Papers by Hongji Zhang
Confidence Based Bidirectional Global Context Aware Training Framework for Neural Machine Translation (2022.acl-long)
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| Challenge: | Existing studies focus on how to effectively exploit bidirectional global contexts in neural machine translation models. |
| Approach: | They propose a Confidence Based Bidirectional Global Context Aware training framework for NMT . they incorporate bidirectional global context to the NMT model on unconfidently-predicted target words . |
| Outcome: | The proposed framework improves the NMT model on three large-scale translation datasets by +1.02, +0.57 BLEU scores. |
DeepRTL2: A Versatile Model for RTL-Related Tasks (2025.findings-acl)
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| Challenge: | Integration of large language models into electronic design automation has been a key driver in eDA. |
| Approach: | They propose a family of large language models that unifies generation- and embedding-based tasks related to RTL. |
| Outcome: | The proposed model achieves state-of-the-art performance across all evaluated tasks. |
A Contrastive Framework for Learning Sentence Representations from Pairwise and Triple-wise Perspective in Angular Space (2022.acl-long)
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| Challenge: | Existing methods for learning sentence representations focus on constitution of positive and negative representation pairs and do not focus on training objective. |
| Approach: | They propose a new method to learn sentence representations using BERT-like pre-trained models . they use a pairwise discriminating power and a model to model the entailment relation of triplet sentences . |
| Outcome: | The proposed method outperforms the previous state-of-the-art on diverse sentence related tasks. |