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Paper Index on ACL Anthology

A Bounded Coordination-Support Capability for Multi-Party Settings: Task-State Monitoring in Firefighter Incident Command A Dataset of Latin Etymologies Extracted from Wiktionary An Efficient Approach for Answering Not Readily Attainable Questions for RAG-based Applications Automated German Alt Text Generation for News Charts Call Support Copilot: A Reproducible Multimodal System for Speech Emotion Recognition, Intent Understanding, and Agent Assistance Can Large Language Models Replace Statistical Software? Code-Switching Detection in Multilingual Child Speech with SwissBERT Concept Extraction and Webb’s Depth of Knowledge: Comparing LLM Question Generation Pipelines for Educational Assessment Data Augmentation for Historical NER: A Systematic Comparison of Lexical and LLM-based Approaches Enhancing Retrieval via Cognitively Motivated Document Expansion Extending the Contact Hypothesis: Cross-Linguistic Evaluation of Religion and Nationality Bias When Prompting LLMs in German and Icelandic Extracting Article-Level Legal Dependencies from Swiss Federal Law using LLMs How Good is AI on Swiss Voting Booklets? A Multilingual OCR and Alignment Benchmark Optimizing Large Language Models for Robust Domain-Specific Text-to-SQL: From Prompting to Preference Alignment Proceedings of the 11th Edition of the Swiss Text Analytics Conference Reinforcement Learning for Latent-Space Thinking in LLMs RUMLEM: A Dictionary-Based Lemmatizer for Romansh Skill Extraction from Resumes and Job Offers across Six Languages Text vs. Phoneme Intermediates for Low-Resource Swiss German The Same Email, Signed Differently: Testing Negotiation Bias and Recommendation Stability in LLMs Which Skills Debate Reaches the Public? Comparing Scientific Literature and Media Coverage of AI and LLM Skill Impacts (2022–2025) Controlling Language and Style of Multi-lingual Generative Language Models with Control Vectors Hybrid Human-LLM Corpus Construction and LLM Evaluation for the Caused-Motion Construction Implicit and Indirect: Detecting Face-threatening and Paired Actions in Asynchronous Online Conversations Northern European Journal of Language Technology, Volume 11 A modular architecture for creating multimodal embodied agents with an episodic Knowledge Graph as an explainable and controllable long-term memory A Neural Approach to Discourse Relation Signal Detection An Analysis of Japanese Sentence-final Particle Yone: Compare Yone and Ne in Response Attribution and the discourse structure of reports Automatic Detection of the Bulgarian Evidential Renarrative
Does ChatGPT Adapt Itself to the Language Used and the Au...
2026-04-20 · via Paper Index on ACL Anthology

Abstract

This paper seeks to quantify and analyse the progress that ChatGPT has made from its GPT-3.5 (2022) to its GPT-4.5 (2025) version when it comes to answering prompts in a selection of differently-resourced languages: English, Bulgarian, Greek, French, Hebrew, Japanese and Russian. Factual correctness, textual quality and an answer’s linguistic and cultural independence from an English baseline are evaluated in the process. Each response is marked positively or negatively for each of the three metrics based on a set of defined criteria and careful humanbased analysis. In addition, three categories of questions are experimented with: general (e.g. communication assistance or request for jokes), perception-related (e.g. creative writing or explanation of physical processes) and geography-/culture-sensitive (questions in a specific language that address a particular, slightly sensitive topic related to the implied audience e.g. ’Why do French people eat snails?’). As hypothesised, the recent GPT-4.5 version demonstrates significant progress in all evaluated categories, thereby resolving past issues such as decreased textual quality of low-resourced languages and, notably, very limited variety in answers to the same question across languages. The metric ’Independence from the (English) Baseline’ receives 80.95% of positive marks in the GPT-4.5 version as opposed to 26.19% for GPT-3.5. Lingering problems include ChatGPT’s incomplete ability to generate relevant and culturally-sensitive jokes and poems.

Anthology ID:
2025.jclib-1.2
Volume:
Journal Computational Linguistics in Bulgaria
Month:
July
Year:
2025
Address:
Sofia, Bulgaria
Editor:
Svetla Koeva
Venue:
JCLIB
SIG:
Publisher:
Institute for Bulgarian Language, Department of Computational Linguistics, Bulgarian Academy of Sciences
Note:
Pages:
11–41
Language:
URL:
https://aclanthology.org/2025.jclib-1.2/
DOI:
10.47810/JCLIB.1.2025.02
Bibkey:
Cite (ACL):
Iglika Nikolova Stoupak, Gaël Lejeune, and Eva Schaeffer-Lacroix. 2025. Does ChatGPT Adapt Itself to the Language Used and the Audience It Implies?. Journal Computational Linguistics in Bulgaria, 1:11–41.
Cite (Informal):
Does ChatGPT Adapt Itself to the Language Used and the Audience It Implies? (Stoupak et al., JCLIB 2025)
Copy Citation:
PDF:
https://aclanthology.org/2025.jclib-1.2.pdf