584 citations · 3.1k across the 56 of their papers we have counts for
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ERNIE-Search: Bridging Cross-Encoder with Dual-Encoder via Self On-the-fly Distillation for Dense Passage Retrieval
Yuxiang Lu, Yiding Liu, Jiaxiang Liu +8
Neural retrievers based on pre-trained language models (PLMs), such as dual-encoders, have achieved promising performance on the task of open-domain question answering (QA). Their…
On Length Divergence Bias in Textual Matching Models
Lan Jiang, Tianshu Lyu, Yankai Lin +3
Despite the remarkable success deep models have achieved in Textual Matching (TM) tasks, it still remains unclear whether they truly understand language or measure the semantic sim…
First Target and Opinion then Polarity: Enhancing Target-opinion Correlation for Aspect Sentiment Triplet Extraction
Lianzhe Huang, Peiyi Wang, Sujian Li +5
Aspect Sentiment Triplet Extraction (ASTE) aims to extract triplets from a sentence, including target entities, associated sentiment polarities, and opinion spans which rationalize…
Data Manipulation: Towards Effective Instance Learning for Neural Dialogue Generation via Learning to Augment and Reweight
Hengyi Cai, Hongshen Chen, Yonghao Song +3
Current state-of-the-art neural dialogue models learn from human conversations following the data-driven paradigm. As such, a reliable training corpus is the crux of building a rob…
Learning from Easy to Complex: Adaptive Multi-curricula Learning for Neural Dialogue Generation
Hengyi Cai, Hongshen Chen, Cheng Zhang +5
Current state-of-the-art neural dialogue systems are mainly data-driven and are trained on human-generated responses. However, due to the subjectivity and open-ended nature of huma…
Posterior-GAN: Towards Informative and Coherent Response Generation with Posterior Generative Adversarial Network
Shaoxiong Feng, Hongshen Chen, Kan Li +1
Neural conversational models learn to generate responses by taking into account the dialog history. These models are typically optimized over the query-response pairs with a maximu…