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Found 9 papers, 3 papers with code
52B to 1T: Lessons Learned via Tele-FLM Series
Large Language Models (LLMs) represent a significant stride toward Artificial General Intelligence.
Tele-FLM Technical Report
Large language models (LLMs) have showcased profound capabilities in language understanding and generation, facilitating a wide array of applications.
TeleChat Technical Report
Subsequently, the model undergoes fine-tuning to align with human preferences, following a detailed methodology that we describe.
Sophisticated deep learning with on-chip optical diffractive tensor processing
With OCU as the fundamental unit, we build an optical convolutional neural network (oCNN) to implement two popular deep learning tasks: classification and regression.
MonoRUn: Monocular 3D Object Detection by Reconstruction and Uncertainty Propagation
To regress the pixel-related 3D object coordinates, we employ a regional reconstruction network with uncertainty awareness.
Ranked #18 on
Monocular 3D Object Detection
on KITTI Cars Moderate
NAST: Non-Autoregressive Spatial-Temporal Transformer for Time Series Forecasting
Although Transformer has made breakthrough success in widespread domains especially in Natural Language Processing (NLP), applying it to time series forecasting is still a great challenge.
SPFCN: Select and Prune the Fully Convolutional Networks for Real-time Parking Slot Detection
For vehicles equipped with the automatic parking system, the accuracy and speed of the parking slot detection are crucial.
DsMCL: Dual-Level Stochastic Multiple Choice Learning for Multi-Modal Trajectory Prediction
One of the important and inherent factors is the multi-modality of vehicle motion.
Detecting Lane and Road Markings at A Distance with Perspective Transformer Layers
This is due to the fact that distant lane and road markings occupy a small number of pixels in the image, and scales of lane and road markings are inconsistent at various distances and perspectives.
