Papers by Qisheng Liao

3 papers
Fumbling in Babel: An Investigation into ChatGPT’s Language Identification Ability (2024.findings-naacl)

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Challenge: ChatGPT is a powerful NLP tool but its language identification abilities are unclear.
Approach: They compile a benchmark comprising 670 languages representing 23 language families spoken in five continents and compare their language identification abilities to ChatGPT's (both GPT-3.5 and GPT-4) performance.
Outcome: The proposed model performs poorly on African languages, while GPT-3.5 and GPT-4 perform poorly on English, Afrikaans, Arabic, Indonesian, Italian, Mandarin Chinese, and several more.
The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languages (2023.emnlp-main)

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Challenge: Existing instruction tuned large language models (LLMs) struggle to understand cross-lingual sociopragmatic meaning (SM) lack of comprehensive investigation into their ability to understand SM is partly due to SM not being adequately represented in any of the existing benchmarks.
Approach: They evaluate the performance of instruction tuned large language models (LLMs) on a multilingual benchmark specifically designed for SM understanding.
Outcome: The proposed benchmark outperforms instruction tuned large language models on a wide range of tasks but falls behind task-specific finetuned models.
FRAPPE: FRAming, Persuasion, and Propaganda Explorer (2024.eacl-demo)

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Challenge: FRAPPE is a linguistic analysis, persuasion, and propaganda-based news analysis system that analyzes articles for genre, framings, and persulasion techniques.
Approach: They propose a FRAming, Persuasion, and Propaganda Explorer system that analyzes articles for genre, framings, and use of persuation techniques.
Outcome: FRAPPE analyzes articles for genre, framings, and use of persuasion techniques . it also draws comparisons between persulasion and framping strategies adopted by a diverse pool of news outlets and countries across multiple languages for different topics .

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