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Yinqi Zhang

6 accepted papers

2025

A Soft Active Surface Gripper for Safe In Hand Manipulation of Fragile Objects

IROS 2025

This paper introduces a soft active surface gripper designed to manipulate fragile objects safely. This gripper consists of two fingers, each equipped with two compliant pneumatic actuators and a soft active surface. The gripper utilizes the elastic belt as its soft active surface, which is driven b

Cited by 0SourceScholar
2025

Complete Chess Games Enable LLM Become A Chess Master

NAACL 2025short

Large language models (LLM) have shown remarkable abilities in text generation, question answering, language translation, reasoning and many other tasks. It continues to advance rapidly and is becoming increasingly influential in various fields, from technology and business to education and entertai…

2025

Learning Class Unique Features in Fine-Grained Visual Classification

ICASSP 2025accepted

A major challenge in Fine-Grained Visual Classification (FGVC) is distinguishing various categories with high inter-class similarity by learning the feature that differentiates the details. Conventional cross-entropy trained Convolutional Neural Network (CNN) fails this challenge as they may suffer…

Cited by 0SourceScholar
2024

Exploring Mathematical Extrapolation of Large Language Models with Synthetic Data

ACL 2024findings

While large language models (LLMs) have shown excellent capabilities in language understanding, text generation and many other tasks, they still struggle in complex multi-step reasoning problems such as mathematical reasoning. In this paper, through a newly proposed arithmetical puzzle problem, we s…

Cited by 2SourcePDFScholar
2022

Self-supervised Models are Good Teaching Assistants for Vision Transformers

ICML 2022spotlight

Transformers have shown remarkable progress on computer vision tasks in the past year. Compared to their CNN counterparts, transformers usually need the help of distillation to achieve comparable results on middle or small sized datasets. Meanwhile, recent researches discover that when transformers…

2020

Sequential Convolution and Runge-Kutta Residual Architecture for Image Compressed Sensing

ECCV 2020poster

In recent years, Deep Neural Networks (DNN) have empowered Compressed Sensing (CS) substantially and have achieved high reconstruction quality and speed far exceeding traditional CS methods. However, there are still lots of issues to be further explored before it can be practical enough. There are m…