미어캣족장 on Instagram: "간식찾는 라쿤 #미어캣족장 #raccoon #guaxinim #rakun #アライグマ"
3,905 likes, 76 comments - meerkatchief on April 28, 2026: "간식찾는 라쿤 #미어캣족장 #raccoon #guaxinim #rakun #アライグマ".
ELLIE RINDY on Instagram: "nailed it! #funny #husbandandwife #princesstreatment #marriedyoung #utahinfluencer"
124K likes, 272 comments - elliee_rindyy on April 16, 2026: "nailed it! #funny #husbandandwife #princesstreatment #marriedyoung #utahinfluencer".
Frased.com on Instagram: "Asians do it better #quoteoftheday #funnyshirt #girlfriend #asian #inlove"
5,620 likes, 96 comments - frased.unfiltered on April 27, 2026: "Asians do it better #quoteoftheday #funnyshirt #girlfriend #asian #inlove".
Evan Tan on Instagram: "Oh no"
23K likes, 542 comments - evantan on January 13, 2026: "Oh no".
Jonathan Tan on Instagram: "Date preparation"
343K likes, 4,607 comments - jonathanxtan on April 16, 2026: "Date preparation".
Ian Boggs on Instagram: "Oldie but a goodie lol"
57K likes, 323 comments - ianboggz on January 23, 2026: "Oldie but a goodie lol".
Causal schema induction for knowledge discovery
Making sense of familiar yet new situations typically involves making generalizations about causal schemas, stories that help humans reason about event sequences. Reasoning about events includes identifying cause and effect relations shared across event instances, a process we refer to as causal schema induction. Statistical schema induction systems may leverage structural knowledge encoded in discourse or the causal graphs associated with event meaning, however resources to study such causal structure are few in number and limited in size. In this work, we investigate how to apply schema induction models to the task of knowledge discovery for enhanced search of English-language news texts. To tackle the problem of data scarcity, we present Torquestra, a manually curated dataset of text-graph-schema units integrating temporal, event, and causal structures. We benchmark our dataset on three knowledge discovery tasks, building and evaluating models for each. Results show that systems that harness causal structure are effective at identifying texts sharing similar causal meaning components rather than relying on lexical cues alone. We make our dataset and models available for research purposes.
Home - Octosphere
Octosphere bridges the gap between academic publishing and the social web. It automatically syncs your research publications from Octopus to the AT Protocol (the atmosphere) — an open, decentralized network for social apps like Bluesky.
Good book for learning and practising axiomatic logic
I want to learn axiomatic (Hilbert style ) logic. not just a book that says that it exist and is an good way to proof theorems. What is a good book to learn and practice this method? would like: ...
Useful Mental Model: Normal Distribution - Scott H Young
Some ideas are so powerful once you know them, you start to see them everywhere. Normal distributions are one of these ideas. Let's understand it!
Bayesian Thinking in Everyday Life
More than 200 years ago, Thomas Bayes came up with a brilliant idea that has helped shape the world today, called Bayes Theorem. This…
Descriptions Aren’t Prescriptions
When we look at a representation of reality, we can choose to either see it as descriptive, meaning it tells us what the world is currently like, or as prescriptive, meaning it tells us how the world should be. Descriptions teach us, but they also give us room to innovate. Prescriptions can get us stuck. One place this tension shows up is in language.
