Ax Eduardo Sebasti\'an, Nicolas Pfitzer, Ajay Shankar, Amanda Prorok 13d ago

Prompting Robot Teams with Natural Language

Framework for prompting multi-robot teams with natural language, decomposing collaborative tasks without runtime LLM calls.

Ax Christian Lagemann, Sajeda Mokbel, Miro Gondrum, Mario R\"uttgers, Yuning Wang, Pol Su\'arez, Ludger Paehler, Deniz A. Bezgin, Aaron B. Buhendwa, Jared L. Callaham, Samuel Ahnert, Nicholas Zolman, Xiao Shao, Jean-Christophe Loiseau, Nikolaus Adams, Matthias Meinke, Wolfgang Schr\"oder, Kai Lagemann, Esther Lagemann, Ricardo Vinuesa, Steven L. Brunton 13d ago

The HydroGym Reinforcement Learning Platform for Fluid Dynamics

HydroGym is a reinforcement learning benchmark platform for fluid dynamics control and modeling.

Ax Chika Maduabuchi, Jindong Wang 13d ago

Event-Driven Video Generation

Event-Driven Video Generation improves text-to-video models by selectively updating latent regions based on event interactions.

Ax Andrew Seohwan Yu, Mohsen Hariri, Kunio Nakamura, Mingrui Yang, Xiaojuan Li, Vipin Chaudhary 13d ago

Medical Image Spatial Grounding with Semantic Sampling

Medical image spatial grounding framework extends vision-language models to 3D anatomical structure localization in medical imaging.

Ax Zhuonan Yang, Jacob Xiaochen Li, Francisco Piedrahita Velez, Eric Todd, David Bau, Michael L. Littman, Stephen H. Bach, Ellie Pavlick 13d ago

Shared Lexical Task Representations Explain Behavioral Variability In LLMs

Analysis of prompt sensitivity in LLMs, showing shared lexical task representations explain behavioral variability between instruction and example-based prompting.

Ax Huixi Technology, :, Chen Zhang, Chenyang Zhou, Guanglei Ding, Guanghui He, Haibin Gao, Jiajia Chen, Jianyong Zhang, Lianyi Yu, Ningyi Xu, Ping Xu, Qingchen Li, Yingjun Hu, Yijia Zhang, Yuxi Liu 13d ago

RhinoVLA Technical Report

RhinoVLA: Vision-Language-Action model optimized for real-time robotic manipulation on edge hardware by reducing visual and context token overhead.

Ax Louis Bagot (SyCoSMA), Mathieu Lefort (LIRIS, SyCoSMA, IRISA, MALT, UR), La\"etitia Matignon (SyCoSMA) 13d ago

Exploration and Online Transfer with Behavioral Foundation Models

Research on behavioral foundation models for zero-shot transfer in RL, enabling agents to generate optimal policies for any reward function without task-specific learning.

HN brandonb 13d ago

LLM-style scaling laws hold for sensor data

Research showing that LLM-style scaling laws (loss vs. model/dataset size) apply to sensor data, with implications for AI economics and emergent capabilities.

HN c7ma23s 13d ago

Show HN: Yourself, in Every Light

Alma: local-first MCP server for AI agents to maintain persistent user context (name, preferences, values) across vendors without vendor lock-in.