20 citations · 57 across the 11 of their papers we have counts for
3 papers · 1 filter
FedReFT: Federated Representation Fine-Tuning with All-But-Me Aggregation
Fatema Siddika, Md Anwar Hossen, J. Pablo Muñoz +3
Parameter-efficient fine-tuning (PEFT) adapts large pre-trained models by updating only a small subset of parameters. Recently, Representation Fine-Tuning (ReFT) has emerged as an…
An Empirical Study on Prompt Compression for Large Language Models
Zheng Zhang, Jinyi Li, Yihuai Lan +2
Prompt engineering enables Large Language Models (LLMs) to perform a variety of tasks. However, lengthy prompts significantly increase computational complexity and economic costs.…
DVM: Towards Controllable LLM Agents in Social Deduction Games
Zheng Zhang, Yihuai Lan, Yangsen Chen +3
Large Language Models (LLMs) have advanced the capability of game agents in social deduction games (SDGs). These games rely heavily on conversation-driven interactions and require…