588 citations · 691 across the 16 of their papers we have counts for
16 papers
Align before Search: Aligning Ads Image to Text for Accurate Cross-Modal Sponsored Search
Yuanmin Tang, Jing Yu, Keke Gai +4
Cross-Modal sponsored search displays multi-modal advertisements (ads) when consumers look for desired products by natural language queries in search engines. Since multi-modal ads…
Model-enhanced Vector Index
Hailin Zhang, Yujing Wang, Qi Chen +16
Embedding-based retrieval methods construct vector indices to search for document representations that are most similar to the query representations. They are widely used in docume…
Constraint-aware and Ranking-distilled Token Pruning for Efficient Transformer Inference
Junyan Li, Li Lyna Zhang, Jiahang Xu +9
Deploying pre-trained transformer models like BERT on downstream tasks in resource-constrained scenarios is challenging due to their high inference cost, which grows rapidly with i…
To Copy Rather Than Memorize: A Vertical Learning Paradigm for Knowledge Graph Completion
Rui Li, Xu Chen, Chaozhuo Li +8
Embedding models have shown great power in knowledge graph completion (KGC) task. By learning structural constraints for each training triple, these methods implicitly memorize int…
SpaceEvo: Hardware-Friendly Search Space Design for Efficient INT8 Inference
Li Lyna Zhang, Xudong Wang, Jiahang Xu +6
The combination of Neural Architecture Search (NAS) and quantization has proven successful in automatically designing low-FLOPs INT8 quantized neural networks (QNN). However, direc…
IRGen: Generative Modeling for Image Retrieval
Yidan Zhang, Ting Zhang, Dong Chen +11
While generative modeling has become prevalent across numerous research fields, its integration into the realm of image retrieval remains largely unexplored and underjustified. In…
UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation
Daixuan Cheng, Shaohan Huang, Junyu Bi +7
Large Language Models (LLMs) are popular for their impressive abilities, but the need for model-specific fine-tuning or task-specific prompt engineering can hinder their generaliza…
Label-Efficient Interactive Time-Series Anomaly Detection
Hong Guo, Yujing Wang, Jieyu Zhang +5
Time-series anomaly detection is an important task and has been widely applied in the industry. Since manual data annotation is expensive and inefficient, most applications adopt u…
SwiftPruner: Reinforced Evolutionary Pruning for Efficient Ad Relevance
Li Lyna Zhang, Youkow Homma, Yujing Wang +5
Ad relevance modeling plays a critical role in online advertising systems including Microsoft Bing. To leverage powerful transformers like BERT in this low-latency setting, many ex…
AutoADR: Automatic Model Design for Ad Relevance
Yiren Chen, Yaming Yang, Hong Sun +7
Large-scale pre-trained models have attracted extensive attention in the research community and shown promising results on various tasks of natural language processing. However, th…
Multivariate Time-series Anomaly Detection via Graph Attention Network
Hang Zhao, Yujing Wang, Juanyong Duan +7
Anomaly detection on multivariate time-series is of great importance in both data mining research and industrial applications. Recent approaches have achieved significant progress…
Automated Model Selection for Time-Series Anomaly Detection
Yuanxiang Ying, Juanyong Duan, Chunlei Wang +3
Time-series anomaly detection is a popular topic in both academia and industrial fields. Many companies need to monitor thousands of temporal signals for their applications and ser…
Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based Visual Question Answering
Zihao Zhu, Jing Yu, Yujing Wang +3
Fact-based Visual Question Answering (FVQA) requires external knowledge beyond visible content to answer questions about an image, which is challenging but indispensable to achieve…
LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression
Yihuan Mao, Yujing Wang, Chufan Wu +6
BERT is a cutting-edge language representation model pre-trained by a large corpus, which achieves superior performances on various natural language understanding tasks. However, a…
TextNAS: A Neural Architecture Search Space tailored for Text Representation
Yujing Wang, Yaming Yang, Yiren Chen +7
Learning text representation is crucial for text classification and other language related tasks. There are a diverse set of text representation networks in the literature, and how…
Time-Series Anomaly Detection Service at Microsoft
Hansheng Ren, Bixiong Xu, Yujing Wang +7
Large companies need to monitor various metrics (for example, Page Views and Revenue) of their applications and services in real time. At Microsoft, we develop a time-series anomal…