Technical Report
Technical reports detail the development and evaluation of novel methods and systems across diverse scientific domains. Current research focuses on improving the performance and efficiency of large language models (LLMs), including advancements in model architectures like transformers and the use of techniques such as retrieval-augmented generation and knowledge distillation. These improvements are driving progress in areas such as autonomous programming, biomolecular structure prediction, and AI-powered solutions for industrial applications, ultimately accelerating scientific discovery and technological innovation.
Papers
PROMISE: A Framework for Developing Complex Conversational Interactions (Technical Report)
Wenyuan Wu, Jasmin Heierli, Max Meisterhans, Adrian Moser, Andri Färber, Mateusz Dolata, Elena Gavagnin, Alexandre de Spindler, Gerhard Schwabe
Kandinsky 3.0 Technical Report
Vladimir Arkhipkin, Andrei Filatov, Viacheslav Vasilev, Anastasia Maltseva, Said Azizov, Igor Pavlov, Julia Agafonova, Andrey Kuznetsov, Denis Dimitrov
Technical Report for Argoverse Challenges on 4D Occupancy Forecasting
Pengfei Zheng, Kanokphan Lertniphonphan, Feng Chen, Siwei Chen, Bingchuan Sun, Jun Xie, Zhepeng Wang
Technical Report for Argoverse Challenges on Unified Sensor-based Detection, Tracking, and Forecasting
Zhepeng Wang, Feng Chen, Kanokphan Lertniphonphan, Siwei Chen, Jinyao Bao, Pengfei Zheng, Jinbao Zhang, Kaer Huang, Tao Zhang