Christine Herlihy
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On Overcoming Miscalibrated Conversational Priors in LLM-based Chatbots
We explore the use of Large Language Model (LLM-based) chatbots to power recommender systems. We observe that the chatbots respond …
Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan
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A structured regression approach for evaluating model performance across intersectional subgroups
Disaggregated evaluation is a central task in AI fairness assessment, with the goal to measure an AI system’s performance across …
Christine Herlihy, Kimberly Truong, Alexandra Chouldechova, Miroslav Dudík
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Data Contamination Through the Lens of Time
Recent claims about the impressive abilities of large language models (LLMs) are often supported by evaluating publicly available …
Manley Roberts, Himanshu Thakur, Christine Herlihy, Colin White, Samuel Dooley
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Networked Restless Bandits with Positive Externalities
Restless multi-armed bandits are often used to model budget-constrained resource allocation tasks where receipt of the resource is …
Christine Herlihy, John P. Dickerson
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Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting
Restless and collapsing bandits are often used to model budget-constrained resource allocation in settings where arms have …
Christine Herlihy, Aviva Prins, Aravind Srinivasan, John Dickerson
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MedNLI Is Not Immune: Natural Language Inference Artifacts in the Clinical Domain
Crowdworker-constructed natural language inference (NLI) datasets have been found to contain statistical artifacts associated with the …
Christine Herlihy, Rachel Rudinger
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A Compositional Framework for Scientific Model Augmentation
Scientists construct and analyze computational models to understand the world. That understanding comes from efforts to augment, …
Micah Halter, Christine Herlihy, James Fairbanks
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