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Zihao Sun

8 accepted papers

2026

An Intention-Guided Reinforcement Learning Approach With Dirichlet Energy Constraint for Heterogeneous Multi-Robot Cooperation

RA-L 2026

Multi-robot systems have demonstrated significant potential in accomplishing complex tasks, such as cooperative pursuit, search-and-rescue operations. The emergence of heterogeneous robots with diverse capabilities and characteristics shows superior adaptability compared with homogeneous teams. Howe

Cited by 0SourceScholar
2026

FGNet: Leveraging Feature-Guided Attention to Refine SAM2 for 3D EM Neuron Segmentation

AAAI 2026technical

Accurate segmentation of neural structures in Electron Microscopy (EM) images is paramount for neuroscience. However, this task is challenged by intricate morphologies, low signal-to-noise ratios, and scarce annotations, limiting the accuracy and generalization of existing methods. To address these

Cited by 0SourcePDFScholar
2025

Complex Robotic Manipulation via Hindsight Goal Diffusion and Graph-based Experience Replay

IROS 2025

Goal-conditioned reinforcement learning (GCRL) is an effective method for multi-goal robotic manipulation tasks. Many studies based on hindsight experience replay (HER) and hindsight goal generation (HGG) have achieved the autonomous acquisition of robotic manipulation in reward-sparse environments

Cited by 0SourceScholar
2024

Data Contamination Can Cross Language Barriers

EMNLP 2024main

The opacity in developing large language models (LLMs) is raising growing concerns about the potential contamination of public benchmarks in the pre-training data. Existing contamination detection methods are typically based on the text overlap between training and evaluation data, which can be too…

2023

PA&DA: Jointly Sampling Path and Data for Consistent NAS

CVPR 2023poster

Based on the weight-sharing mechanism, one-shot NAS methods train a supernet and then inherit the pre-trained weights to evaluate sub-models, largely reducing the search cost. However, several works have pointed out that the shared weights suffer from different gradient descent directions during tra…

2023

Unleashing the Power of Gradient Signal-to-Noise Ratio for Zero-Shot NAS

ICCV 2023poster

Neural Architecture Search (NAS) aims to automatically find optimal neural network architectures in an efficient way. Zero-Shot NAS is a promising technique that leverages proxies to predict the accuracy of candidate architectures without any training. However, we have observed that most existing pr…

Cited by 6PDFcodeScholar
2022

AGNAS: Attention-Guided Micro and Macro-Architecture Search

ICML 2022spotlight

Micro- and macro-architecture search have emerged as two popular NAS paradigms recently. Existing methods leverage different search strategies for searching micro- and macro- architectures. When using architecture parameters to search for micro-structure such as normal cell and reduction cell, the a…

2022

Searching for BurgerFormer with Micro-Meso-Macro Space Design

ICML 2022spotlight

With the success of Transformers in the computer vision field, the automated design of vision Transformers has attracted significant attention. Recently, MetaFormer found that simple average pooling can achieve impressive performance, which naturally raises the question of how to design a search spa…