3 papers
cs.CV2025
Dissecting Embodied Abilities in Multimodal Language Models through Skill-level Evaluation and Diagnosis
Yu Qi, Haibo Zhao, Ziyu Guo +17
Understanding the capability bottlenecks of embodied multimodal large language models (MLLMs) is crucial for improving embodied agents. However, existing embodied benchmarks mainly…
cs.LG2024
Fast Inference for Augmented Large Language Models
Rana Shahout, Cong Liang, Shiji Xin +4
Augmented Large Language Models (LLMs) enhance the capabilities of standalone LLMs by integrating external data sources through API calls. In interactive LLM applications, efficien…
physics.geo-ph2024
GlobalTomo: A global dataset for physics-ML seismic wavefield modeling and FWI
Shiqian Li, Zhi Li, Zhancun Mu +6
Global seismic tomography, taking advantage of seismic waves from natural earthquakes, provides essential insights into the earth's internal dynamics. Advanced Full-waveform Invers…