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06/20/2023
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations
Randomized experiments often need to be stopped prematurely due to the t...
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06/01/2023
Did You Read the Instructions? Rethinking the Effectiveness of Task Definitions in Instruction Learning
Large language models (LLMs) have shown impressive performance in follow...
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05/31/2023
Red Teaming Language Model Detectors with Language Models
The prevalence and high capacity of large language models (LLMs) present...
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05/23/2023
Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation
Instruction tuning has emerged to enhance the capabilities of large lang...
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03/06/2023
CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning
Multimodal contrastive pretraining has been used to train multimodal rep...
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10/22/2022
ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation
Adversarial Examples Detection (AED) is a crucial defense technique agai...
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10/26/2021
Highly Scalable Maximum Likelihood and Conjugate Bayesian Inference for ERGMs on Graph Sets with Equivalent Vertices
The exponential family random graph modeling (ERGM) framework provides a...
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04/18/2021
On the Faithfulness Measurements for Model Interpretations
Recent years have witnessed the emergence of a variety of post-hoc inter...
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03/15/2021
Achieve Efficient Position-Heap-based Privacy-Preserving Substring-of-Keyword Query over Cloud
The cloud computing technique, which was initially used to mitigate the ...
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11/23/2020
Bayesian Nonparametric Estimation for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations
Basketball shot location data provide valuable summary information regar...
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10/31/2020
Bayesian Analysis of Static Light Scattering Data for Globular Proteins
Static light scattering is a popular physical chemistry technique that e...
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10/16/2020
Analysis of professional basketball field goal attempts via a Bayesian matrix clustering approach
We propose a Bayesian nonparametric matrix clustering approach to analyz...
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05/12/2020
On the Robustness of Language Encoders against Grammatical Errors
We conduct a thorough study to diagnose the behaviors of pre-trained lan...
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04/17/2020
Kernel-based Approximate Bayesian Inference for Exponential Family Random Graph Models
Bayesian inference for exponential family random graph models (ERGMs) is...
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10/24/2019
Finite Mixtures of ERGMs for Ensembles of Networks
Ensembles of networks arise in many scientific fields, but currently the...
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08/16/2019
Selection of Exponential-Family Random Graph Models via Held-Out Predictive Evaluation (HOPE)
Statistical models for networks with complex dependencies pose particula...
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05/14/2019