Nov. 5, 2023, 6:47 a.m. | JB. Kim, Hazel Kim, Joonghyuk Hahn, Yo-Sub Han

cs.CL updates on arXiv.org arxiv.org

Solving math word problems depends on how to articulate the problems, the
lens through which models view human linguistic expressions. Real-world
settings count on such a method even more due to the diverse practices of the
same mathematical operations. Earlier works constrain available thinking
processes by limited prediction strategies without considering their
significance in acquiring mathematical knowledge. We introduce Attention-based
THought Expansion Network Architecture (ATHENA) to tackle the challenges of
real-world practices by mimicking human thought expansion mechanisms in the …

arxiv athena count diverse expansion human math mathematical reasoning operations practices prediction processes reasoning strategies thinking thought through word world

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US