└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # Awesome Cultural NLP: [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome) 2 | A curated list of awesome cultural NLP resources, inspired by [awesome-computer-vision](https://github.com/jbhuang0604/awesome-computer-vision). 3 | 4 | **Table Of Contents** 5 | * [Survey](#survey) 6 | * [Dataset](#dataset) 7 | * [Image Captioning](#image-captioning) 8 | * [Models](#models) 9 | * [Vision and Language](#vision-and-language) 10 | * [Evaluation](#evaluation) 11 | * [LLMs](#llms) 12 | * [Text-to-image](#text-to-image) 13 | * [VLMs](#vlms) 14 | * [Analysis](#analysis) 15 | * [Text-to-image](#text-to-image) 16 | * [LLMs](#llms) 17 | * [VLMs](#vlms) 18 | * [Cross-cultural Variations](#cross-cultural-variations) 19 | * [Methodology](#methodology) 20 | * [Data](#data) 21 | * [Alignment](#alignment) 22 | * [Model](#model) 23 | * [Data](#data) 24 | * [Applications](#applications) 25 | 26 | 27 | ## Survey 28 | | Title | Conference / Journal | Paper | Code | Remarks | 29 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 30 | | Survey of Cultural Awareness in Language Models: Text and Beyond | Arxiv 2024 | https://arxiv.org/pdf/2411.00860 | []() | []() | 31 | | Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Art | Arxiv 2024 | [2406.03930](https://arxiv.org/pdf/2406.03930) | []() | []() | 32 | | Towards Measuring and Modeling “Culture” in LLMs: A Survey | Arxiv 2024 | [2403.15412](https://arxiv.org/pdf/2403.15412) | [Github](https://github.com/faridlazuarda/cultural-llm-papers) | Cool paper! | 33 | | Challenges and Strategies in Cross-Cultural NLP | ACL 2022 | [2203.10020](https://arxiv.org/abs/2203.10020) | []() | []() | 34 | | | | []() | []() | []() | 35 | 36 | ## Dataset 37 | | Title | Conference / Journal | Paper | Code | Remarks | 38 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 39 | | DIWALI - Diversity and Inclusivity aWare cuLture specific Items for India: Dataset and Assessment of LLMs for Cultural Text Adaptation in Indian Context | EMNLP Main (Oral) 2025 | [2509.17399](https://arxiv.org/abs/2509.17399) | [Dataset](https://huggingface.co/datasets/nlip/DIWALI), [Code](https://github.com/pramitsahoo/culture-evaluation), [Project Page](https://nlip-lab.github.io/nlip/publications/diwali/)| Data, Cultural Text Adaptation, LLM as Evaluator, Analysis | 40 | | Multi3Hate: Multimodal, Multilingual, and Multicultural Hate Speech Detection with Vision–Language Models | NAACL 2025 | https://aclanthology.org/2025.naacl-long.490/ | [Code](https://github.com/MinhDucBui/Multi3Hate) | [HF Datasets](https://huggingface.co/datasets/MinhDucBui/Multi3Hate) | 41 | | GIMMICK -- Globally Inclusive Multimodal Multitask Cultural Knowledge Benchmarking | Arxiv 2025 | [2502.13766](https://arxiv.org/abs/2502.13766) | [floschne/gimmick](https://github.com/floschne/gimmick) | [HF Datasets](https://huggingface.co/floschne) | 42 | | WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisines | Arxiv 2024 | [2410.12705](https://arxiv.org/pdf/2410.12705) | [Code, Data, and Leaderboard](https://worldcuisines.github.io/) | Data | 43 | |FoodieQA: A Multimodal Dataset for Fine-Grained Understanding of Chinese Food Culture| EMNLP 2024 | https://aclanthology.org/2024.emnlp-main.1063/ | [Code](https://github.com/lyan62/FoodieQA) [Data](https://huggingface.co/datasets/lyan62/FoodieQA)| Data| 44 | | BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages | NeurIPS D&B 2024 | [2406.09948](https://arxiv.org/abs/2406.09948) | [Code and Data](https://github.com/nlee0212/BLEnD) | Data | 45 | | Vision-Language Models under Cultural and Inclusive Considerations | Arxiv 2024 | [2407.06177](https://arxiv.org/pdf/2407.06177) | []() | []() | 46 | | Beyond Aesthetics: Cultural Competence in Text-to-Image Models | Arxiv 2024 | [2407.06863](https://arxiv.org/pdf/2407.06863) | [Data](https://github.com/google-research-datasets/cube) | Data | 47 | | M5 -- A Diverse Benchmark to Assess the Performance of Large Multimodal Models Across Multilingual and Multicultural Vision-Language Tasks | Arxiv 2024 | [2407.03791](https://arxiv.org/pdf/2407.03791) | [floschne/m5b](https://github.com/floschne/m5b) | [HF Datasets](https://huggingface.co/floschne) | 48 | | Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Art | Arxiv 2024 | [2406.03930](https://arxiv.org/pdf/2406.03930) | []() | []() | 49 | | NORMAD: A Benchmark for Measuring the Cultural Adaptability of Large Language Models | Arxiv 2024 | [2404.12464](https://arxiv.org/abs/2404.12464) | [Data](https://github.com/Akhila-Yerukola/NormAd) | Data | 50 | | An image speaks a thousand words, but can everyone listen? On image transcreation for cultural relevance | Arxiv 2024 | [2404.01247](https://arxiv.org/abs/2404.01247) | [Code and Data](https://github.com/simran-khanuja/image-transcreation) | Data + Application 51 | | No Culture Left Behind: Massively Multi-Cultural Knowledge Acquisition & LM Benchmarking on 1000+ Sub-Country Regions and 2000+ Ethnolinguistic Groups | Arxiv 2024 | [2402.09369v1](https://arxiv.org/pdf/2402.09369v1) | [Data](https://github.com/yrf1/LLM-MassiveMulticultureNormsKnowledge-NCLB) | []() | 52 | | The PRISM Alignment Project: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models | Arxiv 2024 (under review) | [2404.16019](https://arxiv.org/pdf/2404.16019) | [Repository](https://github.com/HannahKirk/prism-alignment) | Code and Data | 53 | | Exploring Cross-Cultural Differences in English Hate Speech Annotations: From Dataset Construction to Analysis | NAACL 2024 | [2308.16705](https://arxiv.org/abs/2308.16705) | [Data+Code](https://github.com/nlee0212/CREHate) | []() | 54 | | CLIcK: A Benchmark Dataset of Cultural and Linguistic Intelligence | LREC-COLING '24 | [https://arxiv.org/pdf/2403.06412](https://arxiv.org/pdf/2403.06412) | [Data](https://github.com/rladmstn1714/CLIcK) | []() | 55 | | Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys | EACL Findings 2024 | [2401.10352](https://arxiv.org/abs/2401.10352) | [Dataset](https://github.com/yongcaoplus/cuDialog) | []() | 56 | | Culturally Aware Natural Language Inference | EMNLP 2023 (Findings) | [2023.findings-emnlp.509](https://aclanthology.org/2023.findings-emnlp.509.pdf) | [Data](https://github.com/SALT-NLP/CulturallyAwareNLI) | []() | 57 | | Global Voices, Local Biases: Socio-Cultural Prejudices across Languages | EMNLP 2023 | [2310.17586](https://arxiv.org/abs/2310.17586) | [Data](https://github.com/iamshnoo/weathub) | Data+Analysis 58 | | NORMSAGE: Multi-Lingual Multi-Cultural Norm Discovery from Conversations On-the-Fly | EMNLP 2023 | [2210.08604](https://arxiv.org/abs/2210.08604) | [Code and Data](https://github.com/yrf1/NormSage) | NormsKB 59 | | GeoDE: a Geographically Diverse Evaluation Dataset for Object Recognition | Neurips 2023 | [2301.02560](https://arxiv.org/abs/2301.02560) | [Code and Data](https://geodiverse-data-collection.cs.princeton.edu/) | []() | 60 | | SeeGULL: A Stereotype Benchmark with Broad Geo-Cultural Coverage Leveraging Generative Models | ACL 2023 | [2305.11840](https://arxiv.org/pdf/2305.11840) | [Code](https://github.com/google-research-datasets/seegull) | []() | 61 | | FORK: A Bite-Sized Test Set for Probing Culinary Cultural Biases in Commonsense Reasoning Models | ACL Findings 2023 | [2023.findings-acl.631](https://aclanthology.org/2023.findings-acl.631.pdf) | [Dataset](https://github.com/shramay-palta/FORK_ACL2023) | []() | 62 | | Multi-lingual and Multi-cultural Figurative Language Understanding | ACL Findings 2023 | [2305.16171](https://arxiv.org/abs/2305.16171) | [Code](https://github.com/simran-khanuja/Multilingual-Fig-QA) | []() | 63 | | EnCBP: A New Benchmark Dataset for Finer-Grained Cultural Background Prediction in English | ACL Findings 2022 | [2203.14498](https://arxiv.org/abs/2203.14498) | []() | []() | 64 | | Re-contextualizing Fairness in NLP: The Case of India | AACL 2022 | [2209.12226](https://arxiv.org/abs/2209.12226) | [Data](https://github.com/google-research-datasets/nlp-fairness-for-india) | Data+Analysis 65 | | Visually Grounded Reasoning across Languages and Cultures | EMNLP 2021 | [2109.13238](https://arxiv.org/abs/2109.13238) | [Website](https://marvl-challenge.github.io/) | EMNLP 2021 Best Paper | 66 | | Would you Rather? A New Benchmark for Learning Machine Alignment with Cultural Values and Social Preferences | ACL 2020 | [2020.acl-main.477/](https://aclanthology.org/2020.acl-main.477/) | []() | []() | 67 | | SocialDial: A Benchmark for Socially-Aware Dialogue Systems | SIGIR 2023 | [3539618.3591877](https://dl.acm.org/doi/10.1145/3539618.3591877) | [Data](https://github.com/zhanhl316/SocialDial) | Data+Analysis+New Application | 68 | | RENOVI: A Benchmark Towards Remediating Norm Violations in Socio-Cultural Conversations | NAACL Findings 2024 | [2024.findings-naacl.196](https://aclanthology.org/2024.findings-naacl.196/) | [Data](https://github.com/zhanhl316/ReNoVi) | Data+Analysis+New Application | 69 | 70 | | | | []() | []() | []() | 71 | 72 | ## Image Captioning 73 | | Title | Conference / Journal | Paper | Code | Remarks | 74 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 75 | | CIC: A framework for Culturally-aware Image Captioning | IJCAI 2024 | [2402.05374](https://arxiv.org/abs/2402.05374) | [Webpage](https://shane3606.github.io/cic/) | []() | 76 | | | | []() | []() | []() | 77 | 78 | ## Models 79 | 80 | ### Vision and Language 81 | | Title | Conference / Journal | Paper | Code | Remarks | 82 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 83 | | GIVL: Improving Geographical Inclusivity of Vision-Language Models With Pre-Training Methods | CVPR 2023 | [2301.01893](https://arxiv.org/abs/2301.01893) | [Code (not released yet)](https://github.com/WadeYin9712/GIVL) | []() | 84 | | | | []() | []() | []() | 85 | 86 | ## Evaluation 87 | 88 | ### LLMs 89 | | Title | Conference / Journal | Paper | Code | Remarks | 90 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 91 | | DIWALI - Diversity and Inclusivity aWare cuLture specific Items for India: Dataset and Assessment of LLMs for Cultural Text Adaptation in Indian Context | EMNLP Main (Oral) 2025 | [2509.17399](https://arxiv.org/abs/2509.17399) | [Dataset](https://huggingface.co/datasets/nlip/DIWALI), [Code](https://github.com/pramitsahoo/culture-evaluation), [Project Page](https://nlip-lab.github.io/nlip/publications/diwali/)| Data, Cultural Text Adaptation, LLM as Evaluator, Analysis | 92 | | Cultural Conditioning or Placebo? On the Effectiveness of Socio-Demographic Prompting | Arxiv 2024 | [2406.11661](https://arxiv.org/pdf/2406.11661) | []() | []() | 93 | | Extrinsic Evaluation of Cultural Competence in Large Language Models | Arxiv 2024 | [2406.11565](https://arxiv.org/pdf/2406.11565) | []() | []() | 94 | | CulturalTeaming: AI-Assisted Interactive Red-Teaming for Challenging LLMs’ (Lack of) Multicultural Knowledge | Arxiv 2024 | [2404.06664](https://arxiv.org/pdf/2404.06664) | []() | []() | 95 | | Having Beer after Prayer? Measuring Cultural Bias in Large Language Models | ACL 2024 | [2305.14456](https://arxiv.org/pdf/2305.14456) | [Code](https://github.com/tareknaous/camel) | []() | 96 | | Large language models, social demography, and hegemony: comparing authorship in human and synthetic text | Journal of Big Data | [10.1186/s40537-024-00986-7](https://link.springer.com/article/10.1186/s40537-024-00986-7) | []() | []() | 97 | | | | []() | []() | []() | 98 | 99 | ### Text-to-image 100 | | Title | Conference / Journal | Paper | Code | Remarks | 101 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 102 | | The Factuality Tax of Diversity-Intervened Text-to-Image Generation: Benchmark and Fact-Augmented Intervention | Arxiv 2024 | [2407.00377v1](https://arxiv.org/pdf/2407.00377v1) | []() | []() | 103 | | On the Cultural Gap in Text-to-Image Generation | Arxiv 2023 | [2307.02971](https://arxiv.org/pdf/2307.02971) | [Code](https://github.com/longyuewangdcu/C3-Bench) | []() | 104 | | | | []() | []() | []() | 105 | 106 | ### VLMs 107 | | Title | Conference / Journal | Paper | Code | Remarks | 108 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 109 | | Multi3Hate: Multimodal, Multilingual, and Multicultural Hate Speech Detection with Vision–Language Models | NAACL 2025 | https://aclanthology.org/2025.naacl-long.490/ | [Code](https://github.com/MinhDucBui/Multi3Hate) | [HF Datasets](https://huggingface.co/datasets/MinhDucBui/Multi3Hate) | 110 | | GIMMICK -- Globally Inclusive Multimodal Multitask Cultural Knowledge Benchmarking | Arxiv 2025 | [2502.13766](https://arxiv.org/abs/2502.13766) | [floschne/gimmick](https://github.com/floschne/gimmick) | [HF Datasets](https://huggingface.co/floschne) | 111 | | From Local Concepts to Universals: Evaluating the Multicultural Understanding of Vision-Language Models | Arxiv 2024 | [2407.00263](https://arxiv.org/pdf/2407.00263) | []() | []() | 112 | | | | []() | []() | []() | 113 | 114 | 115 | ## Analysis 116 | 117 | ### Text-to-image 118 | | Title | Conference / Journal | Paper | Code | Remarks | 119 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 120 | | ViSAGe: A Global-Scale Analysis of Visual Stereotypes in Text-to-Image Generation | ACL 2024 | [2401.06310](https://arxiv.org/abs/2401.06310) | []() | []() | 121 | | DIG In: Evaluating Disparities in Image Generations with Indicators for Geographic Diversity | ICLR 2024 | [2308.06198](https://arxiv.org/pdf/2308.06198) | [Code](https://github.com/facebookresearch/DIG-In/) | []() | 122 | | Exploiting Cultural Biases via Homoglyphs in Text-to-Image Synthesis | JAIR 2023 | [2209.08891](https://arxiv.org/abs/2209.08891) | [Code](https://github.com/LukasStruppek/Exploiting-Cultural-Biases-via-Homoglyphs) | []() | 123 | | Navigating Cultural Chasms: Exploring and Unlocking the Cultural POV of Text-To-Image Models | Arxiv 2023 | [2310.01929](https://arxiv.org/abs/2310.01929) | [Code (not released yet)](https://github.com/venturamor/CulText-2-I) | []() | 124 | | Inspecting the Geographical Representativeness of Images from Text-to-Image Models | ICCV 2023 | [2305.11080](https://arxiv.org/abs/2305.11080) | []() | []() | 125 | | Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale | FAccT '23 | [2211.03759](https://arxiv.org/abs/2211.03759) | []() | []() | 126 | | Multilingual Conceptual Coverage in Text-to-Image Models | ACL 2023 | [2306.01735](https://arxiv.org/pdf/2306.01735) | [Code](https://github.com/michaelsaxon/CoCoCroLa) | []() | []() | 127 | | | | []() | []() | []() | 128 | 129 | ### LLMs 130 | | Title | Conference / Journal | Paper | Code | Remarks | 131 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 132 | | DIWALI - Diversity and Inclusivity aWare cuLture specific Items for India: Dataset and Assessment of LLMs for Cultural Text Adaptation in Indian Context | EMNLP Main (Oral) 2025 | [2509.17399](https://arxiv.org/abs/2509.17399) | [Dataset](https://huggingface.co/datasets/nlip/DIWALI), [Code](https://github.com/pramitsahoo/culture-evaluation), [Project Page](https://nlip-lab.github.io/nlip/publications/diwali/)| Data, Cultural Text Adaptation, LLM as Evaluator, Analysis | 133 | | The Echoes of Multilinguality: Tracing Cultural Value Shifts during LM Fine-tuning | ACL 2024 | [2405.12744](https://arxiv.org/pdf/2405.12744) | []() | []() | 134 | | Exploring Changes in Nation Perception with Nationality-Assigned 135 | Personas in LLMs | Arxiv 2024 | [2406.13993](https://arxiv.org/pdf/2406.13993) | []() | []() | 136 | | CULTURE-GEN: Revealing Global Cultural Perception in Language Models through Natural Language Prompting | Arxiv 2024 | [2404.10199v1](https://arxiv.org/abs/2404.10199v1) | [Code](https://github.com/huihanlhh/Culture-Gen/) | []() | 137 | | Knowledge of cultural moral norms in large language models | ACL 2023 | [2306.01857](https://arxiv.org/abs/2306.01857) | []() | []() | 138 | | Multilingual Language Models are not Multicultural: A Case Study in Emotion | WASSA: ACL 2023 | [2307.01370](https://arxiv.org/abs/2307.01370) | []() | []() | 139 | | Social Commonsense for Explanation and Cultural Bias Discovery | | []() | []() | []() | 140 | | DOSA: A Dataset of Social Artifacts from Different Indian Geographical Subcultures | LREC-COLING 2024 | [2403.14651](https://arxiv.org/abs/2403.14651) | [Code](https://github.com/microsoft/DOSA) | []() | 141 | | Attributing Culture-Conditioned Generations to Pretraining Corpora | ICLR 2025 | [2412.20760](https://arxiv.org/abs/2412.20760) | [Code](https://github.com/huihanlhh/CultureGenAttr) | []() | 142 | 143 | ### VLMs 144 | | Title | Conference / Journal | Paper | Code | Remarks | 145 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 146 | | Grounding Multilingual Multimodal LLMs With Cultural Knowledge | Arxiv 2025 | https://arxiv.org/pdf/2508.07414 | | | 147 | | Multilingual Diversity Improves Vision-Language Representations | Arxiv 2024 | [2405.16915](https://arxiv.org/pdf/2405.16915) | []() | []() | 148 | | No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision–Language Models | Arxiv 2024 |[2405.13777](https://arxiv.org/pdf/2405.13777) | []() | []() | 149 | | Computer Vision Datasets and Models Exhibit Cultural and Linguistic Diversity in Perception | Arxiv 2024 | [2310.14356](https://arxiv.org/pdf/2310.14356) | []() | []() | 150 | | Exploring Visual Culture Awareness in GPT-4V: A Comprehensive Probing | arxiv 2024 | [2402.06015](https://arxiv.org/pdf/2402.06015) | []() | []() | 151 | |‘Person’ == Light-skinned, Western Man, and Sexualization of Women of Color: Stereotypes in Stable Diffusion | EMNLP 2023 Findings | [2310.19981](https://arxiv.org/abs/2310.19981) | []() | []() | 152 | | | | []() | []() | []() | 153 | 154 | ### Cross-cultural Variations 155 | | Title | Conference / Journal | Paper | Code | Remarks | 156 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 157 | | Cross-Cultural Analysis of Human Values, Morals, and Biases in Folk Tales | EMNLP 2023 | [2023.emnlp-main.311](https://aclanthology.org/2023.emnlp-main.311/) | []() | []() | 158 | | Social Commonsense for Explanation and Cultural Bias Discovery | EACL 2023 | [2023.eacl-main.271.pdf](https://aclanthology.org/2023.eacl-main.271.pdf) | []() | []() | 159 | | Cross-cultural variation of speech-accompanying gesture: A review | Language and Cognitive Processes: Volume 24, Issue 2, 2009 | [10.1080/01690960802586188](https://www.tandfonline.com/doi/abs/10.1080/01690960802586188) | []() | []() | 160 | | | | []() | []() | []() | 161 | 162 | 163 | 164 | ## Alignment 165 | 166 | ### Models 167 | | Title | Conference / Journal | Paper | Code | Remarks | 168 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 169 | | Cultural Learning-Based Culture Adaptation of Language Models | ACL 2025 | https://aclanthology.org/2025.acl-long.156.pdf | | []() | 170 | | CultureLLM: Incorporating Cultural Differences into Large Language Models | NeurIPS 2024 | [2402.10946](https://arxiv.org/abs/2402.10946) | [Code](https://github.com/Scarelette/CultureLLM) | []() | 171 | | Investigating Cultural Alignment of Large Language Models | Arxiv 2024 | [2402.13231](https://arxiv.org/pdf/2402.13231) | []() | []() | 172 | | Unintended Impacts of LLM Alignment on Global Representation | Arxiv 2024 | [2402.15018](https://arxiv.org/abs/2402.15018) | []() | []() | 173 | | Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study | C3NLP: EACL 2023 | [2303.17466](https://arxiv.org/abs/2303.17466) | []() | Analysis | 174 | | Probing Pre-Trained Language Models for Cross-Cultural Differences in Values | C3NLP: EACL 2023 | [2203.13722](https://arxiv.org/abs/2203.13722) | []() | Analysis | 175 | | | | []() | []() | []() | 176 | 177 | ### Data 178 | | Title | Conference / Journal | Paper | Code | Remarks | 179 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 180 | | NLPositionality: Characterizing Design Biases of Datasets and Models | ACL 2023 (Outstanding Paper) | [2023.acl-long.505.pdf](https://aclanthology.org/2023.acl-long.505.pdf) | [Website](https://nlpositionality.cs.washington.edu/) | []() | 181 | 182 | 183 | ## Methodology 184 | 185 | ### Data 186 | | Title | Conference / Journal | Paper | Code | Remarks | 187 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 188 | | Cultural Concept Adaptation on Multimodal Reasoning | EMNLP 2023 | [EMNLP Main 18](https://aclanthology.org/2023.emnlp-main.18.pdf) | []() | []() | 189 | | | | []() | []() | []() | 190 | 191 | ## Applications 192 | | Title | Conference / Journal | Paper | Code | Remarks | 193 | | ------------------------------------------- | ---------- | ----------------------------------------- | ------------------------------------------- |-----------| 194 | | Cross-Cultural Similarity Features for Cross-Lingual Transfer Learning of Pragmatically Motivated Tasks | EACL 2021 | [2006.09336](https://arxiv.org/abs/2006.09336) | []() | Sentiment Analysis | 195 | | | | []() | []() | []() | 196 | 197 | ## Contributing 198 | Please feel free to send me [pull requests](https://github.com/simran-khanuja/awesome-cultural-nlp/pulls) or email (khanuja.simran7@gmail.com) to add links. 199 | 200 | ## Licenses 201 | License 202 | 203 | [![CC0](http://i.creativecommons.org/p/zero/1.0/88x31.png)](http://creativecommons.org/publicdomain/zero/1.0/) 204 | 205 | To the extent possible under law, [Simran Khanuja](https://simran-khanuja.github.io/) has waived all copyright and related or neighboring rights to this work. 206 | --------------------------------------------------------------------------------