collaborators

5 papers

cs.CL2025

Knowledge Extraction on Semi-Structured Content: Does It Remain Relevant for Question Answering in the Era of LLMs?

Kai Sun, Yin Huang, Srishti Mehra +11

The advent of Large Language Models (LLMs) has significantly advanced web-based Question Answering (QA) systems over semi-structured content, raising questions about the continued…

cs.AI2025

Memory-QA: Answering Recall Questions Based on Multimodal Memories

Hongda Jiang, Xinyuan Zhang, Siddhant Garg +10

We introduce Memory-QA, a novel real-world task that involves answering recall questions about visual content from previously stored multimodal memories. This task poses unique cha…

cs.CL2025

KERAG: Knowledge-Enhanced Retrieval-Augmented Generation for Advanced Question Answering

Yushi Sun, Kai Sun, Yifan Ethan Xu +4

Retrieval-Augmented Generation (RAG) mitigates hallucination in Large Language Models (LLMs) by incorporating external data, with Knowledge Graphs (KGs) offering crucial informatio…

cs.AI2025

Proactive Assistant Dialogue Generation from Streaming Egocentric Videos

Yichi Zhang, Xin Luna Dong, Zhaojiang Lin +5

Recent advances in conversational AI have been substantial, but developing real-time systems for perceptual task guidance remains challenging. These systems must provide interactiv…

cs.CV2024

SnapNTell: Enhancing Entity-Centric Visual Question Answering with Retrieval Augmented Multimodal LLM

Jielin Qiu, Andrea Madotto, Zhaojiang Lin +7

Vision-extended LLMs have made significant strides in Visual Question Answering (VQA). Despite these advancements, VLLMs still encounter substantial difficulties in handling querie…