8 citations · 11 across the 9 of their papers we have counts for
9 papers
FlexSpec: Frozen Drafts Meet Evolving Targets in Edge-Cloud Collaborative LLM Speculative Decoding
Yuchen Li, Rui Kong, Zhonghao Lyu +11
Deploying large language models (LLMs) in mobile and edge computing environments is constrained by limited on-device resources, scarce wireless bandwidth, and frequent model evolut…
Towards AI Search Paradigm
Yuchen Li, Hengyi Cai, Rui Kong +20
In this paper, we introduce the AI Search Paradigm, a comprehensive blueprint for next-generation search systems capable of emulating human information processing and decision-maki…
Pre-trained Molecular Language Models with Random Functional Group Masking
Tianhao Peng, Yuchen Li, Xuhong Li +7
Recent advancements in computational chemistry have leveraged the power of trans-former-based language models, such as MoLFormer, pre-trained using a vast amount of simplified mole…
Generative Pre-trained Ranking Model with Over-parameterization at Web-Scale (Extended Abstract)
Yuchen Li, Haoyi Xiong, Linghe Kong +4
Learning to rank (LTR) is widely employed in web searches to prioritize pertinent webpages from retrieved content based on input queries. However, traditional LTR models encounter…
Pre-trained Graphformer-based Ranking at Web-scale Search (Extended Abstract)
Yuchen Li, Haoyi Xiong, Linghe Kong +4
Both Transformer and Graph Neural Networks (GNNs) have been employed in the domain of learning to rank (LTR). However, these approaches adhere to two distinct yet complementary pro…
Towards Automated Data Sciences with Natural Language and SageCopilot: Practices and Lessons Learned
Yuan Liao, Jiang Bian, Yuhui Yun +9
While the field of NL2SQL has made significant advancements in translating natural language instructions into executable SQL scripts for data querying and processing, achieving ful…
When Search Engine Services meet Large Language Models: Visions and Challenges
Haoyi Xiong, Jiang Bian, Yuchen Li +5
Combining Large Language Models (LLMs) with search engine services marks a significant shift in the field of services computing, opening up new possibilities to enhance how we sear…
Rethinking Resource Management in Edge Learning: A Joint Pre-training and Fine-tuning Design Paradigm
Zhonghao Lyu, Yuchen Li, Guangxu Zhu +3
In some applications, edge learning is experiencing a shift in focusing from conventional learning from scratch to new two-stage learning unifying pre-training and task-specific fi…
Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective
Haoyi Xiong, Xuhong Li, Xiaofei Zhang +5
Given the complexity and lack of transparency in deep neural networks (DNNs), extensive efforts have been made to make these systems more interpretable or explain their behaviors i…