52 citations · 53 across the 4 of their papers we have counts for
4 papers
Decoupling Vision and Language: Codebook Anchored Visual Adaptation
Jason Wu, Tianchen Zhao, Chang Liu +7
Large Vision-Language Models (LVLMs) use their vision encoders to translate images into representations for downstream reasoning, but the encoders often underperform in domain-spec…
Benchmarking Low-Shot Robustness to Natural Distribution Shifts
Aaditya Singh, Kartik Sarangmath, Prithvijit Chattopadhyay +1
Robustness to natural distribution shifts has seen remarkable progress thanks to recent pre-training strategies combined with better fine-tuning methods. However, such fine-tuning…
Know your audience: specializing grounded language models with listener subtraction
Aaditya K. Singh, David Ding, Andrew Saxe +2
Effective communication requires adapting to the idiosyncrasies of each communicative context--such as the common ground shared with each partner. Humans demonstrate this ability t…
Data Distributional Properties Drive Emergent In-Context Learning in Transformers
Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen +5
Large transformer-based models are able to perform in-context few-shot learning, without being explicitly trained for it. This observation raises the question: what aspects of the…