3 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.AI2025
GroundSight: Augmenting Vision-Language Models with Grounding Information and De-hallucination
Xinxi Chen, Tianyang Chen, Lijia Hong
We propose a method to improve Visual Question Answering (VQA) with Retrieval-Augmented Generation (RAG) by introducing text-grounded object localization. Rather than retrieving in…
cs.CL2024★ 3 cited
Honest AI: Fine-Tuning "Small" Language Models to Say "I Don't Know", and Reducing Hallucination in RAG
Xinxi Chen, Li Wang, Wei Wu +2
Hallucination is a key roadblock for applications of Large Language Models (LLMs), particularly for enterprise applications that are sensitive to information accuracy. To address t…
cs.CL2023★ 2 cited
Mini-Giants: "Small" Language Models and Open Source Win-Win
Zhengping Zhou, Lezhi Li, Xinxi Chen +1
ChatGPT is phenomenal. However, it is prohibitively expensive to train and refine such giant models. Fortunately, small language models are flourishing and becoming more and more c…