3 papers
cs.LG2025
LLMBoost: Make Large Language Models Stronger with Boosting
Zehao Chen, Tianxiang Ai, Yifei Li +11
Ensemble learning of LLMs has emerged as a promising alternative to enhance performance, but existing approaches typically treat models as black boxes, combining the inputs or fina…
cs.CL2025
Scoring, Reasoning, and Selecting the Best! Ensembling Large Language Models via a Peer-Review Process
Zhijun Chen, Zeyu Ji, Qianren Mao +13
We propose LLM-PeerReview, an unsupervised LLM Ensemble method that selects the most ideal response from multiple LLM-generated candidates for each query, harnessing the collective…
cs.HC2024
Quality Control in Open-Ended Crowdsourcing: A Survey
Lei Chai, Hailong Sun, Jing Zhang
Crowdsourcing provides a flexible approach for leveraging human intelligence to solve large-scale problems, gaining widespread acceptance in domains like intelligent information pr…