mlsanityData to 13 Oct 2026

DimonGen: Diversified Generative Commonsense Reasoning for Explaining Concept Relationships

arXiv 2212.10545 ↗First posted 20 Dec 2022cs.CL cs.AIcited by 7

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

In this paper, we propose DimonGen, which aims to generate diverse sentences describing concept relationships in various everyday scenarios. To support this, we first create a benchmark dataset for this task by adapting the existing CommonGen dataset. We then propose a two-stage model called MoREE to generate the target sentences. MoREE consists of a mixture of retrievers model that retrieves diverse context sentences related to the given concepts, and a mixture of generators model that generates diverse sentences based on the retrieved contexts. We conduct experiments on the DimonGen task and show that MoREE outperforms strong baselines in terms of both the quality and diversity of the generated sentences. Our results demonstrate that MoREE is able to generate diverse sentences that reflect different relationships between concepts, leading to a comprehensive understanding of concept relationships.

Key facts. Cited by 7 papers in the map (data through 13 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 2 of its 36 references that are in the map. First posted on arXiv 20 Dec 2022.

Builds on

2 of 36 references.

References · 2

  1. 2022Internet-augmented language models through few-shot prompting for open-domain question answeringcited by 131
  2. 2022VER: Unifying Verbalizing Entities and Relationscited by 2

Built on by

Cited by year

Citing papers per year: 2023: 2; 2024: 2; 2025: 3.

7 papers.

  1. 2024Improving Diversity of Commonsense Generation by Large Language Models via In-Context Learningcited by 19
  2. 2025Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Abilitycited by 10
  3. 2023CCGen: Explainable Complementary Concept Generation in E-Commercecited by 5
  4. 2025MODS: Moderating a Mixture of Document Speakers to Summarize Debatable Queries in Document Collectionscited by 4
  5. 2024On the Role of Entity and Event Level Conceptualization in Generalizable Reasoning: A Survey of Tasks, Methods, Applications, and Future Directionscited by 3
  6. 2025Cooking Up Creativity: Enhancing LLM Creativity through Structured Recombinationcited by 3
  7. 2023Descriptive Knowledge Graph in Biomedical Domaincited by 1

Similar, not cited

Close in wording, no citation either way

  1. 2024The Mystery of Compositional Generalization in Graph-based Generative Commonsense Reasoning
  2. 2022Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts
  3. 2022Revisiting Generative Commonsense Reasoning: A Pre-Ordering Approach
  4. 2023Knowledge Graph-Augmented Korean Generative Commonsense Reasoning
  5. 2022Metric-guided Distillation: Distilling Knowledge from the Metric to Ranker and Retriever for Generative Commonsense Reasoning
  6. 2023SituatedGen: Incorporating Geographical and Temporal Contexts into Generative Commonsense Reasoning
  7. 2022Commonsense Knowledge Reasoning and Generation with Pre-trained Language Models: A Survey
  8. 2026CommonWhy: A Dataset for Evaluating Entity-Based Causal Commonsense Reasoning in Large Language Models