42 citations · 158 across the 42 of their papers we have counts for
20 papers · 1 filter
Explore Theory of Mind: Program-guided adversarial data generation for theory of mind reasoning
Melanie Sclar, Jane Yu, Maryam Fazel-Zarandi +4
Do large language models (LLMs) have theory of mind? A plethora of papers and benchmarks have been introduced to evaluate if current models have been able to develop this key abili…
Gradient Localization Improves Lifelong Pretraining of Language Models
Jared Fernandez, Yonatan Bisk, Emma Strubell
Large Language Models (LLMs) trained on web-scale text corpora have been shown to capture world knowledge in their parameters. However, the mechanism by which language models store…
Hardware Scaling Trends and Diminishing Returns in Large-Scale Distributed Training
Jared Fernandez, Luca Wehrstedt, Leonid Shamis +5
Dramatic increases in the capabilities of neural network models in recent years are driven by scaling model size, training data, and corresponding computational resources. To devel…
ANAVI: Audio Noise Awareness using Visuals of Indoor environments for NAVIgation
Vidhi Jain, Rishi Veerapaneni, Yonatan Bisk
We propose Audio Noise Awareness using Visuals of Indoors for NAVIgation for quieter robot path planning. While humans are naturally aware of the noise they make and its impact on…
MotIF: Motion Instruction Fine-tuning
Minyoung Hwang, Joey Hejna, Dorsa Sadigh +1
While success in many robotics tasks can be determined by only observing the final state and how it differs from the initial state - e.g., if an apple is picked up - many tasks req…
Embodied-RAG: General Non-parametric Embodied Memory for Retrieval and Generation
Quanting Xie, So Yeon Min, Pengliang Ji +7
There is no limit to how much a robot might explore and learn, but all of that knowledge needs to be searchable and actionable. Within language research, retrieval augmented genera…