56 citations · 176 across the 29 of their papers we have counts for
16 papers · 1 filter
Generative World Explorer
Taiming Lu, Tianmin Shu, Alan Yuille +2
Planning with partial observation is a central challenge in embodied AI. A majority of prior works have tackled this challenge by developing agents that physically explore their en…
Benchmarking Language Model Creativity: A Case Study on Code Generation
Yining Lu, Dixuan Wang, Tianjian Li +4
As LLMs become increasingly prevalent, it is interesting to consider how ``creative'' these models can be. From cognitive science, creativity consists of at least two key character…
Rel-A.I.: An Interaction-Centered Approach To Measuring Human-LM Reliance
Kaitlyn Zhou, Jena D. Hwang, Xiang Ren +3
The ability to communicate uncertainty, risk, and limitation is crucial for the safety of large language models. However, current evaluations of these abilities rely on simple cali…
WorldAPIs: The World Is Worth How Many APIs? A Thought Experiment
Jiefu Ou, Arda Uzunoglu, Benjamin Van Durme +1
AI systems make decisions in physical environments through primitive actions or affordances that are accessed via API calls. While deploying AI agents in the real world involves nu…
Core: Robust Factual Precision with Informative Sub-Claim Identification
Zhengping Jiang, Jingyu Zhang, Nathaniel Weir +6
Hallucinations pose a challenge to the application of large language models (LLMs) thereby motivating the development of metrics to evaluate factual precision. We observe that popu…
Efficient Large Multi-modal Models via Visual Context Compression
Jieneng Chen, Luoxin Ye, Ju He +3
While significant advancements have been made in compressed representations for text embeddings in large language models (LLMs), the compression of visual tokens in multi-modal LLM…