3 citations · 3 across the 4 of their papers we have counts for
4 papers
When Names Cross Scripts: A Source-Grounded Benchmark for Historical Entity Reconciliation in the Mongol World
Xiang Chen, Zeyu Zhang
Historical people may appear under different languages, scripts, and transcription traditions, while distinct individuals may share highly similar or even identical names. This mak…
PC-MoE: Memory-Efficient and Privacy-Preserving Collaborative Training for Mixture-of-Experts LLMs
Ze Yu Zhang, Bolin Ding, Bryan Kian Hsiang Low
Mixture-of-Experts (MoE) has been gaining popularity due to its successful adaptation to large language models (LLMs). In this work, we introduce Privacy-preserving Collaborative M…
Prompting the Unknown: Understanding Response Uncertainty in Large Language Models
Ze Yu Zhang, Arun Verma, Finale Doshi-Velez +1
Large language models (LLMs) are widely used in decision-making across diverse domains. Ensuring the generation of safe and reliable responses is critical for the effective deploym…
Fine-tuning Language Models with Generative Adversarial Reward Modelling
Zhang Ze Yu, Lau Jia Jaw, Zhang Hui +1
Reinforcement Learning with Human Feedback (RLHF) has been demonstrated to significantly enhance the performance of large language models (LLMs) by aligning their outputs with desi…