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
A framework for conditional diffusion modelling with applications in motif scaffolding for protein design
Kieran Didi, Francisco Vargas, Simon V Mathis, Vincent Dutordoir, Emile Mathieu, Urszula J Komorowska, Pietro Lio
A Framework for Exploring Federated Community Detection
William Leeney, Ryan McConville
Simul-LLM: A Framework for Exploring High-Quality Simultaneous Translation with Large Language Models
Victor Agostinelli, Max Wild, Matthew Raffel, Kazi Ahmed Asif Fuad, Lizhong Chen
Multi Actor-Critic DDPG for Robot Action Space Decomposition: A Framework to Control Large 3D Deformation of Soft Linear Objects
Mélodie Daniel, Aly Magassouba, Miguel Aranda, Laurent Lequièvre, Juan Antonio Corrales Ramon, Roberto Iglesias Rodriguez, Youcef Mezouar
A brief introduction to a framework named Multilevel Guidance-Exploration Network
Guoqing Yang, Zhiming Luo, Jianzhe Gao, Yingxin Lai, Kun Yang, Yifan He, Shaozi Li
OneLLM: One Framework to Align All Modalities with Language
Jiaming Han, Kaixiong Gong, Yiyuan Zhang, Jiaqi Wang, Kaipeng Zhang, Dahua Lin, Yu Qiao, Peng Gao, Xiangyu Yue
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
FlexModel: A Framework for Interpretability of Distributed Large Language Models
Matthew Choi, Muhammad Adil Asif, John Willes, David Emerson
LExCI: A Framework for Reinforcement Learning with Embedded Systems
Kevin Badalian, Lucas Koch, Tobias Brinkmann, Mario Picerno, Marius Wegener, Sung-Yong Lee, Jakob Andert
VEXIR2Vec: An Architecture-Neutral Embedding Framework for Binary Similarity
S. VenkataKeerthy, Yashas Andaluri, Sayan Dey, Soumya Banerjee, Ramakrishna Upadrasta
A framework for mining lifestyle profiles through multi-dimensional and high-order mobility feature clustering
Yeshuo Shu, Gangcheng Zhang, Keyi Liu, Jintong Tang, Liyan Xu
An integrated framework for developing and evaluating an automated lecture style assessment system
Eleni Dimitriadou, Andreas Lanitis
X-InstructBLIP: A Framework for aligning X-Modal instruction-aware representations to LLMs and Emergent Cross-modal Reasoning
Artemis Panagopoulou, Le Xue, Ning Yu, Junnan Li, Dongxu Li, Shafiq Joty, Ran Xu, Silvio Savarese, Caiming Xiong, Juan Carlos Niebles