Papers by Qianlong Du
An Efficient and Precise Training Data Construction Framework for Process-supervised Reward Model in Mathematical Reasoning (2025.acl-long)
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| Challenge: | Existing methods for constructing process supervision training data are costly or suffer from poor quality. |
| Approach: | They propose a framework called EpicPRM which annotates each intermediate reasoning step based on its quantified contribution and uses an adaptive binary search algorithm to enhance annotation precision and efficiency. |
| Outcome: | The proposed framework improves annotation precision and efficiency and can be used to train a high-quality training dataset with 50k annotated intermediate steps. |
Adopting the Word-Pair-Dependency-Triplets with Individual Comparison for Natural Language Inference (C18-1)
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| Challenge: | Existing approaches to perform natural language inference ignore syntactic dependency among words or use tree-LSTM to generate sentence representation with irrelevant information. |
| Approach: | They propose to perform natural language inference with Word-Pair-Dependency-Triplets . they propose to compare the triplets of a given passage-pair to make judgement more interpretable . |
| Outcome: | The proposed approach is better than most of the approaches that use tree structures and comparable to other state-of-the-art approaches. |