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korrents.com
As models keep growing, AI is running out of enough high-quality unique training tokens to keep up.Their words
As the model size grows significantly, we are running out of enough high-quality unique tokens.
Lilian Weng
Everything, newest first — across every channel. Their profile →
Hiding
24 June
1 May 2025
From one piece Why We Think 2 beliefs, in the piece's order there
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korrents.com
Longer test-time thinking improves an AI model's robustness to adversarial or unusual inputs.Their words
thinking for longer should be especially useful when the model is presented with an unusual input, such as an adversarial example or jailbreak attempt
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korrents.com
Large language models cannot reliably self-correct their own mistakes without external feedback.Their words
this self-correction capability turns out to not exist intrinsically among LLMs and does not easily work out of the box, due to various failure modes
28 November 2024
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korrents.com
More capable AI agents are more likely to find and exploit flaws in their reward functions.Their words
A more intelligent agent is more capable of finding "holes" in the design of reward function and exploiting the task specification-in other words, achieving higher proxy rewards but lower true rewards.
Reward Hacking in Reinforcement Learninglilianweng.github.io
7 July 2024
From one piece Extrinsic Hallucinations in LLMs 2 beliefs, in the piece's order there
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korrents.com
Using supervised fine-tuning to teach a language model new knowledge risks increasing its hallucination rate.Their words
These empirical results from Gekhman et al. (2024) point out the risk of using supervised fine-tuning for updating LLMs' knowledge.
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korrents.com
A language model avoids hallucinating only by being factual and admitting when it does not know the answer.Their words
To avoid hallucination, LLMs need to be (1) factual and (2) acknowledge not knowing the answer when applicable.
5 February 2024
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korrents.com
High-quality data collection depends more on careful human execution than on machine learning techniques alone.Their words
Lots of ML techniques in the post can help with data quality, but fundamentally human data collection involves attention to details and careful execution.
25 October 2023
23 June 2023
15 March 2023
8 September 2022
24 September 2021
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