I know we are moving away from Reddit. However, if I don't link, I feel like we may miss out good threads on r/machinelearning. Moreover, the authors don't only post arxiv links, they post other sutff such as Summary, Key points, ... (e.g this).
So can I at least put them in the posts instead of posting in a comment?
I find the link valuable. Despite the proliferation of AI in pop culture, actual discussion of machine learning research is still niche. The community on Reddit is quite valuable and took a long time to form.
If there isn't any discussion on reddit (no discussion in this case), I don't see a reason to link to reddit; you can just link to the project page. That said, if you think there is important discussion happening that is helpful for understanding the paper, then use a teddit link instead, like:
It seems like for creative text generation tasks, metrics have been shown to be deficient; this even holds for the new model-based metrics. That leaves human evaluation (both intrinsic and extrinsic) as the gold standard for those types of tasks. I wonder if the results from this paper (and other future papers that look automatic CV metrics) will lead reviewers to demand more human evaluation in CV tasks like they do for certain NLP tasks.
If the effect is strong enough, then it could have a very negative effect on LLM training in the near future, considering more and more of the internet contains ChatGPT & GPT-4 content in it and automatic detectors are currently quite poor.
Yeah it does not portend well for the future, especially combined with the current explosion of low quality, profit driven content. I fear if left unchecked we could approach some kind of Kessler Syndrome-style scenario where desire for rapid growth and profit will poison the well in the long term. "Garbage in, garbage out"
machinelearning
Popular
Esta revista es de un servidor federado y podría estar incompleta. Explorar más contenido en la instancia original.