4 ms·
Research paper: https://arxiv.org/abs/2301.11305 https://arxiv.org/abs/2301.11305 Additional explanation: https://twitter.com/_eric_mitchell_/status/16188203
by O__________O 4y ago
Research paper:
https://arxiv.org/abs/2301.11305 https://arxiv.org/abs/2301.11305
Additional explanation:
https://twitter.com/_eric_mitchell_/status/1618820361419915264 https://twitter.com/_eric_mitchell_/status/16188203614199152...
- m00viin_pics 4y agoAwesome thread by one of the authors of paper, concise and insightful, thanks for sharing ! Research was aiming to bring a tool/approach on distinguishing text from LLM and other sources but in the end of the day it will only benefit those with non-open-source LLMs adjust to such technique and "fool" better everyone else (cause we need log-probs out of a model on each of the sample text). It seems kinda ironic for me, maybe i missed some crucial point here.
- O__________O 4y agoHighly unlikely any popular model would not provide log-probs, since they’re potentially useful. For example: https://aidungeon.medium.com/controlling-gpt-3-with-logit-bias-55866d593292 https://aidungeon.medium.com/controlling-gpt-3-with-logit-bi...