Question Answering

MMVU: a new benchmark pushes multimodal video understanding to expert level, revealing limitations of current models and paving the way for more advanced AI.

GeAR, a new retrieval model, boosts accuracy by combining document retrieval with fine-grained information generation, leading to better understanding and improved localization.

MAPQATOR: a web app that streamlines creation of reproducible geospatial QA datasets, boosting annotation speed by 30x!

OmniEval: Automatic benchmark for evaluating financial RAG systems.

RetroLLM unifies retrieval & generation in LLMs, boosting accuracy and cutting costs.

MedRGB benchmark reveals current LLMs struggle with noisy medical data, emphasizing the need for robust RAG systems in healthcare AI.

M-LongDoc: a new benchmark and retrieval-aware tuning framework revolutionizes multimodal long document understanding, improving model accuracy by 4.6%.

HtmlRAG boosts RAG system accuracy by using HTML, not plain text, to model retrieved knowledge, improving knowledge representation and mitigating LLM hallucination.

GRS-QA: New benchmark dataset reveals LLM reasoning limitations!