6 papers
CTC-TTS: LLM-based dual-streaming text-to-speech with CTC alignment
Hanwen Liu, Saierdaer Yusuyin, Hao Huang +1
Large-language-model (LLM)-based text-to-speech (TTS) systems can generate natural speech, but most are not designed for low-latency dual-streaming synthesis. High-quality dual-str…
Towards a Hybrid Quantum-Classical Computing Framework for Database Optimization Problems in Real Time Setup
Hanwen Liu, Ibrahim Sabek
Quantum computing has shown promise for solving complex optimization problems in databases, such as join ordering and index selection. Prior work often submits formulated problems…
Is Quantum Computing Ready for Real-Time Database Optimization?
Hanwen Liu, Ibrahim Sabek
Database systems encompass several performance-critical optimization tasks, such as join ordering and index tuning. As data volumes grow and workloads become more complex, these pr…
SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer
Hanwen Liu, Qihan Zhang, Ryan Marcus +1
Query optimization is a crucial problem in database systems that has been studied for decades. Learned query optimizers (LQOs) can improve performance over time by incorporating fe…
Conformal Prediction for Verifiable Learned Query Optimization
Hanwen Liu, Shashank Giridhara, Ibrahim Sabek
Query optimization is critical in relational databases. Recently, numerous Learned Query Optimizers (LQOs) have been proposed, demonstrating superior performance over traditional h…
Mix-of-Granularity: Optimize the Chunking Granularity for Retrieval-Augmented Generation
Zijie Zhong, Hanwen Liu, Xiaoya Cui +2
Integrating information from various reference databases is a major challenge for Retrieval-Augmented Generation (RAG) systems because each knowledge source adopts a unique data st…