4.5k citations · 5.4k across the 26 of their papers we have counts for
5 papers · 1 filter
Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models
Holy Lovenia, Wenliang Dai, Samuel Cahyawijaya +2
Object hallucination poses a significant challenge in vision-language (VL) models, often leading to the generation of nonsensical or unfaithful responses with non-existent objects.…
Survey of Social Bias in Vision-Language Models
Nayeon Lee, Yejin Bang, Holy Lovenia +3
In recent years, the rapid advancement of machine learning (ML) models, particularly transformer-based pre-trained models, has revolutionized Natural Language Processing (NLP) and…
Visual Instruction Tuning with Polite Flamingo
Delong Chen, Jianfeng Liu, Wenliang Dai +1
Recent research has demonstrated that the multi-task fine-tuning of multi-modal Large Language Models (LLMs) using an assortment of annotated downstream vision-language datasets si…
InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
Wenliang Dai, Junnan Li, Dongxu Li +6
Large-scale pre-training and instruction tuning have been successful at creating general-purpose language models with broad competence. However, building general-purpose vision-lan…
A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee +10
This paper proposes a framework for quantitatively evaluating interactive LLMs such as ChatGPT using publicly available data sets. We carry out an extensive technical evaluation of…