A Modular Dual-Arm Robotic Cell for Disassembly and Repair of Industrial Control Electronics
该研究针对工业控制电子设备的自动化拆解与维修问题，提出了一种模块化双臂机器人系统，结合多种传感器、工具及ROS 2控制系统实现自动化的拆解和维修。
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Selected work
Representative Papers
CAD-Based Relation Learning and Geometric-Symbolic Planning for Robotic Assembly
该论文提出一种结合基于学习的关系提取与几何-符号推理的混合ASP框架，以从不完美的CAD数据中生成可行的机器人拆卸序列。
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CARLAverse: A Highly Modular, Distributed, and Multimodal Framework for Human-in-the-Loop Simulation
为解决自动驾驶在混合交通场景中与行人等交互测试问题，提出CARLAverse框架，采用分布式物理架构减少网络延迟，提高仿真真实感。
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A Calibration Audit of Confidence in Feed-Forward 3D Reconstruction
研究针对3D重建模型的置信度校准问题，通过审计七个模型在十三个数据集上的表现，并提出一种幂律方法来修正预测不确定性，改善了置信度准确性。
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ANNOTARES: A Dataset for Extracting Logical Structures from German Statutory Texts
This study addresses the challenging task of automatically identifying and segmenting legal conditions (Tatbestand) from legal consequences (Rechtsfolge) in German statutory texts. To facilitate research on this structural parsing problem, the authors introduce ANNOTARES, the first fine-grained annotated dataset covering three major German legal codes, enabling cross-code generalization studies. The work systematically evaluates a range of approaches, including rule-based baselines, CRF, BiLSTM, BiLSTM-CRF, and Transformer architectures based on BERT and large language models. Experimental results demonstrate that BERT-based and large language models significantly outperform traditional methods in capturing the complex syntactic structures inherent in legal texts, thereby confirming the effectiveness of pretrained language models for extracting logical structures in legal documents.
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A Modular Dual-Arm Robotic Cell for Disassembly and Repair of Industrial Control Electronics
该研究针对工业控制电子设备的自动化拆解与维修问题，提出了一种模块化双臂机器人系统，结合多种传感器、工具及ROS 2控制系统实现自动化的拆解和维修。
0 citationsRead paper
CAD-Based Relation Learning and Geometric-Symbolic Planning for Robotic Assembly
该论文提出一种结合基于学习的关系提取与几何-符号推理的混合ASP框架，以从不完美的CAD数据中生成可行的机器人拆卸序列。
0 citationsRead paper
CARLAverse: A Highly Modular, Distributed, and Multimodal Framework for Human-in-the-Loop Simulation
为解决自动驾驶在混合交通场景中与行人等交互测试问题，提出CARLAverse框架，采用分布式物理架构减少网络延迟，提高仿真真实感。
0 citationsRead paper
A Calibration Audit of Confidence in Feed-Forward 3D Reconstruction
研究针对3D重建模型的置信度校准问题，通过审计七个模型在十三个数据集上的表现，并提出一种幂律方法来修正预测不确定性，改善了置信度准确性。
0 citationsRead paper
ANNOTARES: A Dataset for Extracting Logical Structures from German Statutory Texts
This study addresses the challenging task of automatically identifying and segmenting legal conditions (Tatbestand) from legal consequences (Rechtsfolge) in German statutory texts. To facilitate research on this structural parsing problem, the authors introduce ANNOTARES, the first fine-grained annotated dataset covering three major German legal codes, enabling cross-code generalization studies. The work systematically evaluates a range of approaches, including rule-based baselines, CRF, BiLSTM, BiLSTM-CRF, and Transformer architectures based on BERT and large language models. Experimental results demonstrate that BERT-based and large language models significantly outperform traditional methods in capturing the complex syntactic structures inherent in legal texts, thereby confirming the effectiveness of pretrained language models for extracting logical structures in legal documents.
0 citationsRead paper