17 citations · 30 across the 6 of their papers we have counts for
6 papers
Gemini Robotics: Bringing AI into the Physical World
Gemini Robotics Team, Saminda Abeyruwan, Joshua Ainslie +115
Recent advancements in large multimodal models have led to the emergence of remarkable generalist capabilities in digital domains, yet their translation to physical agents such as…
Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation
Adam Fisch, Joshua Maynez, R. Alex Hofer +3
Prediction-powered inference (PPI) is a method that improves statistical estimates based on limited human-labeled data. PPI achieves this by combining small amounts of human-labele…
Bayesian Prediction-Powered Inference
R. Alex Hofer, Joshua Maynez, Bhuwan Dhingra +3
Prediction-powered inference (PPI) is a method that improves statistical estimates based on limited human-labeled data. Specifically, PPI methods provide tighter confidence interva…
Scalable Neural Methods for Reasoning With a Symbolic Knowledge Base
William W. Cohen, Haitian Sun, R. Alex Hofer +1
We describe a novel way of representing a symbolic knowledge base (KB) called a sparse-matrix reified KB. This representation enables neural modules that are fully differentiable,…
Differentiable Representations For Multihop Inference Rules
William W. Cohen, Haitian Sun, R. Alex Hofer +1
We present efficient differentiable implementations of second-order multi-hop reasoning using a large symbolic knowledge base (KB). We introduce a new operation which can be used t…
Neural Query Language: A Knowledge Base Query Language for Tensorflow
William W. Cohen, Matthew Siegler, Alex Hofer
Large knowledge bases (KBs) are useful for many AI tasks, but are difficult to integrate into modern gradient-based learning systems. Here we describe a framework for accessing sof…