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Yongqiang Zhao

17 accepted papers

2026

ViTac-Tracing: Visual-Tactile Imitation Learning of Deformable Object Tracing

Yongqiang Zhao, Haining Luo, Yupeng Wang, Emmanouil Spyrakos-Papastavridis, Yiannis Demiris, Shan Luo
ICRA 2026poster

Deformable objects often appear in unstructured configurations. Tracing deformable objects helps bringing them into extended states and facilitating the downstream manipulation tasks. Due to the requirements for object-specific modeling or sim-to-real transfer, existing tracing methods either lack g…

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2026

ViTacGen: Robotic Pushing with Vision-To-Touch Generation

Zhiyuan Wu, Yijiong Lin, Yongqiang Zhao, Xuyang Zhang, Zhuo Chen, Nathan Lepora +1
ICRA 2026poster

Robotic pushing is a fundamental manipulation task that requires tactile feedback to capture subtle contact forces and dynamics between the end-effector and the object. However, real tactile sensors often face hardware limitations and deployment challenges, while vision-only policies struggle with s…

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2026

Visual-Tactile Peg-in-Hole Assembly Learning From Peg-Out-of-Hole Disassembly

Yongqiang Zhao, Xuyang Zhang, Zhuo Chen, Matteo Leonetti, Emmanouil Spyrakos-Papastavridis, Shan Luo
RA-L 2026

Peg-in-hole (PiH) assembly is a fundamental yet challenging robotic manipulation task. While reinforcement learning (RL) has shown promise in tackling such tasks, it requires extensive exploration. In this paper, we propose a novel visual-tactile skill learning framework for the PiH task that levera

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2025

M2PA: A Multi-Memory Planning Agent for Open Worlds Inspired by Cognitive Theory

Yanfang Zhou, Xiaodong Li, Yuntao Liu, Yongqiang Zhao, Xintong Wang, Zhenyu Li +2
ACL 2025finding

Open-world planning poses a significant challenge for general artificial intelligence due to environmental complexity and task diversity, especially in long-term tasks and lifelong learning. Inspired by cognitive theories, we propose M2PA, an open-world multi-memory planning agent. M2PA innovates by…

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2025

MVCBRec: Multi-View Contrastive Learning for Bundle Recommendation

Mengmeng Li, Jinlong Tian, Yongqiang Zhao, Hongmei Li, Xudong Fang
ICASSP 2025accepted

Since bundled recommendation can meet various demands of users in one stop, it has always been a research hotspot in the recommendation field. Recent methods usually construct bundle view and item view based on user-bundle interaction and user-item interaction information, and learn representations…

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2025

Metagent-P: A Neuro-Symbolic Planning Agent with Metacognition for Open Worlds

Yanfang Zhou, Yuntao Liu, Xiaodong Li, Yongqiang Zhao, Xintong Wang, Jinlong Tian +2
ACL 2025finding

The challenge of developing agents capable of open-world planning remains fundamental to artificial general intelligence (AGI). While large language models (LLMs) have made progress with their vast world knowledge, their limitations in perception, memory, and reliable reasoning still hinder LLM-base…

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2025

Try Before You Buy: Solving Multi-Model Complex Tasks by Model Competitions

Yongqiang Zhao, Zhenyu Li, Zhi Jin, Feng Zhang, Lianwei Wu, Xinhai Xu +1
ICASSP 2025accepted

Multi-modal large language models (MLLMs) are expanded from large language models (LLMs) with additional capabilities to infer multi-modal data. Current MLLM workflows, when dealing with complex tasks, typically begin by using an LLM to decompose the task into multiple subtasks, then heuristically s…

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2025

ViTacGen: Robotic Pushing With Vision-to-Touch Generation

Zhiyuan Wu, Yijiong Lin, Yongqiang Zhao, Xuyang Zhang, Zhuo Chen, Nathan F. Lepora +1
RA-L 2025

Robotic pushing is a fundamental manipulation task that requires tactile feedback to capture subtle contact forces and dynamics between the end-effector and the object. However, real tactile sensors often face hardware limitations such as high costs and fragility, and deployment challenges involving

Cited by 2Source ↗code ↗Scholar ↗
2024

FOTS: A Fast Optical Tactile Simulator for Sim2Real Learning of Tactile-Motor Robot Manipulation Skills

Yongqiang Zhao, Kun Qian, Boyi Duan, Shan Luo
RA-L 2024

Simulation is a widely used tool in robotics to reduce hardware consumption and gather large-scale data. Despite previous efforts to simulate optical tactile sensors, there remain challenges in efficiently synthesizing images and replicating marker motion under different contact loads. In this work,

Cited by 21Source ↗code ↗Scholar ↗
2024

Integrating Physician Diagnostic Logic into Large Language Models: Preference Learning from Process Feedback

Chengfeng Dou, Ying Zhang, Zhi Jin, Wenpin Jiao, Haiyan Zhao, Yongqiang Zhao +1
ACL 2024findings

The utilization of large language models for medical dialogue generation has attracted considerable attention due to its potential to enhance response richness and coherence. While previous studies have made strides in optimizing model performance, there is a pressing need to bolster the model’s cap…

Cited by 5Source ↗PDF ↗code ↗Scholar ↗
2024

Unified Evidence Enhancement Inference Framework for Fake News Detection

Lianwei Wu, Linyong Wang, Yongqiang Zhao
IJCAI 2024poster

The current approaches for fake news detection are mainly devoted to extracting candidate evidence from comments (or external articles) and establishing interactive reasoning with the news itself to verify the falsehood of the news. However, they still have several drawbacks: 1) The interaction obje…

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2023

CORE: Cooperative Reconstruction for Multi-Agent Perception

Binglu Wang, Lei Zhang, Zhaozhong Wang, Yongqiang Zhao, Tianfei Zhou
ICCV 2023poster

This paper presents CORE, a conceptually simple, effective and communication-efficient model for multi-agent cooperative perception. It addresses the task from a novel perspective of cooperative reconstruction, based on two key insights: 1) cooperating agents together provide a more holistic observa…

Cited by 48PDF ↗code ↗Scholar ↗
2023

PlugMed: Improving Specificity in Patient-Centered Medical Dialogue Generation using In-Context Learning

Chengfeng Dou, Zhi Jin, Wenpin Jiao, Haiyan Zhao, Yongqiang Zhao, Zhengwei Tao
EMNLP 2023long findings

The patient-centered medical dialogue systems strive to offer diagnostic interpretation services to users who are less knowledgeable about medical knowledge, through emphasizing the importance of providing responses specific to the patients. It is difficult for the large language models (LLMs) to gu…

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2023

SEAG: Structure-Aware Event Causality Generation

Zhengwei Tao, Zhi Jin, Xiaoying Bai, Haiyan Zhao, Chengfeng Dou, Yongqiang Zhao +2
ACL 2023findings

Extracting event causality underlies a broad spectrum of natural language processing applications. Cutting-edge methods break this task into Event Detection and Event Causality Identification. Although the pipelined solutions succeed in achieving acceptable results, the inherent nature of separating…

Cited by 7Source ↗PDF ↗Scholar ↗
2023

UniEvent: Unified Generative Model with Multi-Dimensional Prefix for Zero-Shot Event-Relational Reasoning

Zhengwei Tao, Zhi Jin, Haiyan Zhao, Chengfeng Dou, Yongqiang Zhao, Tao Shen +1
ACL 2023long

Reasoning about events and their relations attracts surging research efforts since it is regarded as an indispensable ability to fulfill various event-centric or common-sense reasoning tasks. However, these tasks often suffer from limited data availability due to the labor-intensive nature of their…

Cited by 3Source ↗PDF ↗code ↗Scholar ↗
2020

Full-Time Monocular Road Detection Using Zero-Distribution Prior of Angle of Polarization

Ning Li, Yongqiang Zhao, Quan Pan, Seong G. Kong, Jonathan Cheung-Wai Chan
ECCV 2020poster

This paper presents a road detection technique based on long-wave infrared (LWIR) polarization imaging for autonomous navigation regardless of illumination conditions, day and night. Division of Focal Plane (DoFP) imaging technology enables acquisition of infrared polarization images in real time us…

Cited by 40Source ↗PDF ↗code ↗Scholar ↗