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Jie Yao

5 accepted papers

2026

Design, Control, and Evaluation of a Modular Variable Configuration Rehabilitation Robot for Early Physical Therapy

RA-L 2026

This paper proposes a modular variable configuration rehabilitation robot (MVCRR), aiming to meet the needs of multi-functional, full-cycle rehabilitation. MVCRR integrates a lower-limb training module and a-sit-to-stand module, offering 16 actuated degrees of freedom and supporting four rehabilitat

Cited by 0SourceScholar
2025

P²Net: Parallel Pointer-based Network for Key Information Extraction with Complex Layouts

ACL 2025finding

Key Information Extraction (KIE) is a challenging multimodal task aimed at extracting structured value entities from visually rich documents. Despite recent advancements, two major challenges remain. First, existing datasets typically feature fixed layouts and a limited set of entity categories, whi…

Cited by 0SourcePDFScholar
2024

MathAttack: Attacking Large Language Models towards Math Solving Ability

AAAI 2024technical

With the boom of Large Language Models (LLMs), the research of solving Math Word Problem (MWP) has recently made great progress. However, there are few studies to examine the robustness of LLMs in math solving ability. Instead of attacking prompts in the use of LLMs, we propose a MathAttack model to…

2023

Leader-Follower Formation Control of a Large-Scale Swarm of Satellite System Using the State-Dependent Riccati Equation: Orbit-to-Orbit and In-Same-Orbit Regulation

IROS 2023poster

The state-dependent Riccati equation (SDRE) is a nonlinear optimal controller with a flexible structure which is one of the main advantages of this method. Here in this work, this flexibility is used to present a novel design for handling a soft constraint for state variables (trajectories). The con…

Cited by 3SourceScholar
2023

Learning by Analogy: Diverse Questions Generation in Math Word Problem

ACL 2023findings

Solving math word problem (MWP) with AI techniques has recently made great progress with the success of deep neural networks (DNN), but it is far from being solved. We argue that the ability of learning by analogy is essential for an MWP solver to better understand same problems which may typically…