Summary of Improving Black-box Robustness with In-context Rewriting, by Kyle O’brien et al.
Improving Black-box Robustness with In-Context Rewritingby Kyle O'Brien, Nathan Ng, Isha Puri, Jorge Mendez, Hamid…
Improving Black-box Robustness with In-Context Rewritingby Kyle O'Brien, Nathan Ng, Isha Puri, Jorge Mendez, Hamid…
One Train for Two Tasks: An Encrypted Traffic Classification Framework Using Supervised Contrastive Learningby Haozhen…
Understanding the Training Speedup from Sampling with Approximate Lossesby Rudrajit Das, Xi Chen, Bertram Ieong,…
Efficient Stagewise Pretraining via Progressive Subnetworksby Abhishek Panigrahi, Nikunj Saunshi, Kaifeng Lyu, Sobhan Miryoosefi, Sashank…
Classifying spam emails using agglomerative hierarchical clustering and a topic-based approachby F. Janez-Martino, R. Alaiz-Rodriguez,…
CEHR-GPT: Generating Electronic Health Records with Chronological Patient Timelinesby Chao Pang, Xinzhuo Jiang, Nishanth Parameshwar…
LegalLens: Leveraging LLMs for Legal Violation Identification in Unstructured Textby Dor Bernsohn, Gil Semo, Yaron…
The Use of a Large Language Model for Cyberbullying Detectionby Bayode Ogunleye, Babitha DharmarajFirst submitted…
Identifying Reasons for Contraceptive Switching from Real-World Data Using Large Language Modelsby Brenda Y. Miao,…
Stanceosaurus 2.0: Classifying Stance Towards Russian and Spanish Misinformationby Anton Lavrouk, Ian Ligon, Tarek Naous,…