4 papers
Data Value in the Age of Scaling: Understanding LLM Scaling Dynamics Under Real-Synthetic Data Mixtures
Haohui Wang, Jingyuan Qi, Jianpeng Chen +9
The rapid progress of large language models (LLMs) is fueled by the growing reliance on datasets that blend real and synthetic data. While synthetic data offers scalability and cos…
The Streaming Batch Model for Efficient and Fault-Tolerant Heterogeneous Execution
Frank Sifei Luan, Ron Yifeng Wang, Yile Gu +12
While ML model training and inference are both GPU-intensive, CPU-based data processing is often the bottleneck. Distributed data processing systems based on the batch or stream pr…
EntGPT: Entity Linking with Generative Large Language Models
Yifan Ding, Amrit Poudel, Qingkai Zeng +3
Entity Linking in natural language processing seeks to match text entities to their corresponding entries in a dictionary or knowledge base. Traditional approaches rely on contextu…
Citations and Trust in LLM Generated Responses
Yifan Ding, Matthew Facciani, Amrit Poudel +5
Question answering systems are rapidly advancing, but their opaque nature may impact user trust. We explored trust through an anti-monitoring framework, where trust is predicted to…