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Found 8 papers, 4 papers with code
A novel interface for adversarial trivia question-writing
A critical component when developing question-answering AIs is an adversarial dataset that challenges models to adapt to the complex syntax and reasoning underlying our natural language.
Self-supervised Activity Representation Learning with Incremental Data: An Empirical Study
In the context of mobile sensing environments, various sensors on mobile devices continually generate a vast amount of data.
Language models enable zero-shot prediction of the effects of mutations on protein function
Modeling the effect of sequence variation on function is a fundamental problem for understanding and designing proteins.
Dialogue Object Search
To this end, we introduce a new task, dialogue object search: A robot is tasked to search for a target object (e. g. fork) in a human environment (e. g., kitchen), while engaging in a "video call" with a remote human who has additional but inexact knowledge about the target's location.
Forest Fire Clustering for Single-cell Sequencing with Iterative Label Propagation and Parallelized Monte Carlo Simulation
Here, we introduce Forest Fire Clustering, an efficient and interpretable method for cell-type discovery from single-cell data.
MSA Transformer
Unsupervised protein language models trained across millions of diverse sequences learn structure and function of proteins.
Neural Potts Model
We propose the Neural Potts Model objective as an amortized optimization problem.
TypeWriter: Neural Type Prediction with Search-based Validation
Unfortunately, static type inference for dynamic languages is inherently limited, while probabilistic approaches suffer from imprecision.
Software Engineering
