activity
20232026
most citedHongTu: Scalable Full-Graph GNN Training on Multiple GPUs (via communication-optimized CPU data offloading)

23 citations · 42 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.RO2026

ActTune: Action-Aware Precision and GPU Operating-Point Adaptation for Energy-Efficient Vision-Language-Action Inference

Zou Qingyun, Bin Gao, Wenju Zhao +3

Vision-language-action (VLA) policies repeatedly invoke inference to control robots, making graphics processing unit (GPU) energy a recurring cost of task execution. Reducing energ…

cs.AR2026

ECO: Energy-Oriented Configuration Optimization for Attention FFN Disaggregated LLM Serving

Zou Qingyun, Bin Gao, Zhuobin Huang +3

Energy-efficient LLM serving requires minimizing serving GPU energy while meeting latency and throughput service-level objectives (SLOs). Attention--FFN disaggregation (AFD) enable…

cs.CL2026

SePO: Self-Evolving Prompt Agent for System Prompt Optimization

Wangcheng Tao, Han Wu, Weng-Fai Wong

System prompt optimization improves agent behavior without modifying the underlying model, yielding human-readable, model-agnostic instructions. Existing methods build a prompt age…

cs.AR2026

Is Agentic AI Ready for Real-World Hardware Engineering? A Deep Dive with Phoenix-bench

Qingyun Zou, Feng Yu, Hongshi Tan +2

We ask whether agentic AI systems built for software engineering transfer to realistic hardware engineering. Existing hardware LLM benchmarks isolate sub-tasks but none jointly req…

cs.AR2026

Reward-Weighted On-Policy Distillation with an Open Property-Equivalence Verifier for NL-to-SVA Generation

Qingyun Zou, Yingze Li, Tianen Liu +2

LLM-based generation of SystemVerilog Assertions (SVA) is often reported as nearing saturation, with the strongest specialized model reaching accuracy on NL2SVA-Human.…

cs.LG2026

HLS-Seek: QoR-Aware Code Generation for High-Level Synthesis via Proxy Comparative Reward Reinforcement Learning

Qingyun Zou, Feng Yu, Hongshi Tan +3

High-Level Synthesis (HLS) compiles algorithmic C/C++ descriptions into hardware, with Quality of Results (QoR)---latency and resource utilization---critically governed by pragma c…