Papers Compositional Generalization (AVG)
“Compositional Generalization (AVG)” 태그가 달린 논문 4편 · 필터 해제
NeSyCoCo: A Neuro-Symbolic Concept Composer for Compositional Generalization
Compositional generalization is crucial for artificial intelligence agents to solve complex vision-language reasoning tasks. Neuro-symbolic approaches have demonstrated promise in capturing compositional structures, but …
Compositional Generalization (AVG)Novel ConceptsVisual Question AnsweringVisual Question Answering (VQA)+2Syntax-Guided Transformers: Elevating Compositional Generalization and Grounding in Multimodal Environments
Compositional generalization, the ability of intelligent models to extrapolate understanding of components to novel compositions, is a fundamental yet challenging facet in AI research, especially within multimodal enviro…
Compositional Generalization (AVG)Dependency ParsingWhen Can Transformers Ground and Compose: Insights from Compositional Generalization Benchmarks
Humans can reason compositionally whilst grounding language utterances to the real world. Recent benchmarks like ReaSCAN use navigation tasks grounded in a grid world to assess whether neural models exhibit similar capab…
Compositional Generalization (AVG)Systematic Generalization on gSCAN: What is Nearly Solved and What is Next?
We analyze the grounded SCAN (gSCAN) benchmark, which was recently proposed to study systematic generalization for grounded language understanding. First, we study which aspects of the original benchmark can be solved by…
Compositional Generalization (AVG)Systematic Generalization