5 papers
Vision Language Models are Biased
An Vo, Khai-Nguyen Nguyen, Mohammad Reza Taesiri +3
Large language models (LLMs) memorize a vast amount of prior knowledge from the Internet that helps them on downstream tasks but also may notoriously sway their outputs towards wro…
LooComp: Leverage Leave-One-Out Strategy to Encoder-only Transformer for Efficient Query-aware Context Compression
Thao Do, Dinh Phu Tran, An Vo +2
Efficient context compression is crucial for improving the accuracy and scalability of question answering. For the efficiency of Retrieval Augmented Generation, context should be d…
VMMU: A Vietnamese Multitask Multimodal Understanding and Reasoning Benchmark
Vy Tuong Dang, An Vo, Emilio Villa-Cueva +4
We introduce VMMU, a Vietnamese Multitask Multimodal Understanding and Reasoning Benchmark designed to evaluate how vision-language models (VLMs) interpret and reason over visual a…
B-score: Detecting biases in large language models using response history
An Vo, Mohammad Reza Taesiri, Daeyoung Kim +1
Large language models (LLMs) often exhibit strong biases, e.g, against women or in favor of the number 7. We investigate whether LLMs would be able to output less biased answers wh…
Reference-Based Post-OCR Processing with LLM for Precise Diacritic Text in Historical Document Recognition
Thao Do, Dinh Phu Tran, An Vo +1
Extracting fine-grained OCR text from aged documents in diacritic languages remains challenging due to unexpected artifacts, time-induced degradation, and lack of datasets. While s…