Showing cs.CLShow all
3 papers · 1 filter
cs.CL2025
Decentralized Arena: Towards Democratic and Scalable Automatic Evaluation of Language Models
Yanbin Yin, Kun Zhou, Zhen Wang +11
The recent explosion of large language models (LLMs), each with its own general or specialized strengths, makes scalable, reliable benchmarking more urgent than ever. Standard prac…
cs.CL2025
Synthesizing Privacy-Preserving Text Data via Finetuning without Finetuning Billion-Scale LLMs
Bowen Tan, Zheng Xu, Eric Xing +2
Synthetic data offers a promising path to train models while preserving data privacy. Differentially private (DP) finetuning of large language models (LLMs) as data generator is ef…
cs.CL2024
Dynamic Rewarding with Prompt Optimization Enables Tuning-free Self-Alignment of Language Models
Somanshu Singla, Zhen Wang, Tianyang Liu +3
Aligning Large Language Models (LLMs) traditionally relies on costly training and human preference annotations. Self-alignment seeks to reduce these expenses by enabling models to…