Summary of Enhancing Risk Assessment in Transformers with Loss-at-risk Functions, by Jinghan Zhang et al.
Enhancing Risk Assessment in Transformers with Loss-at-Risk Functionsby Jinghan Zhang, Henry Xie, Xinhao Zhang, Kunpeng…
Summary of Grouped Discrete Representation For Object-centric Learning, by Rongzhen Zhao et al.
Grouped Discrete Representation for Object-Centric Learningby Rongzhen Zhao, Vivienne Wang, Juho Kannala, Joni PajarinenFirst submitted…
Summary of Sparsing Law: Towards Large Language Models with Greater Activation Sparsity, by Yuqi Luo et al.
Sparsing Law: Towards Large Language Models with Greater Activation Sparsityby Yuqi Luo, Chenyang Song, Xu…
Summary of Training Compute-optimal Protein Language Models, by Xingyi Cheng et al.
Training Compute-Optimal Protein Language Modelsby Xingyi Cheng, Bo Chen, Pan Li, Jing Gong, Jie Tang,…
Summary of Provably Transformers Harness Multi-concept Word Semantics For Efficient In-context Learning, by Dake Bu et al.
Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learningby Dake Bu, Wei Huang, Andi…
Summary of Sira: Scalable Inter-frame Relation and Association For Radar Perception, by Ryoma Yataka et al.
SIRA: Scalable Inter-frame Relation and Association for Radar Perceptionby Ryoma Yataka, Pu Perry Wang, Petros…
Summary of Amortized Bayesian Experimental Design For Decision-making, by Daolang Huang et al.
Amortized Bayesian Experimental Design for Decision-Makingby Daolang Huang, Yujia Guo, Luigi Acerbi, Samuel KaskiFirst submitted…
Summary of Ask, and It Shall Be Given: on the Turing Completeness Of Prompting, by Ruizhong Qiu et al.
Ask, and it shall be given: On the Turing completeness of promptingby Ruizhong Qiu, Zhe…
Summary of Show, Don’t Tell: Learning Reward Machines From Demonstrations For Reinforcement Learning-based Cardiac Pacemaker Synthesis, by John Komp et al.
Show, Don’t Tell: Learning Reward Machines from Demonstrations for Reinforcement Learning-Based Cardiac Pacemaker Synthesisby John…
Summary of Shrinking the Giant : Quasi-weightless Transformers For Low Energy Inference, by Shashank Nag et al.
Shrinking the Giant : Quasi-Weightless Transformers for Low Energy Inferenceby Shashank Nag, Alan T. L.…