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Found 17 papers, 3 papers with code
The USTC-NELSLIP Offline Speech Translation Systems for IWSLT 2022
This paper describes USTC-NELSLIP’s submissions to the IWSLT 2022 Offline Speech Translation task, including speech translation of talks from English to German, English to Chinese and English to Japanese.
GauU-Scene V2: Assessing the Reliability of Image-Based Metrics with Expansive Lidar Image Dataset Using 3DGS and NeRF
The experimental results on our multimodal dataset highlight the unreliability of current image-based metrics and reveal significant drawbacks in geometric reconstruction using the current Gaussian Splatting-based method, further illustrating the necessity of our dataset for assessing geometry reconstruction tasks.
PE-GPT: A Physics-Informed Interactive Large Language Model for Power Converter Modulation Design
This paper proposes PE-GPT, a custom-tailored large language model uniquely adapted for power converter modulation design.
Optimizing Group Utility in Itinerary Planning: A Strategic and Crowd-Aware Approach
Itinerary recommendation is a complex sequence prediction problem with numerous real-world applications.
FSVVD: A Dataset of Full Scene Volumetric Video
Recent years have witnessed a rapid development of immersive multimedia which bridges the gap between the real world and virtual space.
A Transformer-based Framework for POI-level Social Post Geolocation
POI-level geo-information of social posts is critical to many location-based applications and services.
Analyzing Scientific Publications using Domain-Specific Word Embedding and Topic Modelling
Word embedding is used to capture semantic meanings of domain-specific words.
Photozilla: A Large-Scale Photography Dataset and Visual Embedding for 20 Photography Styles
The dataset is then used to train 3 classification models to automatically classify the images into the relevant style which resulted in an accuracy of ~96%.
Urban Crowdsensing using Social Media: An Empirical Study on Transformer and Recurrent Neural Networks
An important aspect of urban planning is understanding crowd levels at various locations, which typically require the use of physical sensors.
Designing learning experiences for online teaching and learning
Teaching is about constantly innovating strategies, ways and means to engage diverse students in active and meaningful learning.
EPIC30M: An Epidemics Corpus Of Over 30 Million Relevant Tweets
In this paper, we present EPIC30M, a large-scale epidemic corpus that contains 30 millions micro-blog posts, i. e., tweets crawled from Twitter, from year 2006 to 2020.
CrisisBERT: a Robust Transformer for Crisis Classification and Contextual Crisis Embedding
However, none of the works perform crisis embedding and classification using state of the art attention-based deep neural networks models, such as Transformers and document-level contextual embeddings.
A Large-scale Industrial and Professional Occupation Dataset
There has been growing interest in utilizing occupational data mining and analysis.
IPOD: An Industrial and Professional Occupations Dataset and its Applications to Occupational Data Mining and Analysis
Occupational data mining and analysis is an important task in understanding today's industry and job market.
Strategic and Crowd-Aware Itinerary Recommendation
There is a rapidly growing demand for itinerary planning in tourism but this task remains complex and difficult, especially when considering the need to optimize for queuing time and crowd levels for multiple users.
Learning Efficient Lexically-Constrained Neural Machine Translation with External Memory
Recent years has witnessed dramatic progress of neural machine translation (NMT), however, the method of manually guiding the translation procedure remains to be better explored.
The USTC-NEL Speech Translation system at IWSLT 2018
This paper describes the USTC-NEL system to the speech translation task of the IWSLT Evaluation 2018.
