Ax Robert Aufschl\"ager, Jakob Folz, Gautam Savaliya, Manjitha D Vidanalage, Michael Heigl, Martin Schramm 4/13/2026

Towards Context-Aware Image Anonymization with Multi-Agent Reasoning

CAIAMAR: multi-agent framework for context-aware image anonymization in street-level imagery using agentic reasoning.

Ax Haochuan Kevin Wang, Zechen Zhang 4/13/2026

Kill-Chain Canaries: Stage-Level Tracking of Prompt Injection Across Attack Surfaces and Model Safety Tiers

Kill-chain canary methodology for tracking prompt injection attacks across multi-agent LLM systems with stage-level diagnostics.

Ax Hita Kambhamettu, Will Crichton, Sean Welleck, Harrison Goldstein, Andrew Head 4/13/2026

Explorable Theorems: Making Written Theorems Explorable by Grounding Them in Formal Representations

System for making mathematical theorems interactive by grounding LLM-generated explanations in formal representations enabling execution and stepping.

Ax Myra Cheng, Isabel Sieh, Humishka Zope, Sunny Yu, Lujain Ibrahim, Aryaman Arora, Jared Moore, Desmond Ong, Dan Jurafsky, Diyi Yang 4/13/2026

Verbalizing LLMs' assumptions to explain and control sycophancy

Framework for eliciting and verbalizing LLM assumptions to explain and mitigate sycophantic behavior in model outputs.

Ax Yi Zhou 4/13/2026

From Paper to Program: Accelerating Quantum Many-Body Algorithm Development via a Multi-Stage LLM-Assisted Workflow

Multi-stage LLM-assisted workflow for scientific algorithm development separating theory extraction, formal specification, and code generation.

Ax Cheol Woo Kim, Jai Moondra, Roozbeh Nahavandi, Andrew Perrault, Milind Tambe, Swati Gupta 4/13/2026

Many Preferences, Few Policies: Towards Scalable Language Model Personalization

Method for LLM personalization using a small portfolio of models capturing diverse user preferences without per-user models.

Ax Zequn Chen, Wesley J. Marrero 4/13/2026

Boosted Distributional Reinforcement Learning: Analysis and Healthcare Applications

Distributional reinforcement learning approach for decision-making in healthcare, accounting for uncertainty across heterogeneous populations.

Ax Jingwei Zuo, Xinze Feng, Zien Liu, Kaijian Wang, Fanjiang Ye, Ye Cao, Zhuang Wang, Yuke Wang 4/13/2026

ALTO: Adaptive LoRA Tuning and Orchestration for Heterogeneous LoRA Training Workloads

ALTO: system for adaptive LoRA hyperparameter tuning and orchestration across heterogeneous LLM fine-tuning workloads in multi-tenant environments.

Ax Yiquan Wu, Yuhang Liu, Yifei Liu, Ang Li, Siying Zhou, Kun Kuang, Fei Wu 4/13/2026

WisdomInterrogatory (LuWen): An Open-Source Legal Large Language Model Technical Report

WisdomInterrogatory (LuWen): open-source Chinese legal language model built on Baichuan foundation model for legal domain applications.

Ax Xue Qin, Simin Luan, John See, Cong Yang, Zhijun Li 4/13/2026

Governed Capability Evolution for Embodied Agents: Safe Upgrade, Compatibility Checking, and Runtime Rollback for Embodied Capability Modules

System for safe capability evolution in embodied agents with compatibility checking and runtime rollback mechanisms.

Ax Seungjae Moon, Seunghyun Oh, Youngmin Ro 4/13/2026

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation

Training-free open-vocabulary semantic segmentation framework (OV-Stitcher) leveraging pretrained vision-language models without additional training.

Ax Juwei Yue, Chuanrui Hu, Jiawei Sheng, Zuyi Zhou, Wenyuan Zhang, Tingwen Liu, Li Guo, Yafeng Deng 4/13/2026

HyperMem: Hypergraph Memory for Long-Term Conversations

HyperMem: hypergraph-based memory architecture for conversational agents enabling long-term context tracking and high-order associations.

Ax Yunsong Zhou, Hangxu Liu, Xuekun Jiang, Xing Shen, Yuanzhen Zhou, Hui Wang, Baole Fang, Yang Tian, Mulin Yu, Qiaojun Yu, Li Ma, Hengjie Li, Hanqing Wang, Jia Zeng, Jiangmiao Pang 4/13/2026

SIM1: Physics-Aligned Simulator as Zero-Shot Data Scaler in Deformable Worlds

Physics-aligned simulator (SIM1) for generating synthetic data in deformable object robotic manipulation tasks.

Ax Ruiyao Xu, Kaize Ding 4/13/2026

GNN-as-Judge: Unleashing the Power of LLMs for Graph Learning with GNN Feedback

Framework combining LLMs with graph neural networks for text-attributed graph learning in low-resource settings using GNN feedback.

Ax Ali Slim, Haydar Hamieh, Jawad Kotaich, Yehya Ghosn, Mahdi Chehimi, Ammar Mohanna, Hasan Abed Al Kader Hammoud, Bernard Ghanem 4/13/2026

QuanBench+: A Unified Multi-Framework Benchmark for LLM-Based Quantum Code Generation

QuanBench+ unified benchmark for LLM quantum code generation across Qiskit, PennyLane, Cirq with 42 aligned executable tasks.

Ax Pavel Golikov, Evgenii Opryshko, Gennady Pekhimenko, Mark C. Jeffrey 4/13/2026

Robust Reasoning Benchmark

Benchmark evaluating robustness of LLM reasoning with 14 perturbation techniques applied to mathematical reasoning tasks.

Ax Yeping Jin, Jiaming Hu, Ioannis Ch. Paschalidis 4/13/2026

Distributionally Robust Token Optimization in RLHF

DRTO combines token-level RLHF with distributional robustness to improve LLM resilience to input perturbations and formatting changes.

Ax Phong Lam, Ha-Linh Nguyen, Thu-Trang Nguyen, Son Nguyen, Hieu Dinh Vo 4/13/2026

Structured Exploration and Exploitation of Label Functions for Automated Data Annotation

Automated label function generation for data annotation using LLMs with structured exploration-exploitation strategy.

Ax Abdulrahman Albaiz, Fathi Amsaad 4/13/2026

Fully Autonomous Z-Score-Based TinyML Anomaly Detection on Resource-Constrained MCUs Using Power Side-Channel Data

TinyML Z-score anomaly detection system running on resource-constrained microcontrollers using power side-channel data.

Ax Chuxu Song, Zhencan Peng, Jiuqi Wei, Chuanhui Yang 4/13/2026

CSAttention: Centroid-Scoring Attention for Accelerating LLM Inference

CSAttention: sparse attention mechanism for accelerating LLM inference by reducing KV-cache bottlenecks through centroid-scoring without retraining.

Ax Matthew DosSantos DiSorbo, Harang Ju 4/13/2026

Act or Escalate? Evaluating Escalation Behavior in Automation with Language Models

Framework evaluating when LLMs should act versus escalate decisions using uncertainty estimation across five real-world domains.

Ax Brendan R. Hogan, Xiwen Chen, James T. Wilson, Kashif Rasul, Adel Boyarsky, Thomas Kamei, Anderson Schneider, Yuriy Nevmyvaka 4/13/2026

AlphaLab: Autonomous Multi-Agent Research Across Optimization Domains with Frontier LLMs

AlphaLab autonomous research system using frontier LLMs as agents to automate full experimental cycles in optimization domains without human intervention.

Ax Ivo Nowak 4/13/2026

StructRL: Recovering Dynamic Programming Structure from Learning Dynamics in Distributional Reinforcement Learning

StructRL: recovers dynamic programming structure from distributional RL learning dynamics. Bridges data-driven and structured approaches for stable learning.

Ax Yesmine Abdennadher, Philip N. Garner 4/13/2026

Practical Bayesian Inference for Speech SNNs: Uncertainty and Loss-Landscape Smoothing

Bayesian inference for spiking neural networks in speech processing. Explores weight uncertainty and loss landscape smoothing for temporal tasks.

Ax Yongchan Chun, Chanhee Park, Jeongho Yoon, Jaehyung Seo, Heuiseok Lim 4/13/2026

Evidential Transformation Network: Turning Pretrained Models into Evidential Models for Post-hoc Uncertainty Estimation

Evidential Transformation Network: adapts pretrained models for post-hoc uncertainty estimation. Efficient alternative to ensembles/MC dropout for deployed models.

Ax Rahul D Ray, Utkarsh Srivastava 4/13/2026

VOLTA: The Surprising Ineffectiveness of Auxiliary Losses for Calibrated Deep Learning

VOLTA: benchmark comparing uncertainty quantification methods for deep learning. Evaluates 10 UQ baselines across modalities and distribution shifts.

Ax Ramakrishnan Krishnamurthy, Arpit Agarwal, Lakshminarayanan Subramanian, Maximilian Nickel 4/13/2026

Creator Incentives in Recommender Systems: A Cooperative Game-Theoretic Approach for Stable and Fair Collaboration in Multi-Agent Bandits

Game-theoretic analysis of creator incentives in multi-agent recommender systems. Cooperative game formulation for fair collaboration in bandit problems.

Ax Maxim Ostroukhov, Ruslan Mikhailov, Vladimir Iashin, Artem Sokolov, Andrei Akshonov, Vitaly Protasov, Dmitrii Beloborodov, Vince Mullin, Roman Yokunda Enzmann, Georgios Kolovos, Jason Renders, Pavel Nesterov, Anton Repushko 4/13/2026

PRAGMA: Revolut Foundation Model

PRAGMA: foundation models for banking event sequences. Transformer-based architecture with self-supervised pretraining on financial transaction data.

Ax Fengwei Teng, Jinyi Bai, Xinhao Yao, Demi Ruohan Wang, Jiahao Zhao, Zhijiang Guo 4/13/2026

Skip-Connected Policy Optimization for Implicit Advantage

Skip-Connected Policy Optimization (SKPO) for reinforcement learning with reasoning tasks. Improves upon GRPO by addressing high-variance advantage estimation.

Ax Nan Huang, Xiaoxiao Zhou, Junxia Cui, Mario Tapia-Pacheco, Tiffany Amariuta, Yang Li, Jingbo Shang 4/13/2026

EvoLen: Evolution-Guided Tokenization for DNA Language Model

EvoLen: evolution-guided tokenization approach for DNA language models. Addresses fundamental tokenization design challenges in biological sequence modeling.

Ax Charles Arnal, Vivien Cabannes, Taco Cohen, Julia Kempe, Remi Munos 4/13/2026

Efficient RL Training for LLMs with Experience Replay

Experience replay for LLM post-training RL formalizing optimal buffer design as trade-off between sample efficiency and data freshness.

Ax Tiejin Chen, Huaiyuan Yao, Jia Chen, Evangelos E. Papalexakis, Hua Wei 4/13/2026

Every Response Counts: Quantifying Uncertainty of LLM-based Multi-Agent Systems through Tensor Decomposition

Tensor decomposition method quantifying uncertainty in LLM-based multi-agent systems accounting for communication and role dependencies.

Ax Diyi Hu, Bhaskar Krishnamachari 4/13/2026

Wireless Communication Enhanced Value Decomposition for Multi-Agent Reinforcement Learning

CLOVER framework for multi-agent RL cooperation conditioning value decomposition on realistic wireless communication graphs.

Ax Hananel Hazan, Yanbo Zhang, Benedikt Hartl, Michael Levin 4/13/2026

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need

LottaLoRA training paradigm showing frozen random backbones with trained LoRA adapters recover 96-100% performance across diverse tasks.

Ax Mingjie Hu, Siyang Gao, Jian-qiang Hu, Enlu Zhou 4/13/2026

Adaptive Simulation Experiment for LLM Policy Optimization

Adaptive simulation experiment framework using pairwise comparisons to optimize LLM policies for operations management tasks.

Ax Zhaolin Gao (Sid), Yu (Sid), Wang, Bo Liu, Thorsten Joachims, Kiant\'e Brantley, Wen Sun 4/13/2026

$p1$: Better Prompt Optimization with Fewer Prompts

Prompt optimization method decomposing reward variance into response and prompt variance to identify task amenability to optimization.

Ax Yashodhan D. Hakke, Almuatazbellah M. Boker, Lamine Mili, Michael von Spakovsky, Hoda Eldardiry 4/13/2026

Alleviating Community Fear in Disasters via Multi-Agent Actor-Critic Reinforcement Learning

Multi-agent actor-critic reinforcement learning for disaster resilience controlling power, communication, and emergency response systems.

Ax Mehran Taghian, Yunke Peng, Xing Huang, Yao Wang, Yaoyuan Wang, Wei Guo, Yuanyong Luo, Tianchi Hu, Junsong Wang, Xin Wang, Hu Liu, Yu Cheng, Ziwei Yu, Hongliang Li, Mehdi Rahimifar, Lei Yan, Xuefei Wang, Zhuang Ma, Lei Liu, Hui Yu, Anandharaju Durai Raju, Hoang Le, Hei Yi Mak, Tanzila Rahman, Shadan Golestan 4/13/2026

HiFloat4 Format for Language Model Pre-training on Ascend NPUs

4-bit floating-point format (HiFloat4) for efficient language model pre-training on Ascend NPU hardware.

Ax Chia-Hong Hsu, Randall Balestriero 4/13/2026

Post-Hoc Guidance for Consistency Models by Joint Flow Distribution Learning

Guidance method for consistency models using joint flow distribution learning to enable classifier-free guidance without separate teacher model.

Ax Chia-Hong Hsu, Frank Wood 4/13/2026

Discrete Meanflow Training Curriculum

Training curriculum method for discrete flow-based image generation models to improve one-step sampling stability and quality.

Ax Roi Paul 4/13/2026

Spectral Geometry of LoRA Adapters Encodes Training Objective and Predicts Harmful Compliance

Analysis of LoRA adapter spectral geometry to identify fine-tuning objectives and predict harmful model behavior in language models.

Ax Jinqi Luo, Jinyu Yang, Tal Neiman, Lei Fan, Bing Yin, Son Tran, Mubarak Shah, Ren\'e Vidal 4/13/2026

Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs

Safety steering mechanism for multimodal LLMs using dictionary-aligned concept control to prevent unsafe outputs without retraining.

Ax Yuwen Jiang 4/13/2026

Finite-Sample Analysis of Nonlinear Independent Component Analysis:Sample Complexity and Identifiability Bounds

Theoretical analysis of finite-sample properties and identifiability bounds for nonlinear Independent Component Analysis algorithms.

Ax Amrut Nadgir, Vijay Balasubramanian, Pratik Chaudhari 4/13/2026

How does Chain of Thought decompose complex tasks?

Demonstrates power-law scaling of classification error with number of classes and how chain-of-thought decomposition reduces error through task splitting.

Ax Tokio Kajitsuka, Ukyo Honda, Sho Takase 4/13/2026

Revisiting the Capacity Gap in Chain-of-Thought Distillation from a Practical Perspective

Practical analysis of chain-of-thought distillation from students to teachers, revisiting capacity gap assumptions and baseline comparisons.

Ax Abhiram Vellore, Niraj K. Jha 4/13/2026

Uncertainty-Aware Transformers: Conformal Prediction for Language Models

Conformal prediction framework for transformers providing uncertainty quantification and calibration for trustworthy LLM deployment.

Ax Hang Gao, Kunyu Li, Huang Hong, Baoquan Cui, Fengge Wu 4/13/2026

A Closer Look at the Application of Causal Inference in Graph Representation Learning

Analysis of causal inference applications in graph representation learning and risks of aggregating graph elements.

Ax Donney Fan, Geoff Pleiss 4/13/2026

Adaptive Candidate Point Thompson Sampling for High-Dimensional Bayesian Optimization

Adaptive Thompson sampling for high-dimensional Bayesian optimization addressing sparse candidate point grids.

Ax Taojie Zhu, Dongyang Xu, Ding Zou, Sen Zhao, Qiaobo Hao, Zhiguo Yang, Yonghong He 4/13/2026

Bridging SFT and RL: Dynamic Policy Optimization for Robust Reasoning

Dynamic policy optimization bridging SFT and RL for LLMs, addressing bias-variance tradeoff in post-training through adaptive loss weighting.

Ax Zhipeng Zhou, Linxiao Cao, Pengcheng Wu, Peilin Zhao, Chunyan Miao 4/13/2026

Delve into the Applicability of Advanced Optimizers for Multi-Task Learning

Empirical study on effectiveness of advanced optimizers for multi-task learning, identifying overlooked factors in optimization approaches.