Hao Mark Chen - RankMe

19 papers A* 3Journal 12Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Dynamic Expert Sharing: Decoupling Memory from Parallelism in Mixture-of-Experts Diffusion LLMs. CoRR Hao Mark Chen, Zhiwen Mo, Royson Lee, Qianzhou Wang, Da Li, Shell Xu Hu, Wayne Luk, Timothy M. Hospedales, Hongxiang Fan
2026	—	`conf`	Enhancing Trustworthiness with Mixed Precision: Benchmarks, Opportunities, and Challenges. ASP-DAC Guanxi Lu, Hao Mark Chen, Zhiqiang Que, Wayne Luk, Hongxiang Fan
2026	—	`conf`	FastTTS: Accelerating Test-Time Scaling for Edge LLM Reasoning. ASPLOS (2) Hao Mark Chen, Zhiwen Mo, Guanxi Lu, Shuang Liang, Lingxiao Ma, Wayne Luk, Hongxiang Fan
2026	—	`conf`	Hardware-Efficient Union-Find Decoder Towards Scalable Topological Quantum Codes. ASP-DAC Shuang Liang, Jubo Xu, Yuncheng Lu, Hao Mark Chen, Bo Yuan, Hongxiang Fan
2025	J	`jnl`	AdaBlock-dLLM: Semantic-Aware Diffusion LLM Inference via Adaptive Block Size. CoRR Guanxi Lu, Hao Mark Chen, Yuto Karashima, Zhican Wang, Daichi Fujiki, Hongxiang Fan
2025	J	`jnl`	Advancing AI-assisted Hardware Design with Hierarchical Decentralized Training and Personalized Inference-Time Optimization. CoRR Hao Mark Chen, Zehuan Zhang, Wanru Zhao, Nicholas D. Lane, Hongxiang Fan
2025	J	`jnl`	Democratizing Agentic AI with Fast Test-Time Scaling on the Edge. CoRR Hao Mark Chen, Zhiwen Mo, Guanxi Lu, Shuang Liang, Lingxiao Ma, Wayne Luk, Hongxiang Fan
2025	A*	`conf`	Enhancing LLM-based Quantum Code Generation with Multi-Agent Optimization and Quantum Error Correction. DAC Charlie Campbell, Hao Mark Chen, Wayne Luk, Hongxiang Fan
2025	J	`jnl`	Enhancing LLM-based Quantum Code Generation with Multi-Agent Optimization and Quantum Error Correction. CoRR Charlie Campbell, Hao Mark Chen, Wayne Luk, Hongxiang Fan
2025	J	`jnl`	Enhancing Trustworthiness with Mixed Precision: Benchmarks, Opportunities, and Challenges. CoRR Guanxi Lu, Hao Mark Chen, Zhiqiang Que, Wayne Luk, Hongxiang Fan
2025	J	`jnl`	FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization. CoRR Hao Mark Chen, Shell Xu Hu, Wayne Luk, Timothy M. Hospedales, Hongxiang Fan
2025	—	`conf`	Hardware-Aware Parallel Prompt Decoding for Memory-Efficient Acceleration of LLM Inference. EMNLP (Findings) Hao Mark Chen, Wayne Luk, Yiu Ka Fai Cedric, Rui Li, Konstantin Mishchenko, Stylianos I. Venieris, Hongxiang Fan
2025	A*	`conf`	Progressive Mixed-Precision Decoding for Efficient LLM Inference. ICLR Hao Mark Chen, Fuwen Tan, Alexandros Kouris, Royson Lee, Hongxiang Fan, Stylianos I. Venieris
2025	J	`jnl`	Rethinking Optimal Verification Granularity for Compute-Efficient Test-Time Scaling. CoRR Hao Mark Chen, Guanxi Lu, Yasuyuki Okoshi, Zhiwen Mo, Masato Motomura, Hongxiang Fan
2024	J	`jnl`	Enhancing Dropout-based Bayesian Neural Networks with Multi-Exit on FPGA. CoRR Hao Mark Chen, Liam Castelli, Martin Ferianc, Hongyu Zhou, Shuanglong Liu, Wayne Luk, Hongxiang Fan
2024	A*	`conf`	Hardware-Aware Neural Dropout Search for Reliable Uncertainty Prediction on FPGA. DAC Zehuan Zhang, Hongxiang Fan, Hao Mark Chen, Lukasz Dudziak, Wayne Luk
2024	J	`jnl`	Hardware-Aware Neural Dropout Search for Reliable Uncertainty Prediction on FPGA. CoRR Zehuan Zhang, Hongxiang Fan, Hao Mark Chen, Lukasz Dudziak, Wayne Luk
2024	J	`jnl`	Hardware-Aware Parallel Prompt Decoding for Memory-Efficient Acceleration of LLM Inference. CoRR Hao Mark Chen, Wayne Luk, Ka Fai Cedric Yiu, Rui Li, Konstantin Mishchenko, Stylianos I. Venieris, Hongxiang Fan
2024	J	`jnl`	Progressive Mixed-Precision Decoding for Efficient LLM Inference. CoRR Hao Mark Chen, Fuwen Tan, Alexandros Kouris, Royson Lee, Hongxiang Fan, Stylianos I. Venieris