collaborators

5 papers

cs.LG2026

AcceptMoE: Commitment-Weighted Self-Sizing Verifier Expert Sets for Efficient MoE Speculative Decoding

Shuang Liang, Hao Mark Chen, Hao +6

Speculative decoding verifies a tree of draft tokens in one target-model forward pass. For a mixture-of-experts (MoE) target, however, parallel verification can activate the union…

cs.AR2026

Coset Ensemble Decoder for Quantum Error Correction with Algorithm-Hardware Co-Design

Shuang Liang, Jubo Xu, Giulio Bassanino +8

Reliable large-scale quantum computation relies on fault-tolerant architectures, where quantum error correction (QEC) continuously extracts and decodes error syndromes in real time…

cs.NI2026

SPAC: Automating FPGA-based Network Switches with Protocol Adaptive Customization

Guoyu Li, Yang Cao, Lucas H L Ng +9

With network requirements diverging across emerging applications, latency-critical services demand minimal logic delay, while hyperscale training and collectives require sustained…

cs.AR2026

DeepStack: Facilitating Co-Design Exploration of 3D DRAM-Stacked Accelerators for Distributed LLM Inference

Zhiwen Mo, Guoyu Li, Hao Mark Chen +11

Advances in hybrid bonding and packaging have driven growing interest in 3D DRAM-stacked AI accelerators. As large language models (LLMs) scale to hundreds of billions or trillions…

cs.LG2026

Dynamic Expert Sharing: Decoupling Memory from Parallelism in Mixture-of-Experts Diffusion LLMs

Hao Mark Chen, Zhiwen Mo, Royson Lee +6

Among parallel decoding paradigms, diffusion large language models (dLLMs) have emerged as a promising candidate that balances generation quality and throughput. However, their int…