Summary of Transgpt: Multi-modal Generative Pre-trained Transformer For Transportation, by Peng Wang et al.
TransGPT: Multi-modal Generative Pre-trained Transformer for Transportationby Peng Wang, Xiang Wei, Fangxu Hu, Wenjuan HanFirst…
Summary of Aya Dataset: An Open-access Collection For Multilingual Instruction Tuning, by Shivalika Singh et al.
Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuningby Shivalika Singh, Freddie Vargus, Daniel Dsouza,…
Summary of Efficient Models For the Detection Of Hate, Abuse and Profanity, by Christoph Tillmann et al.
Efficient Models for the Detection of Hate, Abuse and Profanityby Christoph Tillmann, Aashka Trivedi, Bishwaranjan…
Summary of Autoaugment Is What You Need: Enhancing Rule-based Augmentation Methods in Low-resource Regimes, by Juhwan Choi et al.
AutoAugment Is What You Need: Enhancing Rule-based Augmentation Methods in Low-resource Regimesby Juhwan Choi, Kyohoon…
Summary of Softeda: Rethinking Rule-based Data Augmentation with Soft Labels, by Juhwan Choi et al.
SoftEDA: Rethinking Rule-Based Data Augmentation with Soft Labelsby Juhwan Choi, Kyohoon Jin, Junho Lee, Sangmin…
Summary of Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-source Llms, by Simone Balloccu et al.
Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMsby Simone Balloccu, Patrícia Schmidtová,…
Summary of Partially Recentralization Softmax Loss For Vision-language Models Robustness, by Hao Wang et al.
Partially Recentralization Softmax Loss for Vision-Language Models Robustnessby Hao Wang, Jinzhe Jiang, Xin Zhang, Chen…
Summary of Are Machines Better at Complex Reasoning? Unveiling Human-machine Inference Gaps in Entailment Verification, by Soumya Sanyal et al.
Are Machines Better at Complex Reasoning? Unveiling Human-Machine Inference Gaps in Entailment Verificationby Soumya Sanyal,…
Summary of “what’s My Model Inside Of?”: Exploring the Role Of Environments For Grounded Natural Language Understanding, by Ronen Tamari
“What’s my model inside of?”: Exploring the role of environments for grounded natural language understandingby…
Summary of C-rag: Certified Generation Risks For Retrieval-augmented Language Models, by Mintong Kang et al.
C-RAG: Certified Generation Risks for Retrieval-Augmented Language Modelsby Mintong Kang, Nezihe Merve Gürel, Ning Yu,…