Search Results for author:
Found 3 papers, 1 papers with code
Beyond LLMs: Advancing the Landscape of Complex Reasoning
Since the advent of Large Language Models a few years ago, they have often been considered the de facto solution for many AI problems.
Braid: Weaving Symbolic and Neural Knowledge into Coherent Logical Explanations
Traditional symbolic reasoning engines, while attractive for their precision and explicability, have a few major drawbacks: the use of brittle inference procedures that rely on exact matching (unification) of logical terms, an inability to deal with uncertainty, and the need for a precompiled rule-base of knowledge (the "knowledge acquisition" problem).
To Test Machine Comprehension, Start by Defining Comprehension
Many tasks aim to measure machine reading comprehension (MRC), often focusing on question types presumed to be difficult.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
