4 papers
On the Practice of Scaling Search Conversion Rate Prediction
James Pak, Jyun-Yu Jiang, Fan Zhang +13
Scaling a Search Conversion Rate (CVR) prediction model, especially in high-traffic environments, presents a challenge: superior model quality needs to be balanced with strict cons…
Beyond Independent Passages: Adaptive Passage Combination Retrieval for Retrieval Augmented Open-Domain Question Answering
Ting-Wen Ko, Jyun-Yu Jiang, Pu-Jen Cheng
Retrieval-augmented generation (RAG) enhances large language models (LLMs) by incorporating external documents at inference time, enabling up-to-date knowledge access without costl…
Retrieval-augmented Encoders for Extreme Multi-label Text Classification
Yau-Shian Wang, Wei-Cheng Chang, Jyun-Yu Jiang +3
Extreme multi-label classification (XMC) seeks to find relevant labels from an extremely large label collection for a given text input. To tackle such a vast label space, current s…
MinPrompt: Graph-based Minimal Prompt Data Augmentation for Few-shot Question Answering
Xiusi Chen, Jyun-Yu Jiang, Wei-Cheng Chang +3
Recent advances in few-shot question answering (QA) mostly rely on the power of pre-trained large language models (LLMs) and fine-tuning in specific settings. Although the pre-trai…