1 citations · 1 across the 4 of their papers we have counts for
10 papers
What We are Missing in Multimodal LLM Evaluation?
Po-han Li, Shenghui Chen, Sandeep Chinchali +1
Multimodal large language models (MLLMs) can process diverse inputs, e.g., text, images, audio, and video, and generate textual responses. While their capabilities have advanced ra…
SSR: A Generic Framework for Text-Aided Map Compression for Localization
Mohammad Omama, Po-han Li, Harsh Goel +6
Mapping is crucial in robotics for localization and downstream decision-making. As robots are deployed in ever-broader settings, the maps they rely on continue to increase in size.…
ViSIL: Unified Evaluation of Information Loss in Multimodal Video Captioning
Po-han Li, Shenghui Chen, Ufuk Topcu +1
Multimodal video captioning condenses dense footage into a structured format of keyframes and natural language. By creating a cohesive multimodal summary, this approach anchors gen…
UNCAP: Uncertainty-Guided Neurosymbolic Planning Using Natural Language Communication for Cooperative Autonomous Vehicles
Neel P. Bhatt, Po-han Li, Kushagra Gupta +7
Safe large-scale coordination of multiple cooperative connected autonomous vehicles (CAVs) hinges on communication that is both efficient and interpretable. Existing approaches eit…
Fair Resource Allocation for Fleet Intelligence
Oguzhan Baser, Kaan Kale, Po-han Li +1
Resource allocation is crucial for the performance optimization of cloud-assisted multi-agent intelligence. Traditional methods often overlook agents' diverse computational capabil…
Dense Dynamics-Aware Reward Synthesis: Integrating Prior Experience with Demonstrations
Cevahir Koprulu, Po-han Li, Tianyu Qiu +5
Many continuous control problems can be formulated as sparse-reward reinforcement learning (RL) tasks. In principle, online RL methods can automatically explore the state space to…