1 citations · 1 across the 5 of their papers we have counts for
6 papers
Valid Inference with Imperfect Synthetic Data
Yewon Byun, Shantanu Gupta, Zachary C. Lipton +2
Predictions and generations from large language models are increasingly being explored as an aid in limited data regimes, such as in computational social science and human subjects…
Online Data Collection for Efficient Semiparametric Inference
Shantanu Gupta, Zachary C. Lipton, David Childers
While many works have studied statistical data fusion, they typically assume that the various datasets are given in advance. However, in practice, estimation requires difficult dat…
Failure Modes of LLMs for Causal Reasoning on Narratives
Khurram Yamin, Shantanu Gupta, Gaurav R. Ghosal +2
The ability to robustly identify causal relationships is essential for autonomous decision-making and adaptation to novel scenarios. However, accurately inferring causal structure…
A Unified Causal Framework for Auditing Recommender Systems for Ethical Concerns
Vibhhu Sharma, Shantanu Gupta, Nil-Jana Akpinar +2
As recommender systems become widely deployed in different domains, they increasingly influence their users' beliefs and preferences. Auditing recommender systems is crucial as it…
Learned Causal Method Prediction
Shantanu Gupta, Cheng Zhang, Agrin Hilmkil
For a given causal question, it is important to efficiently decide which causal inference method to use for a given dataset. This is challenging because causal methods typically re…
Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs
Jacqueline Maasch, Weishen Pan, Shantanu Gupta +3
Causal discovery is crucial for causal inference in observational studies, as it can enable the identification of valid adjustment sets (VAS) for unbiased effect estimation. Howeve…