GitHub

Scaling Agentic Reinforcement Learning with a Multi-Turn, Multi-Task Framework

For a minimal example of how to use the environment framework, refer to examples/simple-calculator. For the environment and training data used in our paper, see AgentBench FC. For reproducing the ...
IEEE

SegCR: A Multimodal and Multitask Complementary Fusion Network for Remote Sensing Semantic Segmentation and Cloud Removal

Abstract: The synthetic aperture radar (SAR) can provide complementary information to optical images due to its insensitivity to atmospheric conditions, making optical–SAR fusion semantic segmentation ...
IEEE

EMVP: An Edge-Assisted Multi-Task Visual Perception System for Multi-Vehicle Scenarios

Abstract: Visual perception, as a core component of Intelligent Transportation Systems (ITS), plays a key role in enhancing safety and efficiency in urban mobility. While single-task visual perception ...

IIM Ranchi Launches State-of-the-Art Finance Lab for Experiential Learning and Research

Ranchi has come up with a finance lab aimed at supporting experiential learning and research in finance and allied areas. Located on the second floor of the Kanhu Block, the lab has been set up with ...
Microsoft

Scalable and Efficient MoE Training for Multitask Multilingual Models

The Mixture of Experts (MoE) models are an emerging class of sparsely activated deep learning models that have sublinear compute costs with respect to their parameters. In contrast with dense models, ...