7:00 – 4:00 ASRC GOES

• Dissertation – reworked the last paragraph of the Reflection and reflex section
  • Spooky to see this: Adversarial Examples that Fool both Computer Vision and Time-Limited Humans
    • Citing papers including ‘human’
• Evolver – more documentation
• Send this out to the HCC mailing list: The introvert’s academic “alternative networking” guide
• Arpita’s proposal defense
  • Stanford: Open information extraction (open IE) refers to the extraction of relation tuples, typically binary relations, from plain text, such as (Mark Zuckerberg; founded; Facebook). The central difference from other information extraction is that the schema for these relations does not need to be specified in advance; typically the relation name is just the text linking two arguments. For example, Barack Obama was born in Hawaii would create a triple (Barack Obama; was born in; Hawaii), corresponding to the open domain relation was-born-in(Barack-Obama, Hawaii).
  • Open Information Extraction 5
  • UKG Open Information Extraction
  • Supervised Ensemble of Open IE
  • Datasets
    • AW-OIE
    • AW-OIE-C
    • WEB
    • NYT
    • PENN
  • Why the choice of 100 dimensins for your symentic embedding? How does it compare to other dimensions?
  • Contextual embedding for NLP?
  • Input-Output Hidden Markov Model (version on GitHub)