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Ming Du

5 accepted papers

2025

Boosting Text-to-SQL through Multi-grained Error Identification

COLING 2025main

Text-to-SQL is a technology that converts natural language questions into executable SQL queries, allowing users to query and manage relational databases more easily. In recent years, large language models have significantly advanced the development of text-to-SQL. However, existing methods often ov…

2025

Enhancing Multimodal Named Entity Recognition through Adaptive Mixup Image Augmentation

COLING 2025main

Multimodal named entity recognition (MNER) extends traditional named entity recognition (NER) by integrating visual and textual information. However, current methods still face significant challenges due to the text-image mismatch problem. Recent advancements in text-to-image synthesis provide promi…

Cited by 0SourcePDFScholar
2025

Gesture Identification and Object Temperature Detection of a Robotic Hand Using a Wireless Flexible Sensing Feedback Control System

RA-L 2025

The ability of robotic hands to sense their environment and provide feedback is becoming increasingly vital for advanced robotic systems. Real-time tactile interaction is crucial for ensuring safe and effective human-machine collaboration. However, conventional sensors face significant challenges in

Cited by 0SourceScholar
2024

Adaptive Reinforcement Tuning Language Models as Hard Data Generators for Sentence Representation

COLING 2024main

Sentence representation learning is a fundamental task in NLP. Existing methods use contrastive learning (CL) to learn effective sentence representations, which benefit from high-quality contrastive data but require extensive human annotation. Large language models (LLMs) like ChatGPT and GPT4 can a…

2022

Different Data, Different Modalities! Reinforced Data Splitting for Effective Multimodal Information Extraction from Social Media Posts

COLING 2022main

Recently, multimodal information extraction from social media posts has gained increasing attention in the natural language processing community. Despite their success, current approaches overestimate the significance of images. In this paper, we argue that different social media posts should consid…