mlsanityData to 14 Oct 2026

Towards Generalizable Neuro-Symbolic Systems for Commonsense Question Answering

arXiv 1910.14087 ↗First posted 30 Oct 2019cs.CLcited by 37

Not on the map. Why?

Abstract (arXiv)

Non-extractive commonsense QA remains a challenging AI task, as it requires systems to reason about, synthesize, and gather disparate pieces of information, in order to generate responses to queries. Recent approaches on such tasks show increased performance, only when models are either pre-trained with additional information or when domain-specific heuristics are used, without any special consideration regarding the knowledge resource type. In this paper, we perform a survey of recent commonsense QA methods and we provide a systematic analysis of popular knowledge resources and knowledge-integration methods, across benchmarks from multiple commonsense datasets. Our results and analysis show that attention-based injection seems to be a preferable choice for knowledge integration and that the degree of domain overlap, between knowledge bases and datasets, plays a crucial role in determining model success.

Key facts. Cited by 37 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Oct 2019.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 16; 2022: 10; 2023: 8; 2024: 3.

37 papers.

Sort:

By area:

  1. 2021QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answeringcited by 388
  2. 2021Generated Knowledge Prompting for Commonsense Reasoningcited by 214
  3. 2021UNICORN on RAINBOW: A Universal Commonsense Reasoning Model on a New Multitask Benchmarkcited by 98
  4. 2021JointLK: Joint Reasoning with Language Models and Knowledge Graphs for Commonsense Question Answeringcited by 40
  5. 2021A Survey on Neural-symbolic Learning Systemscited by 39
  6. 2021Core Challenges in Embodied Vision-Language Planningcited by 30
  7. 2021Dimensions of Commonsense Knowledgecited by 29
  8. 2023CAR: Conceptualization-Augmented Reasoner for Zero-Shot Commonsense Question Answeringcited by 28
  9. 2021GNN is a Counter? Revisiting GNN for Question Answeringcited by 21
  10. 2021Think about it! Improving defeasible reasoning by first modeling the question scenariocited by 20
  11. 2021Benchmarking Knowledge-Enhanced Commonsense Question Answering via Knowledge-to-Text Transformationcited by 19
  12. 2022Unpacking Large Language Models with Conceptual Consistencycited by 18
25 more
  1. 2023BRAINTEASER: Lateral Thinking Puzzles for Large Language Modelscited by 18
  2. 2023GrapeQA: GRaph Augmentation and Pruning to Enhance Question-Answeringcited by 17
  3. 2023A Study of Situational Reasoning for Traffic Understandingcited by 13
  4. 2022Robust and Explainable Identification of Logical Fallacies in Natural Language Argumentscited by 12
  5. 2021Exploring Strategies for Generalizable Commonsense Reasoning with Pre-trained Modelscited by 11
  6. 2022Coalescing Global and Local Information for Procedural Text Understandingcited by 10
  7. 2023Traffic-Domain Video Question Answering with Automatic Captioningcited by 10
  8. 2024Neuro-Symbolic AI: Explainability, Challenges, and Future Trendscited by 10
  9. 2021PaCo: Preconditions Attributed to Commonsense Knowledgecited by 9
  10. 2021Identify, Align, and Integrate: Matching Knowledge Graphs to Commonsense Reasoning Taskscited by 9
  11. 2023Characterizing Large Language Models as Rationalizers of Knowledge-intensive Taskscited by 9
  12. 2021SalKG: Learning From Knowledge Graph Explanations for Commonsense Reasoningcited by 7
  13. 2022Modularized Transfer Learning with Multiple Knowledge Graphs for Zero-shot Commonsense Reasoningcited by 5
  14. 2024Cognitive LLMs: Towards Integrating Cognitive Architectures and Large Language Models for Manufacturing Decision-makingcited by 5
  15. 2022Hidden Schema Networkscited by 4
  16. 2022Knowledge-driven Scene Priors for Semantic Audio-Visual Embodied Navigationcited by 4
  17. 2021ArT: All-round Thinker for Unsupervised Commonsense Question-Answeringcited by 3
  18. 2022Generalizable Neuro-symbolic Systems for Commonsense Question Answeringcited by 3
  19. 2022Intelligent Traffic Monitoring with Hybrid AIcited by 2
  20. 2021Understanding in Artificial Intelligencecited by 0
  21. 2022elBERto: Self-supervised Commonsense Learning for Question Answeringcited by 0
  22. 2022DiffG-RL: Leveraging Difference between State and Common Sensecited by 0
  23. 2023Core Challenges in Embodied Vision-Language Planningcited by 0
  24. 2023What can knowledge graph alignment gain with Neuro-Symbolic learning approaches?cited by 0
  25. 2024Bridging the Gap: Representation Spaces in Neuro-Symbolic AIcited by 0