Perplexity(@perplexity_ai)
We've published new research on how we post-train models for accurate search-augmented answers. Our...
8.0内容质量
TL;DR · AI 摘要
Perplexity发布新研究，介绍SFT+RL pipeline如何提升搜索增强型问答能力。
核心要点
- SFT+RL pipeline改善搜索、引用和指令遵循能力。
- 使用Qwen模型在事实性上媲美或超越GPT模型。
- 以更低的成本实现高性能的事实性输出。
#AI#Qwen#GPT#机器学习
打开原文Our SFT + RL pipeline improves search, citation quality, instruction following, and efficiency.
With Qwen models, we match or beat GPT models on factuality at a lower cost. https://t.co/0w0Jmc9xlS" / X
Perplexity on X: "We've published new research on how we post-train models for accurate search-augmented answers. Our SFT + RL pipeline improves search, citation quality, instruction following, and efficiency. With Qwen models, we match or beat GPT models on factuality at a lower cost. https://t.co/0w0Jmc9xlS" / X
Don’t miss what’s happening
We've published new research on how we post-train models for accurate search-augmented answers. Our SFT + RL pipeline improves search, citation quality, instruction following, and efficiency. With Qwen models, we match or beat GPT models on factuality at a lower cost.
·
41
91
920
423
Read 41 replies