Summary of Upcycling Instruction Tuning From Dense to Mixture-of-experts Via Parameter Merging, by Tingfeng Hui et al.
Upcycling Instruction Tuning from Dense to Mixture-of-Experts via Parameter Mergingby Tingfeng Hui, Zhenyu Zhang, Shuohuan…
Upcycling Instruction Tuning from Dense to Mixture-of-Experts via Parameter Mergingby Tingfeng Hui, Zhenyu Zhang, Shuohuan…
Automated Red Teaming with GOAT: the Generative Offensive Agent Testerby Maya Pavlova, Erik Brinkman, Krithika…
DRUPI: Dataset Reduction Using Privileged Informationby Shaobo Wang, Yantai Yang, Shuaiyu Zhang, Chenghao Sun, Weiya…
On Using Certified Training towards Empirical Robustnessby Alessandro De Palma, Serge Durand, Zakaria Chihani, François…
Does Graph Prompt Work? A Data Operation Perspective with Theoretical Analysisby Qunzhong Wang, Xiangguo Sun,…
Fira: Can We Achieve Full-rank Training of LLMs Under Low-rank Constraint?by Xi Chen, Kaituo Feng,…
Moral Alignment for LLM Agentsby Elizaveta Tennant, Stephen Hailes, Mirco MusolesiFirst submitted to arxiv on:…
On The Adaptation of Unlimiformer for Decoder-Only Transformersby Kian Ahrabian, Alon Benhaim, Barun Patra, Jay…
Stable Offline Value Function Learning with Bisimulation-based Representationsby Brahma S. Pavse, Yudong Chen, Qiaomin Xie,…
shapiq: Shapley Interactions for Machine Learningby Maximilian Muschalik, Hubert Baniecki, Fabian Fumagalli, Patrick Kolpaczki, Barbara…