Detecting and Approximating Redundant Computational Blocks in Neural Networksby Irene Cannistraci, Emanuele Rodolà, Bastian RieckFirst…
Failure-Proof Non-Contrastive Self-Supervised Learningby Emanuele Sansone, Tim Lebailly, Tinne TuytelaarsFirst submitted to arxiv on: 7…
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Samplingby Jasmine Bayrooti, Carl Henrik Ek, Amanda ProrokFirst…
Contrastive Learning to Improve Retrieval for Real-world Fact Checkingby Aniruddh Sriram, Fangyuan Xu, Eunsol Choi,…
Adversarial Multi-Agent Evaluation of Large Language Models through Iterative Debatesby Chaithanya Bandi, Abir HarrasseFirst submitted…
Federated Learning Nodes Can Reconstruct Peers’ Image Databy Ethan Wilson, Kai Yue, Chau-Wai Wong, Huaiyu…
On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoningby…
Towards Measuring Goal-Directedness in AI Systemsby Dylan Xu, Juan-Pablo RiveraFirst submitted to arxiv on: 7…
Deeper Insights Without Updates: The Power of In-Context Learning Over Fine-Tuningby Qingyu Yin, Xuzheng He,…
A Clifford Algebraic Approach to E(n)-Equivariant High-order Graph Neural Networksby Viet-Hoang Tran, Thieu N. Vo,…