2 citations · 3 across the 4 of their papers we have counts for
4 papers
Weakly Supervised Semantic Parsing with Execution-based Spurious Program Filtering
Kang-il Lee, Segwang Kim, Kyomin Jung
The problem of spurious programs is a longstanding challenge when training a semantic parser from weak supervision. To eliminate such programs that have wrong semantics but correct…
Asking Clarification Questions to Handle Ambiguity in Open-Domain QA
Dongryeol Lee, Segwang Kim, Minwoo Lee +4
Ambiguous questions persist in open-domain question answering, because formulating a precise question with a unique answer is often challenging. Previously, Min et al. (2020) have…
Neural Sequence-to-grid Module for Learning Symbolic Rules
Segwang Kim, Hyoungwook Nam, Joonyoung Kim +1
Logical reasoning tasks over symbols, such as learning arithmetic operations and computer program evaluations, have become challenges to deep learning. In particular, even state-of…
Number Sequence Prediction Problems for Evaluating Computational Powers of Neural Networks
Hyoungwook Nam, Segwang Kim, Kyomin Jung
Inspired by number series tests to measure human intelligence, we suggest number sequence prediction tasks to assess neural network models' computational powers for solving algorit…