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Found 7 papers, 2 papers with code
Does Machine Learning Amplify Pricing Errors in the Housing Market? -- The Economics of Machine Learning Feedback Loops
In this work, we develop an analytical model of machine learning feedback loops in the context of the housing market.
Expanding Knowledge Graphs with Humans in the Loop
Concretely, given a knowledge graph, our method predicts the "parents" of new concepts to be added to this graph for further verification by human experts.
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond
A fundamental goal of scientific research is to learn about causal relationships.
Uncovering Latent Biases in Text: Method and Application to Peer Review
In this work, we introduce a novel framework to quantify bias in text caused by the visibility of subgroup membership indicators.
Detecting Attackable Sentences in Arguments
Finding attackable sentences in an argument is the first step toward successful refutation in argumentation.
Influence via Ethos: On the Persuasive Power of Reputation in Deliberation Online
Deliberation among individuals online plays a key role in shaping the opinions that drive votes, purchases, donations and other critical offline behavior.
