Summary of Towards Sim-to-real Industrial Parts Classification with Synthetic Dataset, by Xiaomeng Zhu et al.
Towards Sim-to-Real Industrial Parts Classification with Synthetic Datasetby Xiaomeng Zhu, Talha Bilal, Pär Mårtensson, Lars…
Summary of Balanced Mixed-type Tabular Data Synthesis with Diffusion Models, by Zeyu Yang et al.
Balanced Mixed-Type Tabular Data Synthesis with Diffusion Modelsby Zeyu Yang, Han Yu, Peikun Guo, Khadija…
Summary of Sqbc: Active Learning Using Llm-generated Synthetic Data For Stance Detection in Online Political Discussions, by Stefan Sylvius Wagner et al.
SQBC: Active Learning using LLM-Generated Synthetic Data for Stance Detection in Online Political Discussionsby Stefan…
Summary of Gansemble For Small and Imbalanced Data Sets: a Baseline For Synthetic Microplastics Data, by Daniel Platnick et al.
GANsemble for Small and Imbalanced Data Sets: A Baseline for Synthetic Microplastics Databy Daniel Platnick,…
Summary of What Needs to Go Right For An Induction Head? a Mechanistic Study Of In-context Learning Circuits and Their Formation, by Aaditya K. Singh et al.
What needs to go right for an induction head? A mechanistic study of in-context learning…
Summary of Feel-good Thompson Sampling For Contextual Dueling Bandits, by Xuheng Li et al.
Feel-Good Thompson Sampling for Contextual Dueling Banditsby Xuheng Li, Heyang Zhao, Quanquan GuFirst submitted to…
Summary of Codeclm: Aligning Language Models with Tailored Synthetic Data, by Zifeng Wang et al.
CodecLM: Aligning Language Models with Tailored Synthetic Databy Zifeng Wang, Chun-Liang Li, Vincent Perot, Long…
Summary of How Bad Is Training on Synthetic Data? a Statistical Analysis Of Language Model Collapse, by Mohamed El Amine Seddik et al.
How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapseby Mohamed…
Summary of Faraday: Synthetic Smart Meter Generator For the Smart Grid, by Sheng Chai and Gus Chadney
Faraday: Synthetic Smart Meter Generator for the smart gridby Sheng Chai, Gus ChadneyFirst submitted to…
Summary of Fairm: Learning Invariant Representations For Algorithmic Fairness and Domain Generalization with Minimax Optimality, by Sai Li and Linjun Zhang
FAIRM: Learning invariant representations for algorithmic fairness and domain generalization with minimax optimalityby Sai Li,…