4 papers
Can MLLMs "Read" What is Missing?
Jindi Guo, Chaozheng Huang, Xi Fang
We introduce MMTR-Bench, a benchmark designed to evaluate the intrinsic ability of Multimodal Large Language Models (MLLMs) to reconstruct masked text directly from visual context.…
OmniScience: A Large-scale Multi-modal Dataset for Scientific Image Understanding
Haoyi Tao, Chaozheng Huang, Nan Wang +4
Multimodal Large Language Models demonstrate strong performance on natural image understanding, yet exhibit limited capability in interpreting scientific images, including but not…
RxnBench: A Multimodal Benchmark for Evaluating Large Language Models on Chemical Reaction Understanding from Scientific Literature
Hanzheng Li, Xi Fang, Yixuan Li +9
The integration of Multimodal Large Language Models (MLLMs) into chemistry promises to revolutionize scientific discovery, yet their ability to comprehend the dense, graphical lang…
Uni-Parser Technical Report
Xi Fang, Haoyi Tao, Shuwen Yang +8
This technical report introduces Uni-Parser, an industrial-grade document parsing engine tailored for scientific literature and patents, delivering high throughput, robust accuracy…