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Found 9 papers, 4 papers with code
Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent
In this paper, we introduce Hunyuan-Large, which is currently the largest open-source Transformer-based mixture of experts model, with a total of 389 billion parameters and 52 billion activation parameters, capable of handling up to 256K tokens.
Flatten: Video Action Recognition is an Image Classification task
In recent years, video action recognition, as a fundamental task in the field of video understanding, has been deeply explored by numerous researchers. Most traditional video action recognition methods typically involve converting videos into three-dimensional data that encapsulates both spatial and temporal information, subsequently leveraging prevalent image understanding models to model and analyze these data.
Traffic Signal Cycle Control with Centralized Critic and Decentralized Actors under Varying Intervention Frequencies
Traffic congestion in urban areas is a significant problem, leading to prolonged travel times, reduced efficiency, and increased environmental concerns.
Are LLMs Effective Backbones for Fine-tuning? An Experimental Investigation of Supervised LLMs on Chinese Short Text Matching
The recent success of Large Language Models (LLMs) has garnered significant attention in both academia and industry.
UniTSA: A Universal Reinforcement Learning Framework for V2X Traffic Signal Control
Traffic congestion is a persistent problem in urban areas, which calls for the development of effective traffic signal control (TSC) systems.
ADLight: A Universal Approach of Traffic Signal Control with Augmented Data Using Reinforcement Learning
In this paper, we propose a novel reinforcement learning approach with augmented data (ADLight) to train a universal model for intersections with different structures.
Rate-Splitting Multiple Access for Multi-Antenna Joint Radar and Communications
In this work, we propose a powerful and unified multi-antenna DFRC transmission framework, where an additional radar sequence is transmitted apart from communication streams to enhance radar beampattern matching capability, and Rate-Splitting Multiple Access (RSMA) is adopted to better manage the interference.
Multi-Antenna Joint Radar and Communications: Precoder Optimization and Weighted Sum-Rate vs Probing Power Tradeoff
The tradeoffs between WSR and probing power at target are compared among both proposed transmissions and two practically simpler dual-function implementations i. e., time division and frequency division.
Signal Shaping for Non-Uniform Beamspace Modulated mmWave Hybrid MIMO Communications
Specifically, we firstly propose a joint optimization based signal shaping (JOSS) approach, in which the symbol vector sets used for all analog precoder activation states are jointly optimized by solving a series of quadratically constrained quadratic programming (QCQP) problems.
