Ax Lauri Suomela, Sasanka Kuruppu Arachchige, German F. Torres, Harry Edelman, Joni-Kristian K\"am\"ar\"ainen 2/26/2026

Synthetic vs. Real Training Data for Visual Navigation

Investigates sim-to-real gap in visual navigation by comparing simulator-trained and real-world-trained policies. Demonstrates simulator policies can match real-world performance.

Ax Kartik Hegde, Rehana Mahfuz, Yinyi Guo, Erik Visser 2/26/2026

Aligning Audio Captions with Human Preferences

Preference-aligned audio captioning framework using RLHF with CLAP-based reward model trained on human-labeled preferences. Addresses gap between supervised learning and real preferences.

Ax Advik Raj Basani, Pin-Yu Chen 2/26/2026

Diversity Boosts AI-Generated Text Detection

DivEye detector for AI-generated text using diversity metrics. Improves detection of synthetic text while providing interpretability over black-box classifiers.

Ax Raheem Karim Hashmani, Garrett W. Merz, Helen Qu, Mariel Pettee, Kyle Cranmer 2/26/2026

Multimodal Datasets with Controllable Mutual Information

Framework for generating multimodal datasets with controllable mutual information between modalities. Enables systematic study of MI estimators and multimodal self-supervised learning.

Ax NVIDIA, :, Arslan Ali, Junjie Bai, Maciej Bala, Yogesh Balaji, Aaron Blakeman, Tiffany Cai, Jiaxin Cao, Tianshi Cao, Elizabeth Cha, Yu-Wei Chao, Prithvijit Chattopadhyay, Mike Chen, Yongxin Chen, Yu Chen, Shuai Cheng, Yin Cui, Jenna Diamond, Yifan Ding, Jiaojiao Fan, Linxi Fan, Liang Feng, Francesco Ferroni, Sanja Fidler, Xiao Fu, Ruiyuan Gao, Yunhao Ge, Jinwei Gu, Aryaman Gupta, Siddharth Gururani, Imad El Hanafi, Ali Hassani, Zekun Hao, Jacob Huffman, Joel Jang, Pooya Jannaty, Jan Kautz, Grace Lam, Xuan Li, Zhaoshuo Li, Maosheng Liao, Chen-Hsuan Lin, Tsung-Yi Lin, Yen-Chen Lin, Huan Ling, Ming-Yu Liu, Xian Liu, Yifan Lu, Alice Luo, Qianli Ma, Hanzi Mao, Kaichun Mo, Seungjun Nah, Yashraj Narang, Abhijeet Panaskar, Lindsey Pavao, Trung Pham, Morteza Ramezanali, Fitsum Reda, Scott Reed, Xuanchi Ren, Haonan Shao, Yue Shen, Stella Shi, Shuran Song, Bartosz Stefaniak, Shangkun Sun, Shitao Tang, Sameena Tasmeen, Lyne Tchapmi, Wei-Cheng Tseng, Jibin Varghese, Andrew Z. Wang, Hao Wang, Haoxiang Wang, Heng Wang, Ting-Chun Wang, Fangyin Wei, Jiashu Xu, Dinghao Yang, Xiaodong Yang, Haotian Ye, Seonghyeon Ye, Xiaohui Zeng, Jing Zhang, Qinsheng Zhang, Kaiwen Zheng, Andrew Zhu, Yuke Zhu 2/26/2026

World Simulation with Video Foundation Models for Physical AI

Cosmos-Predict2.5 foundation model for world simulation unifying text/image/video generation. Leverages vision-language model for grounded physical AI predictions.

Ax Soufiane Hayou 2/26/2026

A Proof of Learning Rate Transfer under $\mu$P

Theoretical proof that optimal learning rates transfer across widths in MLPs with μP parameterization. Shows learning rate converges to nonzero constant at infinite width.

Ax Christian Catalini, Xiang Hui, Jane Wu 2/26/2026

Some Simple Economics of AGI

Economic analysis of AGI's impact on labor and growth. Argues human verification becomes the bottleneck as AI decouples cognition from biology.

HN shakiness3383 2/26/2026

Examining Bias and AI in Latin America

Study analyzing gender and social stereotypes in Spanish-language LLMs using 4,156 test questions from Latin American researchers.

HN OsamaJaber 2/26/2026

Open-Source Agent Operating System

Production-grade open-source agent operating system written in Rust with 137K LOC, 14 crates, comprehensive testing.

HN stagezerowil 2/26/2026

Claude Code Video Toolkit

Skills and MCP servers for Claude Code to generate videos programmatically using Remotion and FFmpeg.

HN e2e4 2/26/2026

Multi-agent workflows often fail

Analysis of multi-agent workflow failures, identifying three engineering patterns for reliable agent systems. Technical guidance on agent design.

HN acartag7 2/25/2026

Show HN: Edictum – Runtime governance for LLM agent tool calls

Edictum is a runtime governance library for LLM agents that enforces safety contracts at tool-call boundaries. Tested on 6 frontier models across 17,420 interactions, identifying a 'GAP' where models refuse harmful text requests but execute them via tool calls.

HN halst 2/25/2026

Say No to Human-AI Workflow Segregation

Opinion on documentation quality for both AI agents and humans. Argues against segregating workflows between human and AI use, advocating unified documentation standards.