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cs.CL2025

ViQA-COVID: COVID-19 Machine Reading Comprehension Dataset for Vietnamese

Hai-Chung Nguyen-Phung, Ngoc C. Lê, Van-Chien Nguyen +2

After two years of appearance, COVID-19 has negatively affected people and normal life around the world. As in May 2022, there are more than 522 million cases and six million death…

cs.CL2024

When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards

Norah Alzahrani, Hisham Abdullah Alyahya, Yazeed Alnumay +9

Large Language Model (LLM) leaderboards based on benchmark rankings are regularly used to guide practitioners in model selection. Often, the published leaderboard rankings are take…

cs.CL2024

Navigating the Shadows: Unveiling Effective Disturbances for Modern AI Content Detectors

Ying Zhou, Ben He, Le Sun

With the launch of ChatGPT, large language models (LLMs) have attracted global attention. In the realm of article writing, LLMs have witnessed extensive utilization, giving rise to…

cs.CL2024

Branch-Solve-Merge Improves Large Language Model Evaluation and Generation

Swarnadeep Saha, Omer Levy, Asli Celikyilmaz +3

Large Language Models (LLMs) are frequently used for multi-faceted language generation and evaluation tasks that involve satisfying intricate user constraints or taking into accoun…

cs.CL2024

"Sorry, Come Again?" Prompting -- Enhancing Comprehension and Diminishing Hallucination with [PAUSE]-injected Optimal Paraphrasing

Vipula Rawte, S. M Towhidul Islam Tonmoy, S M Mehedi Zaman +4

Hallucination has emerged as the most vulnerable aspect of contemporary Large Language Models (LLMs). In this paper, we introduce the Sorry, Come Again (SCA) prompting, aimed to av…