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Czech Academy of Sciences
#sciencestudies | #researchfunding | #scholarlycommunication | #digitalhumanities | #computationalsocialscience | #scienceofscience | #rstats | #VedaVyzkum
Czech Academy of Sciences
It seems that the Noble Memorial Prize in Economic Sciences has gone to researchers who have worked on the problem of how to colonise a country better.
https://www.nobelprize.org/prizes/economic-sciences/2024/press-release/
The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2024 was awarded jointly to Daron Acemoglu, Simon Henry Roberts Johnson and James A. Robinson "for studies of how institutions are formed and affect prosperity"
Nice post by Stephen Turner about using Parquet files instead of CSV, with nanoparquet and/or duckdb: https://blog.stephenturner.us/p/use-nanoparquet-instead-of-readr-csv
📊 Today, CWTS has launched the Leiden Ranking Open Edition 2024! 🎉
As in the first release in January, the new version is completely based on @OpenAlex data, made possible by Our Research, and provides an open and transparent alternative to traditional university rankings.
Hello world! We're a research group led by Tiago Peixoto (@tiago) at the newly founded IT:U, Linz, Austria.
We focus on inverse problems in network science and complex systems.
Follow this account to get scientific updates!
new blog post on whether LLMs really reason, think, summarise etc.
as always, all comments welcome
https://write.as/ulrikehahn/do-llms-really-reason-understand-think-summarise
It's intriguing that there are neurons in LLMs that play specific functional roles such as regulating confidence (https://arxiv.org/abs/2406.16254) and that they may consistently emerge across different realizations of the LLMs (https://arxiv.org/abs/2401.12181).
Any biological analogues in human brain?
Despite their widespread use, the mechanisms by which large language models (LLMs) represent and regulate uncertainty in next-token predictions remain largely unexplored. This study investigates two critical components believed to influence this uncertainty: the recently discovered entropy neurons and a new set of components that we term token frequency neurons. Entropy neurons are characterized by an unusually high weight norm and influence the final layer normalization (LayerNorm) scale to effectively scale down the logits. Our work shows that entropy neurons operate by writing onto an unembedding null space, allowing them to impact the residual stream norm with minimal direct effect on the logits themselves. We observe the presence of entropy neurons across a range of models, up to 7 billion parameters. On the other hand, token frequency neurons, which we discover and describe here for the first time, boost or suppress each token's logit proportionally to its log frequency, thereby shifting the output distribution towards or away from the unigram distribution. Finally, we present a detailed case study where entropy neurons actively manage confidence in the setting of induction, i.e. detecting and continuing repeated subsequences.
This ....