588 citations · 691 across the 16 of their papers we have counts for
7 papers · 1 filter
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…