3 papers
cs.CV2026
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…
physics.geo-ph2025
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…
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…