Many users expressed excitement about the paper showing that appending 300 dots boosts frontier LLMs on multi-hop reasoning tasks because they found the unexpected quirk cool and interesting.
Based on 20 visible X reactions from 96 accounts; directional sample.
Ask a question below.
Published answers will appear here.
@kaleybrauer The fact that you had to “investigate” and publish a whole paper on it is such a woman moment. All you had to do is understand the basics of how a transformer works. Each extra dot, is a new “round” where it chooses where to apply the attention mechanism.
@kaleybrauer How is this different from train of thought? Couldn’t the LLM learn to generate its own “dots whiteboard” with optimal length by itself..?
@kaleybrauer Did you ablate a lower bound on the amount of dots needed to give correct answers (ofc depending on per-question difficulty)?
@kaleybrauer Loved this! Was great chatting to you about it (ICML).
@kaleybrauer wait this is soo coool
Think tokens (still) exist in 2026! Nice study. Doesn't even need to be LLM... https://www.isca-archive.org/interspeech_2024/yang24g_interspeech.html "Empty" tokens are not always what they appear to be http://www.catb.org/jargon/html/koans.html#id3141241
Many users expressed excitement about the paper showing that appending 300 dots boosts frontier LLMs on multi-hop reasoning tasks because they found the unexpected quirk cool and interesting.
Based on 20 visible X reactions from 96 accounts; directional sample.
Ask a question below.
Published answers will appear here.