Summary of Quo Vadis, Motion Generation? From Large Language Models to Large Motion Models, by Ye Wang et al.
Quo Vadis, Motion Generation? From Large Language Models to Large Motion Modelsby Ye Wang, Sipeng…
Summary of Scalable Frame-based Construction Of Sociocultural Normbases For Socially-aware Dialogues, by Shilin Qu et al.
Scalable Frame-based Construction of Sociocultural NormBases for Socially-Aware Dialoguesby Shilin Qu, Weiqing Wang, Xin Zhou,…
Summary of Candoit: Causal Discovery with Observational and Interventional Data From Time-series, by Luca Castri et al.
CAnDOIT: Causal Discovery with Observational and Interventional Data from Time-Seriesby Luca Castri, Sariah Mghames, Marc…
Summary of Training Language Models on Synthetic Edit Sequences Improves Code Synthesis, by Ulyana Piterbarg and Lerrel Pinto and Rob Fergus
Training Language Models on Synthetic Edit Sequences Improves Code Synthesisby Ulyana Piterbarg, Lerrel Pinto, Rob…
Summary of Efficient Learning Of Differential Network in Multi-source Non-paranormal Graphical Models, by Mojtaba Nikahd and Seyed Abolfazl Motahari
Efficient learning of differential network in multi-source non-paranormal graphical modelsby Mojtaba Nikahd, Seyed Abolfazl MotahariFirst…
Summary of Pfguard: a Generative Framework with Privacy and Fairness Safeguards, by Soyeon Kim et al.
PFGuard: A Generative Framework with Privacy and Fairness Safeguardsby Soyeon Kim, Yuji Roh, Geon Heo,…
Summary of Active Learning Of Deep Neural Networks Via Gradient-free Cutting Planes, by Erica Zhang et al.
Active Learning of Deep Neural Networks via Gradient-Free Cutting Planesby Erica Zhang, Fangzhao Zhang, Mert…
Summary of Deep Generative Modeling For Identification Of Noisy, Non-stationary Dynamical Systems, by Doris Voina and Steven Brunton and J. Nathan Kutz
Deep Generative Modeling for Identification of Noisy, Non-Stationary Dynamical Systemsby Doris Voina, Steven Brunton, J.…
Summary of Towards a Theoretical Understanding Of Synthetic Data in Llm Post-training: a Reverse-bottleneck Perspective, by Zeyu Gan et al.
Towards a Theoretical Understanding of Synthetic Data in LLM Post-Training: A Reverse-Bottleneck Perspectiveby Zeyu Gan,…
Summary of Forte : Finding Outliers with Representation Typicality Estimation, by Debargha Ganguly et al.
Forte : Finding Outliers with Representation Typicality Estimationby Debargha Ganguly, Warren Morningstar, Andrew Yu, Vipin…