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Found 6 papers, 3 papers with code
Improving LLM-based Machine Translation with Systematic Self-Correction
Large Language Models (LLMs) have achieved impressive results in Machine Translation (MT).
DMBGN: Deep Multi-Behavior Graph Networks for Voucher Redemption Rate Prediction
In this paper, we propose a Deep Multi-behavior Graph Networks (DMBGN) to shed light on this field for the voucher redemption rate prediction.
Deep Interest with Hierarchical Attention Network for Click-Through Rate Prediction
Deep Interest Network (DIN) is a state-of-the-art model which uses attention mechanism to capture user interests from historical behaviors.
A Multi-task Learning Approach for Improving Product Title Compression with User Search Log Data
It is a challenging and practical research problem to obtain effective compression of lengthy product titles for E-commerce.
Dependency Parsing with Partial Annotations: An Empirical Comparison
This paper describes and compares two straightforward approaches for dependency parsing with partial annotations (PA).
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