Kalahi: A handcrafted, grassroots cultural LLM evaluation suite for Filipino
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Abstract (arXiv)
Multilingual large language models (LLMs) today may not necessarily provide culturally appropriate and relevant responses to its Filipino users. We introduce Kalahi, a cultural LLM evaluation suite collaboratively created by native Filipino speakers. It is composed of 150 high-quality, handcrafted and nuanced prompts that test LLMs for generations that are relevant to shared Filipino cultural knowledge and values. Strong LLM performance in Kalahi indicates a model's ability to generate responses similar to what an average Filipino would say or do in a given situation. We conducted experiments on LLMs with multilingual and Filipino language support. Results show that Kalahi, while trivial for Filipinos, is challenging for LLMs, with the best model answering only 46.0% of the questions correctly compared to native Filipino performance of 89.10%. Thus, Kalahi can be used to accurately and reliably evaluate Filipino cultural representation in LLMs.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 34 of its 68 references that are in the map. First posted on arXiv 20 Sep 2024.
Builds on
34 of 68 references.
References · 34
- 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
- 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
- 2021TruthfulQA: Measuring How Models Mimic Human Falsehoodscited by 2,919
- 2024Qwen2 Technical Reportcited by 2,076
- 2022BLOOM: A 176B-Parameter Open-Access Multilingual Language Modelcited by 1,968
- 2024Gemma 2: Improving Open Language Models at a Practical Sizecited by 1,928
- 2020BLEURT: Learning Robust Metrics for Text Generationcited by 1,196
- 2021A General Language Assistant as a Laboratory for Alignmentcited by 1,023
- 2018XNLI: Evaluating Cross-lingual Sentence Representationscited by 913
- 2023The Falcon Series of Open Language Modelscited by 526
- 2023Towards Measuring the Representation of Subjective Global Opinions in Language Modelscited by 424
- 2020XCOPA: A Multilingual Dataset for Causal Commonsense Reasoningcited by 330
22 more
- 2023MEGA: Multilingual Evaluation of Generative AIcited by 291
- 2022Challenges and Strategies in Cross-Cultural NLPcited by 216
- 2023ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learningcited by 203
- 2024Towards Measuring and Modeling "Culture" in LLMs: A Surveycited by 166
- 2022Probing Pre-Trained Language Models for Cross-Cultural Differences in Valuescited by 147
- 2022Power to the People? Opportunities and Challenges for Participatory AIcited by 137
- 2024Aya 23: Open Weight Releases to Further Multilingual Progresscited by 121
- 2024CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmarkcited by 118
- 2023SeaLLMs -- Large Language Models for Southeast Asiacited by 104
- 2022Towards Leaving No Indic Language Behind: Building Monolingual Corpora, Benchmark and Models for Indic Languagescited by 99
- 2023SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural Reasoningcited by 94
- 2024Can multiple-choice questions really be useful in detecting the abilities of LLMs?cited by 66
- 2024Massively Multi-Cultural Knowledge Acquisition & LM Benchmarkingcited by 63
- 2024How Well Do LLMs Represent Values Across Cultures? Empirical Analysis of LLM Responses Based on Hofstede Cultural Dimensionscited by 51
- 2024IndoCulture: Exploring Geographically-Influenced Cultural Commonsense Reasoning Across Eleven Indonesian Provincescited by 38
- 2023COPAL-ID: Indonesian Language Reasoning with Local Culture and Nuancescited by 35
- 2023EtiCor: Corpus for Analyzing LLMs for Etiquettescited by 33
- 2024Does Mapo Tofu Contain Coffee? Probing LLMs for Food-related Cultural Knowledgecited by 29
- 2024DOSA: A Dataset of Social Artifacts from Different Indian Geographical Subculturescited by 23
- 2024A Study on Large Language Models' Limitations in Multiple-Choice Question Answeringcited by 22
- 2024Cultural Conditioning or Placebo? On the Effectiveness of Socio-Demographic Promptingcited by 22
- 2024Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveyscited by 18
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