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Transactions of the Association for Computational Linguistics

Efficient Tuning of Large Language Models for Knowledge-Grounded Dialogue Generation A Systematic Review of NLP for Dementia: Tasks, Datasets and Opportunities TALE: Token-Adaptive Low-Rank KVCache Approximation with Reconstruction Elimination Large Language Models Are Human-Like Internally BenCzechMark : A Czech-centric Multitask and Multimetric Benchmark for Large Language Models with Duel Scoring Mechanism Adding Chocolate to MINT: Mitigating Metric Interference in Machine Translation Objectifying the Subjective: Cognitive Biases in Topic Interpretations Elements of World Knowledge (EWoK): A cognition-inspired framework for evaluating basic world knowledge in language models End-to-End Long Document Summarization using Gradient Caching MURI: High-Quality Instruction Tuning Datasets for Low-Resource Languages via Reverse Instructions CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and Augmentation Human Choice Prediction in Language-Based Persuasion Games: Simulation-Based Off-Policy Evaluation Adversarial Defence without Adversarial Defence: Enhancing Language Model Robustness via Instance-level Principal Component Removal Exploring Practical Gaps in Using Cross Entropy to Implement Maximum Mutual Information Criterion for Rationalization Benchmarking Linguistic Diversity of Large Language Models Do Large Multimodal Models Solve Caption Generation for Scientific Figure? Lessons Learned from SciCap Challenge 2023 MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systems KEFT: Knowledge-Enhanced Fine-Tuning for Large Language Models in Domain-Specific Question Answering Active Knowledge Structuring for Large Language Models in Materials Science Text Mining How to Select Datapoints for Efficient Human Evaluation of NLG Models? A Unifying Scheme for Extractive Content Selection Tasks Early Detection and Reduction of Memorisation for Domain Adaptation and Instruction Tuning Towards More Realistic Extraction Attacks: An Adversarial Perspective The Frame Representation Hypothesis: Multi-Token LLM Interpretability and Concept-Guided Text Generation Overcoming Source Object Grounding for Semantic Image Editing Explanatory Summarization with Discourse-Driven Planning On the Effect of Instruction Tuning Loss on Generalization BharatBBQ: A Multilingual Bias Benchmark for Question Answering in the Indian Context Are Triggers Needed for Document-Level Event Extraction? Safe Pruning LoRA: Robust Distance-Guided Pruning for Safety Alignment in Adaptation of LLMs
Culturally Aware and Adapted NLP: A Taxonomy and a Survey...
Chen Cecilia · 2025-12-25 · via Transactions of the Association for Computational Linguistics

Abstract

The surge of interest in culture in NLP has inspired much recent research, but a shared understanding of "culture" remains unclear, making it difficult to evaluate progress in this emerging area. Drawing on prior research in NLP and related fields, we propose a fine-grained taxonomy of elements in culture that can provide a systematic framework for analyzing and understanding research progress. Using the taxonomy, we survey existing resources and methods for culturally aware and adapted NLP, providing an overview of the state of the art and the research gaps that still need to be filled.

Article at MIT Press