6 citations · 6 across the 4 of their papers we have counts for
4 papers
Separate the Wheat from the Chaff: Winnowing Down Divergent Views in Retrieval Augmented Generation
Song Wang, Zihan Chen, Peng Wang +5
Retrieval-augmented generation (RAG) enhances large language models (LLMs) by integrating external knowledge sources to address their limitations in accessing up-to-date or special…
BILLY: Steering Large Language Models via Merging Persona Vectors for Creative Generation
Tsung-Min Pai, Jui-I Wang, Li-Chun Lu +3
Multi-LLM systems enhance the creativity of large language models by simulating human collective intelligence but suffer from significant drawbacks, such as high computational cost…
Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks
Chien-yu Huang, Wei-Chih Chen, Shu-wen Yang +77
Multimodal foundation models, such as Gemini and ChatGPT, have revolutionized human-machine interactions by seamlessly integrating various forms of data. Developing a universal spo…
LLM Discussion: Enhancing the Creativity of Large Language Models via Discussion Framework and Role-Play
Li-Chun Lu, Shou-Jen Chen, Tsung-Min Pai +3
Large language models (LLMs) have shown exceptional proficiency in natural language processing but often fall short of generating creative and original responses to open-ended ques…