activity
20222026
most citedLearning Domain-Aware Detection Head with Prompt Tuning

5 citations · 10 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2026

DA-Mamba: Learning Domain-Aware State Space Model for Global-Local Alignment in Domain Adaptive Object Detection

Haochen Li, Rui Zhang, Hantao Yao +5

Domain Adaptive Object Detection (DAOD) aims to transfer detectors from a labeled source domain to an unlabeled target domain. Existing DAOD methods employ multi-granularity featur…

cs.AR2025

Hardwired-Neurons Language Processing Units as General-Purpose Cognitive Substrates

Yang Liu, Yi Chen, Yongwei Zhao +24

The rapid advancement of Large Language Models (LLMs) has established language as a core general-purpose cognitive substrate, driving the demand for specialized Language Processing…

cs.LG2025

QiMeng-Attention: SOTA Attention Operator is generated by SOTA Attention Algorithm

Qirui Zhou, Shaohui Peng, Weiqiang Xiong +11

The attention operator remains a critical performance bottleneck in large language models (LLMs), particularly for long-context scenarios. While FlashAttention is the most widely u…

cs.AR2025

QiMeng: Fully Automated Hardware and Software Design for Processor Chip

Rui Zhang, Yuanbo Wen, Shuyao Cheng +17

Processor chip design technology serves as a key frontier driving breakthroughs in computer science and related fields. With the rapid advancement of information technology, conven…

cs.AR2025

AGON: Automated Design Framework for Customizing Processors from ISA Documents

Chongxiao Li, Di Huang, Pengwei Jin +12

Customized processors are attractive solutions for vast domain-specific applications due to their high energy efficiency. However, designing a processor in traditional flows is tim…

cs.CV2024★ 1 cited

DA-Ada: Learning Domain-Aware Adapter for Domain Adaptive Object Detection

Haochen Li, Rui Zhang, Hantao Yao +7

Domain adaptive object detection (DAOD) aims to generalize detectors trained on an annotated source domain to an unlabelled target domain. As the visual-language models (VLMs) can…

cs.AR2024

Cambricon-LLM: A Chiplet-Based Hybrid Architecture for On-Device Inference of 70B LLM

Zhongkai Yu, Shengwen Liang, Tianyun Ma +12

Deploying advanced large language models on edge devices, such as smartphones and robotics, is a growing trend that enhances user data privacy and network connectivity resilience w…

cs.AI2023

Emergent Communication for Rules Reasoning

Yuxuan Guo, Yifan Hao, Rui Zhang +14

Research on emergent communication between deep-learning-based agents has received extensive attention due to its inspiration for linguistics and artificial intelligence. However,…

cs.AI2023★ 2 cited

Pushing the Limits of Machine Design: Automated CPU Design with AI

Shuyao Cheng, Pengwei Jin, Qi Guo +16

Design activity -- constructing an artifact description satisfying given goals and constraints -- distinguishes humanity from other animals and traditional machines, and endowing m…

cs.CV2023★ 5 cited

Learning Domain-Aware Detection Head with Prompt Tuning

Haochen Li, Rui Zhang, Hantao Yao +5

Domain adaptive object detection (DAOD) aims to generalize detectors trained on an annotated source domain to an unlabelled target domain. However, existing methods focus on reduci…

cs.CV2022★ 2 cited

Real-Time Robust Video Object Detection System Against Physical-World Adversarial Attacks

Husheng Han, Xing Hu, Kaidi Xu +7

DNN-based video object detection (VOD) powers autonomous driving and video surveillance industries with rising importance and promising opportunities. However, adversarial patch at…