mlsanityData to 14 Oct 2026

GD-COMET: A Geo-Diverse Commonsense Inference Model

arXiv 2310.15383 ↗First posted 23 Oct 2023cs.CLcited by 13

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Abstract (arXiv)

With the increasing integration of AI into everyday life, it's becoming crucial to design AI systems that serve users from diverse backgrounds by making them culturally aware. In this paper, we present GD-COMET, a geo-diverse version of the COMET commonsense inference model. GD-COMET goes beyond Western commonsense knowledge and is capable of generating inferences pertaining to a broad range of cultures. We demonstrate the effectiveness of GD-COMET through a comprehensive human evaluation across 5 diverse cultures, as well as extrinsic evaluation on a geo-diverse task. The evaluation shows that GD-COMET captures and generates culturally nuanced commonsense knowledge, demonstrating its potential to benefit NLP applications across the board and contribute to making NLP more inclusive.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Builds on 25 of its 35 references that are in the map. First posted on arXiv 23 Oct 2023.

Builds on

25 of 35 references.

References · 25

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  2. 2016ConceptNet 5.5: An Open Multilingual Graph of General Knowledgecited by 1,067
  3. 2019VL-BERT: Pre-training of Generic Visual-Linguistic Representationscited by 954
  4. 2018From Recognition to Cognition: Visual Commonsense Reasoningcited by 556
  5. 2019COMET: Commonsense Transformers for Automatic Knowledge Graph Constructioncited by 450
  6. 2021Symbolic Knowledge Distillation: from General Language Models to Commonsense Modelscited by 270
  7. 2020COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphscited by 254
  8. 2022Challenges and Strategies in Cross-Cultural NLPcited by 218
  9. 2023Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Studycited by 206
  10. 2021Visually Grounded Reasoning across Languages and Culturescited by 189
  11. 2020Social Biases in NLP Models as Barriers for Persons with Disabilitiescited by 182
  12. 2022Probing Pre-Trained Language Models for Cross-Cultural Differences in Valuescited by 149
13 more
  1. 2022Extracting Cultural Commonsense Knowledge at Scalecited by 76
  2. 2021Common Sense Beyond English: Evaluating and Improving Multilingual Language Models for Commonsense Reasoningcited by 65
  3. 2020Measuring Social Biases in Grounded Vision and Language Embeddingscited by 61
  4. 2021Broaden the Vision: Geo-Diverse Visual Commonsense Reasoningcited by 59
  5. 2020Automated Storytelling via Causal, Commonsense Plot Orderingcited by 38
  6. 2020R3: Reverse, Retrieve, and Rank for Sarcasm Generation with Commonsense Knowledgecited by 32
  7. 2021Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resourcescited by 30
  8. 2020Towards an Atlas of Cultural Commonsense for Machine Reasoningcited by 29
  9. 2019Commonsense Properties from Query Logs and Question Answering Forumscited by 26
  10. 2020Paragraph-level Commonsense Transformers with Recurrent Memorycited by 23
  11. 2022StereoKG: Data-Driven Knowledge Graph Construction for Cultural Knowledge and Stereotypescited by 14
  12. 2023GIVL: Improving Geographical Inclusivity of Vision-Language Models with Pre-Training Methodscited by 11
  13. 2023COMET-M: Reasoning about Multiple Events in Complex Sentencescited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 4; 2025: 5; 2026: 4.

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  1. 2024Towards Measuring and Modeling "Culture" in LLMs: A Surveycited by 167
  2. 2025Culture is Not Trivia: Sociocultural Theory for Cultural NLPcited by 40
  3. 2024Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Artcited by 26
  4. 2024Cultural Commonsense Knowledge for Intercultural Dialoguescited by 20
  5. 2024From Local Concepts to Universals: Evaluating the Multicultural Understanding of Vision-Language Modelscited by 14
  6. 2025A survey of diversity quantification in natural language processing: The why, what, where and howcited by 4
  7. 2026Steering LLMs for Culturally Localized Generationcited by 4
  8. 2026Location Not Found: Exposing Implicit Local and Global Biases in Multilingual LLMscited by 4
  9. 2026Every Token Counts: Exact Likert-Scale Distributions for Measuring LLM Attitudes and Biasescited by 3
  10. 2025Arguments that Alter Minds: LLM Rationales Sway Human (and LLM) Notions of Plausibilitycited by 2
  11. 2025Speaking the Right Language: The Impact of Expertise Alignment in User-AI Interactionscited by 1
  12. 2025ALIGN: Word Association Learning for Cultural Alignment in Large Language Modelscited by 0
1 more
  1. 2026LLMs as Cultural Archives: Cultural Commonsense Knowledge Graph Extractioncited by 0