New Framework
Recent research focuses on developing versatile frameworks for various tasks, primarily aiming to improve efficiency, reproducibility, and accessibility within their respective domains. These frameworks leverage diverse techniques, including programmatic data generation for LLMs, deep learning architectures for image and audio processing, and reinforcement learning for optimization and automated testing. The resulting advancements enhance the development and evaluation of AI models, improve the reliability of benchmarking processes, and offer new tools for diverse applications ranging from healthcare diagnostics to autonomous vehicle navigation.
Papers
Robots Can Feel: LLM-based Framework for Robot Ethical Reasoning
Artem Lykov, Miguel Altamirano Cabrera, Koffivi Fidèle Gbagbe, Dzmitry Tsetserukou
A Framework of SO(3)-equivariant Non-linear Representation Learning and its Application to Electronic-Structure Hamiltonian Prediction
Shi Yin, Xinyang Pan, Fengyan Wang, Lixin He
Can LLMs Deeply Detect Complex Malicious Queries? A Framework for Jailbreaking via Obfuscating Intent
Shang Shang, Xinqiang Zhao, Zhongjiang Yao, Yepeng Yao, Liya Su, Zijing Fan, Xiaodan Zhang, Zhengwei Jiang
ReinWiFi: A Reinforcement-Learning-Based Framework for the Application-Layer QoS Optimization of WiFi Networks
Qianren Li, Bojie Lv, Yuncong Hong, Rui Wang
A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challenges
ZhengZhao Feng, Rui Wang, TianXing Wang, Mingli Song, Sai Wu, Shuibing He
Detail-Enhancing Framework for Reference-Based Image Super-Resolution
Zihan Wang, Ziliang Xiong, Hongying Tang, Xiaobing Yuan
A Framework for Real-time Safeguarding the Text Generation of Large Language Model
Ximing Dong, Dayi Lin, Shaowei Wang, Ahmed E. Hassan
A Framework to Model ML Engineering Processes
Sergio Morales, Robert Clarisó, Jordi Cabot
Leak Proof CMap; a framework for training and evaluation of cell line agnostic L1000 similarity methods
Steven Shave, Richard Kasprowicz, Abdullah M. Athar, Denise Vlachou, Neil O. Carragher, Cuong Q. Nguyen
A Framework for Learning and Reusing Robotic Skills
Brendan Hertel, Nhu Tran, Meriem Elkoudi, Reza Azadeh
KGValidator: A Framework for Automatic Validation of Knowledge Graph Construction
Jack Boylan, Shashank Mangla, Dominic Thorn, Demian Gholipour Ghalandari, Parsa Ghaffari, Chris Hokamp
SynthEval: A Framework for Detailed Utility and Privacy Evaluation of Tabular Synthetic Data
Anton Danholt Lautrup, Tobias Hyrup, Arthur Zimek, Peter Schneider-Kamp