Tech Xplore

An AI approach for single-image-based 3D character animation with preserved proportions

In Proceedings of the SIGGRAPH Asia 2025 Conference Papers, a research team affiliated with UNIST reports a new AI technology ...
Frontiers

Are S.M.A.R.T goals really smart? The psychological effects of goal-setting in a learning task

Aim: Specific, Measurable, Achievable, Realistic, Time-bound (SMART) goals are commonly used in educational settings as a strategy to optimise learning. However, research and theory suggest that such ...
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

Mobility-Aware Multi-Task Decentralized Federated Learning for Vehicular Networks: Modeling, Analysis, and Optimization

Abstract: Federated learning (FL) is a promising paradigm that can enable collaborative model training between vehicles while protecting data privacy, thereby significantly improving the performance ...
automaton-media

For all its multitasking, Pragmata’s gameplay has a surprisingly forgiving learning curve. Steam demo impressions

To get PC players hyped for Pragmata’s 2026 launch (and to test the game on a wide range of different specs), Capcom has released the totally free Sketchbook Demo. Lasting roughly 20 minutes, it ...
IEEE

Competitive Multitasking Sampling With Deep Reinforcement Learning for Surrogate-Assisted Constrained Multiobjective Optimization

Abstract: When solving expensive constrained multiobjective optimization problems by surrogate-assisted evolutionary algorithms, the evolutionary sampling method is utilized to select valuable ...