Kind of .. depending on how sensitive you are to accuracy.
Also also, we've had powerful summarization techniques for decades now (deep-learning, or otherwise) - and they aren't susceptible to the hallucinations of present day Generative LLMs.
Also also, we've had powerful summarization techniques for decades now (deep-learning, or otherwise) - and they aren't susceptible to the hallucinations of present day Generative LLMs.
https://old.reddit.com/r/askscience/comments/4s5b5q/how_exac...
However, for most use cases, falsely attributing statements is a terrible failure case for a summarizing tool.
do you mean BERT, Seq2Seq and similar?
My biggest takeaway from summarization tasks was that the benchmarks/evals seemed rather.. lacking.