3 citations · 3 across the 8 of their papers we have counts for
5 papers · 1 filter
FedQHD: Closed-Form Function-Space Federated Reinforcement Learning
Yuchen Hou, Yongshan Chen, Zhuowen Zou +4
Federated reinforcement learning enables decentralized agents to collaboratively improve policies or value estimates without exchanging raw trajectories. However, FedAvg-style para…
ReSAE: Residualized Sparse Autoencoders for Multi-Layer Transformer Interventions
Prathyush Poduval, Calvin Yeung, Neel Desai +1
Sparse autoencoders are usually trained one layer at a time, even though transformer residual stream activations are strongly coupled across depth. This creates a practical problem…
Geometric Priors for Generalizable World Models via Vector Symbolic Architecture
William Youngwoo Chung, Calvin Yeung, Hansen Jin Lillemark +3
A key challenge in artificial intelligence and neuroscience is understanding how neural systems learn representations that capture the underlying dynamics of the world. Most world…
Encoder-Free Knowledge-Graph Reasoning with LLMs via Hyperdimensional Path Retrieval
Yezi Liu, William Youngwoo Chung, Hanning Chen +2
Recent progress in large language models (LLMs) has made knowledge-grounded reasoning increasingly practical, yet KG-based QA systems often pay a steep price in efficiency and tran…
Generalized Holographic Reduced Representations
Calvin Yeung, Zhuowen Zou, SungHeon Jeong +3
Hyperdimensional Computing (HDC) is a computationally and data-efficient paradigm that acts as a bridge between connectionist and symbolic approaches to artificial intelligence (AI…