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Found 11 papers, 6 papers with code
LPS@LT-EDI-ACL2022:An Ensemble Approach about Hope Speech Detection
The task shared by sponsor about Hope Speech Detection for Equality, Diversity, and Inclusion at LT-EDI-ACL-2022. The goal of this task is to identify whether a given comment contains hope speech or not, and hope is considered significant for the well-being, recuperation and restoration of human life. Our work aims to change the prevalent way of thinking by moving away from a preoccupation with discrimination, loneliness or the worst things in life to building the confidence, support and good qualities based on comments by individuals.
Towards Pareto Optimal Throughput in Small Language Model Serving
Large language models (LLMs) have revolutionized the state-of-the-art of many different natural language processing tasks.
The Case for Universal Basic Computing Power
The Universal Basic Computing Power (UBCP) initiative ensures global, free access to a set amount of computing power specifically for AI research and development (R&D).
H3WB: Human3.6M 3D WholeBody Dataset and Benchmark
We also propose three tasks: i) 3D whole-body pose lifting from 2D complete whole-body pose, ii) 3D whole-body pose lifting from 2D incomplete whole-body pose, and iii) 3D whole-body pose estimation from a single RGB image.
Ranked #2 on
3D Human Pose Estimation
on H3WB
Decanus to Legatus: Synthetic training for 2D-3D human pose lifting
3D human pose estimation is a challenging task because of the difficulty to acquire ground-truth data outside of controlled environments.
Impedance-based Root-cause Analysis: Comparative Study of Impedance Models and Calculation of Eigenvalue Sensitivity
Impedance models of power systems are useful when state-space models of apparatus such as inverter-based resources (IBRs) have not been made available and instead only black-box impedance models are available.
Intelligent Traffic Light via Policy-based Deep Reinforcement Learning
At first, the obtained optimal policy from PPO is compared to those from DQN and DDQN.
Participation Analysis in Impedance Models: The Grey-Box Approach for Power System Stability
This paper develops a grey-box approach to small-signal stability analysis of complex power systems that facilitates root-cause tracing without requiring disclosure of the full details of the internal control structure of apparatus connected to the system.
Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods
Convolutional networks are successful due to their equivariance/invariance under translations.
Isolation Kernel and Its Effect on SVM
This paper investigates data dependent kernels that are derived directly from data.
Multi-Label Learning with Global and Local Label Correlation
In fact, in the real-world applications, both cases may occur that some label correlations are globally applicable and some are shared only in a local group of instances.
