Summary of Authorship Verification Based on the Likelihood Ratio Of Grammar Models, by Andrea Nini et al.
Authorship Verification based on the Likelihood Ratio of Grammar Modelsby Andrea Nini, Oren Halvani, Lukas…
Summary of Monitoring Ai-modified Content at Scale: a Case Study on the Impact Of Chatgpt on Ai Conference Peer Reviews, by Weixin Liang et al.
Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI…
Summary of Spatial Clustering Approach For Vessel Path Identification, by Mohamed Abuella et al.
Spatial Clustering Approach for Vessel Path Identificationby Mohamed Abuella, M. Amine Atoui, Slawomir Nowaczyk, Simon…
Summary of Learning to Decode Collaboratively with Multiple Language Models, by Shannon Zejiang Shen et al.
Learning to Decode Collaboratively with Multiple Language Modelsby Shannon Zejiang Shen, Hunter Lang, Bailin Wang,…
Summary of Error Bounds For Particle Gradient Descent, and Extensions Of the Log-sobolev and Talagrand Inequalities, by Rocco Caprio et al.
Error bounds for particle gradient descent, and extensions of the log-Sobolev and Talagrand inequalitiesby Rocco…
Summary of Approximations to the Fisher Information Metric Of Deep Generative Models For Out-of-distribution Detection, by Sam Dauncey et al.
Approximations to the Fisher Information Metric of Deep Generative Models for Out-Of-Distribution Detectionby Sam Dauncey,…
Summary of Can a Confident Prior Replace a Cold Posterior?, by Martin Marek et al.
Can a Confident Prior Replace a Cold Posterior?by Martin Marek, Brooks Paige, Pavel IzmailovFirst submitted…
Summary of Trained Random Forests Completely Reveal Your Dataset, by Julien Ferry et al.
Trained Random Forests Completely Reveal your Datasetby Julien Ferry, Ricardo Fukasawa, Timothée Pascal, Thibaut VidalFirst…
Summary of Inferring Dynamic Networks From Marginals with Iterative Proportional Fitting, by Serina Chang et al.
Inferring Dynamic Networks from Marginals with Iterative Proportional Fittingby Serina Chang, Frederic Koehler, Zhaonan Qu,…
Summary of Imagine, Initialize, and Explore: An Effective Exploration Method in Multi-agent Reinforcement Learning, by Zeyang Liu et al.
Imagine, Initialize, and Explore: An Effective Exploration Method in Multi-Agent Reinforcement Learningby Zeyang Liu, Lipeng…