5 papers
Mechanism Design Is Not Enough: Prosocial Agents for Cooperative AI
Xuanqiang Angelo Huang, Charlie Tharas, Samuele Marro +4
Ensuring that AI agents behave safely and beneficially when interacting with other parties has emerged as one of the central challenges of modern AI safety. While mechanism design,…
Distribution-Aware Reward Estimation for Test-Time Reinforcement Learning
Bodong Du, Xuanqi Huang, Xiaomeng Li
Test-time reinforcement learning (TTRL) enables large language models (LLMs) to self-improve on unlabeled inputs, but its effectiveness critically depends on how reward signals are…
Single-Core Superscalar Optimization of Clifford Neural Layers
X. Angelo Huang, Ruben Ciranni, Giovanni Spadaccini +1
Within the growing interest in the physical sciences in developing networks with equivariance properties, Clifford neural layers shine as one approach that delivers and $O(n…
Clapping: Removing Per-sample Storage for Pipeline Parallel Distributed Optimization with Communication Compression
Boao Kong, Xu Huang, Yuqi Xu +3
Pipeline-parallel distributed optimization is essential for large-scale machine learning but is challenged by significant communication overhead from transmitting high-dimensional…
Neurons: Emulating the Human Visual Cortex Improves Fidelity and Interpretability in fMRI-to-Video Reconstruction
Haonan Wang, Qixiang Zhang, Lehan Wang +2
Decoding visual stimuli from neural activity is essential for understanding the human brain. While fMRI methods have successfully reconstructed static images, fMRI-to-video reconst…