8 papers
Rushes: A Human Preference Dataset for Pluralistic Alignment
Michael Xu, Jorge Leandro, Sudha Rao +5
We introduce Rushes, a dataset and benchmark for studying revealed human engagement preferences in interactive narrative environments. Rushes is collected through a game interface…
City Navigation in the Wild: Exploring Emergent Navigation from Web-Scale Knowledge in MLLMs
Dwip Dalal, Utkarsh Mishra, Narendra Ahuja +1
Leveraging multimodal large language models (MLLMs) to develop embodied agents offers significant promise for addressing complex real-world tasks. However, current evaluation bench…
GenZ: Foundational models as latent variable generators within traditional statistical models
Marko Jojic, Nebojsa Jojic
We present GenZ, a hybrid model that bridges foundational models and statistical modeling through interpretable semantic features. While large language models possess broad domain…
Learning Informative Attention Weights for Person Re-Identification
Yancheng Wang, Nebojsa Jojic, Yingzhen Yang
Attention mechanisms have been widely used in deep learning, and recent efforts have been devoted to incorporating attention modules into deep neural networks (DNNs) for person Re-…
Echoes in AI: Quantifying lack of plot diversity in LLM outputs
Weijia Xu, Nebojsa Jojic, Sudha Rao +2
With rapid advances in large language models (LLMs), there has been an increasing application of LLMs in creative content ideation and generation. A critical question emerges: can…
fLSA: Learning Semantic Structures in Document Collections Using Foundation Models
Weijia Xu, Nebojsa Jojic, Nicolas Le Roux
Humans can learn to solve new tasks by inducing high-level strategies from example solutions to similar problems and then adapting these strategies to solve unseen problems. Can we…