Ax Ali Forootani, Raffaele Iervolino 3/16/2026

Learnable Koopman-Enhanced Transformer-Based Time Series Forecasting with Spectral Control

Integration of Koopman operator theory with transformer architectures for time series forecasting with learnable spectral parameterizations.

Ax Kevin Zhai, Sabbir Mollah, Zhenyi Wang, Mubarak Shah 3/16/2026

CORE: Context-Robust Remasking for Diffusion Language Models

Decoding strategy for masked diffusion language models that dynamically adjusts token retention based on context coverage.

Ax Nghia Nguyen, Tianjiao Ding, Ren\'e Vidal 3/16/2026

Hierarchical Concept Embedding & Pursuit for Interpretable Image Classification

Interpretable image classification using hierarchical concept embeddings recovered from vision-language model latent spaces.

Ax Zhen Bi, Xueshu Chen, Luoyang Sun, Yuhang Yao, Qing Shen, Jungang Lou, Cheng Deng 3/16/2026

RooflineBench: A Benchmarking Framework for On-Device LLMs via Roofline Analysis

Benchmarking framework using roofline analysis to characterize performance of small language models on resource-constrained edge hardware.

Ax Chethana Prasad Kabgere, Shylaja SS 3/16/2026

On the Geometric Coherence of Global Aggregation in Federated Graph Neural Networks

Federated learning approach addressing heterogeneous graph structures in distributed GNN training across multiple clients.

Ax Shubhangi Upasani, Chen Wu, Jay Rainton, Bo Li, Urmish Thakker, Changran Hu, Qizheng Zhang 3/16/2026

Test-Time Adaptation via Many-Shot Prompting: Benefits, Limits, and Pitfalls

Study of many-shot in-context learning as test-time adaptation for LLMs, analyzing benefits and reliability limits with open-source models.

Ax Jonas Landsgesell, Pascal Knoll 3/16/2026

Distributional Regression with Tabular Foundation Models: Evaluating Probabilistic Predictions via Proper Scoring Rules

Evaluation framework using proper scoring rules for assessing distributional predictions from tabular foundation models beyond point estimates.

Ax Hiroki Naganuma, Atish Agarwala, Priya Kasimbeg, George E. Dahl 3/16/2026

What do near-optimal learning rate schedules look like?

Search procedure to identify optimal learning rate schedule shapes for neural network training across different workloads.

Ax Amit Singh, Vedant Nipane, Pulkit Agrawal, Jatin Kishnani, Sairanjan Mishra 3/16/2026

H2LooP Spark Preview: Continual Pretraining of Large Language Models for Low-Level Embedded Systems Code

Continual pretraining of LLMs specialized for low-level embedded systems code generation, targeting underrepresented hardware domains.

Ax Yichuan Deng, Zhao Song, Kaijun Yuan, Tianyi Zhou 3/16/2026

Why Softmax Attention Outperforms Linear Attention

Comparative analysis of softmax vs linear attention mechanisms in transformer architectures, examining computational efficiency tradeoffs.

Ax Guido Di Federico, Louis J. Durlofsky 3/16/2026

Latent diffusion models for parameterization and data assimilation of facies-based geomodels

Latent diffusion models for geological parameterization and data assimilation, generating realistic geomodels with reduced variables for history matching.

Ax Jianwei Li, Jung-Eun Kim 3/16/2026

Superficial Safety Alignment Hypothesis

Analyzes brittleness of LLM safety alignment mechanisms, proposing superficial safety alignment hypothesis explaining why standard alignment approaches are vulnerable.

Ax Pablo de los Riscos, Fernando J. Corbacho 3/16/2026

Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots

Active causal structure learning framework enabling autonomous robots and AGI agents to dynamically construct causal models of environmental interactions.

Ax Xialie Zhuang, Zhikai Jia, Jianjin Li, Zhenyu Zhang, Li Shen, Zheng Cao, Shiwei Liu 3/16/2026

Mask-Enhanced Autoregressive Prediction: Pay Less Attention to Learn More

Training paradigm integrating masked language modeling with next-token prediction to improve in-context retrieval in large language models.

Ax Deyu Bo, Songhua Liu, Xinchao Wang 3/16/2026

Understanding Dataset Distillation via Spectral Filtering

Spectral filtering framework unifying dataset distillation methods by interpreting them as filters affecting feature correlation eigenvalues.

Ax Jonathan Garc\'ia, Philipp Petersen 3/16/2026

Minimax learning rates for estimating binary classifiers under margin conditions

Theoretical analysis of minimax learning rates for binary classification under geometric margin conditions with horizon function decision boundaries.

Ax Vinod Raman, Hilal Asi, Satyen Kale 3/16/2026

AdaBoN: Adaptive Best-of-N Alignment

Prompt-adaptive Best-of-N alignment strategy using reward models to reduce computational cost of test-time alignment for language models.

Ax Thai-Hoc Vu, Ngo Hoang Tu, Thien Huynh-The, Kyungchun Lee, Sunghwan Kim, Miroslav Voznak, Quoc-Viet Pham 3/16/2026

Integration of TinyML and LargeML: A Survey of 6G and Beyond

Survey on integrating TinyML and LargeML for 6G networks, covering deep learning applications in mobile systems, autonomous vehicles, and smart services.

Ax Konstantin Dobler, Desmond Elliott, Gerard de Melo 3/16/2026

Token Distillation: Attention-aware Input Embeddings For New Tokens

Attention-aware embedding initialization method for new tokens in LLMs without expensive retraining, addressing vocabulary limitations in specialized domains.

Ax Tobias J. Riedlinger, Kira Maag, Hanno Gottschalk 3/16/2026

Towards Reliable Detection of Empty Space: Conditional Marked Point Processes for Object Detection

Conditional marked point processes for reliable object detection uncertainty quantification, addressing miscalibrated confidence scores in neural networks.

Ax Amirabbas Hojjati, Lu Li, Ibrahim Hameed, Anis Yazidi, Pedro G. Lind, Rabindra Khadka 3/16/2026

From Video to EEG: Adapting Joint Embedding Predictive Architecture to Uncover Saptiotemporal Dynamics in Brain Signal Analysis

Self-supervised learning approach adapting joint embedding architecture from video to EEG signals for brain activity analysis with limited labeled data.

Ax Maida Wang, Xiao Xue, Mingyang Gao, Peter V. Coveney 3/16/2026

Quantum-Informed Machine Learning for Predicting Spatiotemporal Chaos with Practical Quantum Advantage

Quantum-informed ML framework combining quantum generative models with classical predictors for long-term spatiotemporal chaos prediction.

Ax Wei Lu, Amit Dhanda, Daniel L. Chen, Christian B. Hansen 3/16/2026

Aligning Large Language Model Agents with Rational and Moral Preferences: A Supervised Fine-Tuning Approach

Supervised fine-tuning method to align LLM agents with rational and moral preferences in strategic economic games, addressing systematic behavioral deviations.

Ax Alexandre Brown, Glen Berseth 3/16/2026

SegDAC: Visual Generalization in Reinforcement Learning via Dynamic Object Tokens

Object-centric representations for visual RL policies using dynamic tokens to improve generalization under visual condition changes without fixed-size slots.

Ax Gabriele Digregorio, Marco Di Gennaro, Stefano Zanero, Stefano Longari, Michele Carminati 3/16/2026

On the (In)Security of Loading Machine Learning Models

Security evaluation of ML model sharing frameworks and hubs, assessing vulnerabilities in loading shared models and security awareness gaps among practitioners.

Ax Yinzhanghao Zhou, Tsung-Han Lee, Ao Chen, Nicola Lanat\`a, Hong Guo 3/16/2026

Neural-Quantum-States Impurity Solver for Quantum Embedding Problems

Neural quantum states impurity solver for quantum embedding problems. Graph transformer-based NQS for solving Hamiltonians in quantum chemistry.

Ax Tongfei Guo, Lili Su 3/16/2026

Dynamic Aware: Adaptive Multi-Mode Out-of-Distribution Detection for Trajectory Prediction in Autonomous Vehicles

Dynamic Aware: out-of-distribution detection for trajectory prediction in autonomous vehicles. Adaptive multi-mode approach for distribution shift in AVs.

Ax Ahmed Jaber, Wangshu Zhu, Ayon Roy, Karthick Jayavelu, Justin Downes, Sameer Mohamed, Candace Agonafir, Linnia Hawkins, Tian Zheng 3/16/2026

AutoClimDS: Climate Data Science Agentic AI -- A Knowledge Graph is All You Need

AutoClimDS: agentic AI system for climate data science. Knowledge graph-based workflows for discovering climate patterns from fragmented data sources.

Ax Katsuhiko Hayashi, Hidetaka Kamigaito 3/16/2026

From Formal Language Theory to Statistical Learning: Finite Observability of Subregular Languages

Formal language theory applied to statistical learning. Proves subregular language classes are linearly separable with simple models.

Ax Shuofei Qiao, Yanqiu Zhao, Zhisong Qiu, Xiaobin Wang, Jintian Zhang, Zhao Bin, Ningyu Zhang, Yong Jiang, Pengjun Xie, Fei Huang, Huajun Chen 3/16/2026

Scaling Generalist Data-Analytic Agents

DataMind: scalable data-analytic AI agents for automated discovery. Open-source agent framework handling diverse-format data files and multi-step reasoning.

Ax Hritik Bansal, Devendra Singh Sachan, Kai-Wei Chang, Aditya Grover, Gargi Ghosh, Wen-tau Yih, Ramakanth Pasunuru 3/16/2026

HoneyBee: Data Recipes for Vision-Language Reasoners

HoneyBee: data curation approaches for vision-language reasoning datasets. Analyzes impact of context, content, and format on VLM reasoning capabilities.

Ax Lizhi Yang, Blake Werner, Massimiliano de Sa, Aaron D. Ames 3/16/2026

CBF-RL: Safety Filtering Reinforcement Learning in Training with Control Barrier Functions

CBF-RL: integrates control barrier functions into reinforcement learning training. Enforces dynamic safety constraints during RL policy training, not just inference.

Ax Yash Jangir, Yidi Zhang, Pang-Chi Lo, Kashu Yamazaki, Chenyu Zhang, Kuan-Hsun Tu, Tsung-Wei Ke, Lei Ke, Yonatan Bisk, Katerina Fragkiadaki 3/16/2026

RobotArena $\infty$: Scalable Robot Benchmarking via Real-to-Sim Translation

RobotArena ∞: scalable robot benchmarking via real-to-sim translation. Enables rigorous evaluation of robot policies across diverse tasks and environments.

Ax Roy Rinberg, Adam Karvonen, Alexander Hoover, Daniel Reuter, Keri Warr 3/16/2026

Verifying LLM Inference to Detect Model Weight Exfiltration

Verifying LLM inference to detect model weight exfiltration via steganography. Defends inference servers against model theft and anomalous behavior.

Ax Anees Ur Rehman Hashmi, Numan Saeed, Christoph Lippert 3/16/2026

AnatomiX, an Anatomy-Aware Grounded Multimodal Large Language Model for Chest X-Ray Interpretation

AnatomiX: anatomy-aware multimodal LLM for chest X-ray interpretation. Improves spatial reasoning and anatomical understanding in medical imaging.

Ax Numan Halit Guldemir, Oluwafemi Olukoya, Jes\'us Mart\'inez-del-Rinc\'on 3/16/2026

FARM: Few-shot Adaptive Malware Family Classification under Concept Drift

FARM framework for malware family classification under concept drift. Uses triplet autoencoder for few-shot adaptation to covariate and label drift.

Ax Xinwu Ye, Yicheng Mao, Jia Zhang, Yimeng Liu, Li Hao, Fang Wu, Zhiwei Li, Yuxuan Liao, Zehong Wang, Yingcheng Wu, Zhiyuan Liu, Zhenfei Yin, Li Yuan, Philip Torr, Huan Sun, Xiangxiang Zeng, Mengdi Wang, Le Cong, Shenghua Gao, Xiangru Tang 3/16/2026

LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning

LatentChem: latent reasoning interface for chemical LLMs. Decouples chemical computation from discrete tokens to improve efficiency and performance in chemical reasoning.

Ax Arindam Khaled 3/16/2026

Pyramid MoA: A Probabilistic Framework for Cost-Optimized Anytime Inference

Pyramid MoA: probabilistic framework for cost-optimized LLM inference via cascading and routing. Balances inference cost and reasoning capability for large language models.

Ax Markus Knauer, Samuel Bustamante, Thomas Eiband, Alin Albu-Sch\"affer, Freek Stulp, Jo\~ao Silv\'erio 3/16/2026

IROSA: Interactive Robot Skill Adaptation using Natural Language

IROSA: framework combining foundation models with imitation learning for robot skill adaptation via natural language. LLM application to robotics.

Ax Jinman Wu, Yi Xie, Shen Lin, Shiqian Zhao, Xiaofeng Chen 3/16/2026

Knowing without Acting: The Disentangled Geometry of Safety Mechanisms in Large Language Models

Disentangled Safety Hypothesis: mechanistic study of LLM safety showing decoupling between harmfulness detection and refusal. ML interpretability research.

Ax Linus Folkerts, Will Payne, Simon Inman, Philippos Giavridis, Joe Skinner, Sam Deverett, James Aung, Ekin Zorer, Michael Schmatz, Mahmoud Ghanem, John Wilkinson, Alan Steer, Vy Hong, Jessica Wang 3/16/2026

Measuring AI Agents' Progress on Multi-Step Cyber Attack Scenarios

Benchmark evaluating frontier AI models on multi-step cyber attack scenarios. Agent capability measurement across extended action sequences.

Ax Mayank Saini, Arit Kumar Bishwas 3/16/2026

One Supervisor, Many Modalities: Adaptive Tool Orchestration for Autonomous Queries

Agentic framework for multimodal query processing with adaptive tool orchestration across text/image/audio/video. Research on agent coordination and tool selection.

Ax Abhinaba Basu, Pavan Chakraborty 3/16/2026

Proof-Carrying Materials: Falsifiable Safety Certificates for Machine-Learned Interatomic Potentials

Proof-Carrying Materials: falsifiable safety certificates for machine-learned interatomic potentials. ML research on reliability guarantees for scientific models.

BL 3/16/2026

Why Codex Security Doesn’t Include a SAST Report

Codex Security: AI agent for code security that analyzes repository architecture and trust boundaries before validating findings with humans.

HN mooreds 3/15/2026

Multi-agent fleet management for coding agents

Open-source AgentFactory orchestrates fleet of coding agents (Claude, Codex, Spring AI) through automated pipeline for issue resolution and code shipping.

HN jostylr 3/15/2026

OpenJarvis: Personal AI, on Personal Devices

Open-source framework for personal AI agents running entirely on-device with efficiency-aware evaluations and learning loop using local trace data.

HN EvanZhouDev 3/15/2026

Show HN: Free OpenAI API Access with ChatGPT Account

NPM package enabling free OpenAI API access via ChatGPT OAuth tokens. Creates localhost proxy to ChatGPT backend API with Vercel AI SDK provider support.

HN piotrgrudzien 3/15/2026

I'm Too Lazy to Check Datadog Every Morning, So I Made AI Do It

AI automation tool to summarize Datadog monitoring alerts and escalate issues, reducing manual dashboard review.

HN tjohnell 3/15/2026

LLMs can be absolutely exhausting

Discussion of mental fatigue and workflow challenges when working with LLMs like Claude and Codex, and recovery strategies.

HN jeremyjh 3/15/2026

Claude-Code-Workflow – Orchestrate Multiple CLI Agents

Multi-agent workflow orchestration system supporting Gemini, Qwen, Claude with role-based agents, background execution, and visual workflow editing.