most citedMoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks

10 citations · 11 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2023

Machine Translation for Nko: Tools, Corpora and Baseline Results

Moussa Koulako Bala Doumbouya, Baba Mamadi Diané, Solo Farabado Cissé +9

Currently, there is no usable machine translation system for Nko, a language spoken by tens of millions of people across multiple West African countries, which holds significant cu…

cs.LG2023

Variational Temporal IRT: Fast, Accurate, and Explainable Inference of Dynamic Learner Proficiency

Yunsung Kim, Sreechan Sankaranarayanan, Chris Piech +1

Dynamic Item Response Models extend the standard Item Response Theory (IRT) to capture temporal dynamics in learner ability. While these models have the potential to allow instruct…

cs.CL202310 cited

MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks

Allen Nie, Yuhui Zhang, Atharva Amdekar +3

Human commonsense understanding of the physical and social world is organized around intuitive theories. These theories support making causal and moral judgments. When something ba…

cs.LG2023

BanditPAM++: Faster -medoids Clustering

Mo Tiwari, Ryan Kang, Donghyun Lee +4

Clustering is a fundamental task in data science with wide-ranging applications. In -medoids clustering, cluster centers must be actual datapoints and arbitrary distance metrics…

cs.CL20231 cited

The BEA 2023 Shared Task on Generating AI Teacher Responses in Educational Dialogues

Anaïs Tack, Ekaterina Kochmar, Zheng Yuan +2

This paper describes the results of the first shared task on the generation of teacher responses in educational dialogues. The goal of the task was to benchmark the ability of gene…

cs.LG2023

Bayesian Decision Trees via Tractable Priors and Probabilistic Context-Free Grammars

Colin Sullivan, Mo Tiwari, Sebastian Thrun +1

Decision Trees are some of the most popular machine learning models today due to their out-of-the-box performance and interpretability. Often, Decision Trees models are constructed…