no code implementations • 4 Mar 2024 • Si Sun, Hanqing Zhang, Zhiyuan Liu, Jie Bao, Dawei Song
Dense Retrieval (DR) is now considered as a promising tool to enhance the memorization capacity of Large Language Models (LLM) such as GPT3 and GPT-4 by incorporating external memories.
2 code implementations • 28 Sep 2023 • Hanqing Zhang, Sun Si, Haiming Wu, Dawei Song
Large-scale Causal Language Models (CLMs), e. g., GPT3 and ChatGPT, have brought great success in text generation.
1 code implementation • 18 Oct 2022 • Hanqing Zhang, Dawei Song
Prompt learning with immensely large Casual Language Models (CLMs) has been shown promising for attribute-controllable text generation (CTG).
no code implementations • 14 Jan 2022 • Hanqing Zhang, Haolin Song, Shaoyu Li, Ming Zhou, Dawei Song
In recent years, methods using large-scale pre-trained language models (PLMs), in particular the widely used transformer-based PLMs, have become a new paradigm of NLG, allowing generation of more diverse and fluent text.
1 code implementation • 13 Oct 2021 • Zhuosheng Zhang, Hanqing Zhang, Keming Chen, Yuhang Guo, Jingyun Hua, Yulong Wang, Ming Zhou
Although pre-trained models (PLMs) have achieved remarkable improvements in a wide range of NLP tasks, they are expensive in terms of time and resources.
no code implementations • 8 Jun 2017 • Alvaro Rodriquez, Hanqing Zhang, Jonatan Klaminder, Tomas Brodin, Patrik L. Andersson, Magnus Andersson
The main advantages of ToxTrac are: i) no specific knowledge of the geometry of the tracked bodies is needed; ii) processing speed, ToxTrac can operate at a rate >25 frames per second in HD videos using modern desktop computers; iii) simultaneous tracking of multiple organisms in multiple arenas; iv) integrated distortion correction and camera calibration; v) robust against false positives; vi) preservation of individual identification if crossing occurs; vii) useful statistics and heat maps in real scale are exported in: image, text and excel formats.
no code implementations • 27 Jan 2017 • Hanqing Zhang, Tim Stangner, Krister Wiklund, Alvaro Rodriguez, Magnus Andersson
We present a versatile and fast MATLAB program (UmUTracker) that automatically detects and tracks particles by analyzing video sequences acquired by either light microscopy or digital in-line holographic microscopy.
no code implementations • 11 May 2016 • Alvaro Rodriguez, Hanqing Zhang, Krister Wiklund, Tomas Brodin, Jonatan Klaminder, Patrik Andersson, Magnus Andersson
Particle tracking is common in many biophysical, ecological, and micro-fluidic applications.
no code implementations • 2 Nov 2015 • Hanqing Zhang, Krister Wiklund, Magnus Andersson
Extensive experiments using both synthetic and real images were presented and results were compared to leading state-of-the-art algorithms and showed that the proposed algorithm: are efficient in finding circles with a low number of iterations; has high rejection rate of false-positive circle candidates; and has high robustness against noise, making it adaptive and useful in many vision applications.