Search Results for author:
Found 14 papers, 9 papers with code
Context versus Prior Knowledge in Language Models
To answer a question, language models often need to integrate prior knowledge learned during pretraining and new information presented in context.
The AL$\ell_0$CORE Tensor Decomposition for Sparse Count Data
This paper introduces AL$\ell_0$CORE, a new form of probabilistic non-negative tensor decomposition.
Measurement in the Age of LLMs: An Application to Ideological Scaling
Much of social science is centered around terms like ``ideology'' or ``power'', which generally elude precise definition, and whose contextual meanings are trapped in surrounding language.
The Ordered Matrix Dirichlet for State-Space Models
For discrete data, SSMs commonly do so through a state-to-action emission matrix and a state-to-state transition matrix.
An Ordinal Latent Variable Model of Conflict Intensity
It is based only on the action category ("what") and disregards the subject ("who") and object ("to whom") of an event, as well as contextual information, like associated casualty count, that should contribute to the perception of an event's "intensity".
Doubly Non-Central Beta Matrix Factorization for DNA Methylation Data
We present a new non-negative matrix factorization model for $(0, 1)$ bounded-support data based on the doubly non-central beta (DNCB) distribution, a generalization of the beta distribution.
Poisson-Randomized Gamma Dynamical Systems
This paper presents the Poisson-randomized gamma dynamical system (PRGDS), a model for sequentially observed count tensors that encodes a strong inductive bias toward sparsity and burstiness.
Locally Private Bayesian Inference for Count Models
We present a general method for privacy-preserving Bayesian inference in Poisson factorization, a broad class of models that includes some of the most widely used models in the social sciences.
Poisson--Gamma Dynamical Systems
We introduce a new dynamical system for sequentially observed multivariate count data.
Poisson-Gamma dynamical systems
This paper presents a dynamical system based on the Poisson-Gamma construction for sequentially observed multivariate count data.
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations
We introduce Bayesian Poisson Tucker decomposition (BPTD) for modeling country--country interaction event data.
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts
We demonstrate that our model's predictive performance is better than that of standard non-negative tensor factorization methods.
Inferring Multilateral Relations from Dynamic Pairwise Interactions
Correlations between anomalous activity patterns can yield pertinent information about complex social processes: a significant deviation from normal behavior, exhibited simultaneously by multiple pairs of actors, provides evidence for some underlying relationship involving those pairs---i. e., a multilateral relation.
International Multicultural Name Matching Competition: Design, Execution, Results, and Lessons Learned
This paper describes different aspects of an open competition to evaluate multicultural name matching software, including the contest design, development of the test data, different phases of the competition, behavior of the participating teams, results of the competition, and lessons learned throughout.
