wipf, Philip S. Yu, Qitian Wu 5/15/2026

Resolving Action Bottleneck: Agentic Reinforcement Learning Informed by Token-Level Energy

Token-level credit assignment method for agentic RL using energy-based perspectives to improve PPO and GRPO training signals.

Ax Oubo Ma, Ruixiao Lin, Yang Dai, Jiahao Chen, Chunyi Zhou, Linkang Du, Shouling Ji 5/15/2026

Angel or Demon: Investigating the Plasticity Interventions' Impact on Backdoor Threats in Deep Reinforcement Learning

Studies impact of plasticity interventions on backdoor attack vulnerabilities in deep reinforcement learning agents.

Ax Zhipeng Zhang 5/15/2026

Silent Collapse in Recursive Learning Systems

Identifies silent collapse phenomenon in recursive learning systems where models trained on self-generated data degrade undetected by standard metrics.

Ax Andreas Schlaginhaufen, Maryam Kamgarpour 5/15/2026

Fast Rates for Inverse Reinforcement Learning

Statistical results for entropy-regularized inverse reinforcement learning with linear reward classes in finite-horizon MDPs.

Ax Sohaib Afifi 5/15/2026

An Amortized Efficiency Threshold for Comparing Neural and Heuristic Solvers in Combinatorial Optimization

Analysis of energy efficiency comparing neural combinatorial optimization solvers to CPU metaheuristics accounting for training costs.

Ax Manrui Jiang, Jingru Huang, Yong Chen, Chen Zhang 5/15/2026

DRL-STAF: A Deep Reinforcement Learning Framework for State-Aware Forecasting of Complex Multivariate Hidden Markov Processes

Deep reinforcement learning framework combining HMMs with neural networks for forecasting multivariate hidden Markov processes.

Ax Shin So, Kyelim Lee, Albert No 5/15/2026

Slower Generalization, Faster Memorization: A Sweet Spot in Algorithmic Learning

Study of grokking phenomenon showing Transformers achieve fastest validation accuracy at intermediate dataset sizes, not largest ones.

Ax Nabil Iqbal, T. Anderson Keller, Yue Song, Takeru Miyato, Max Welling 5/15/2026

Spontaneous symmetry breaking and Goldstone modes for deep information propagation

Studies Goldstone-like modes in equivariant deep neural networks, demonstrating how symmetry breaking enables coherent information propagation across layers.

Ax Davide Scassola, Andrea Coser, Sebastiano Saccani 5/15/2026

ReMIA: a Powerful and Efficient Alternative to Membership Inference Attacks against Synthetic Data Generators

Proposes ReMIA, efficient membership inference attack against synthetic data generators that avoids shadow model overhead for privacy evaluation.

Ax Tommaso Mencattini, Francesco Montagna, Francesco Locatello 5/15/2026

The Rate-Distortion-Polysemanticity Tradeoff in SAEs

Characterizes tradeoff between reconstruction accuracy, feature efficiency, and interpretability in sparse autoencoders for mechanistic interpretability.