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Found 9 papers, 3 papers with code
LLM-Oriented Retrieval Tuner
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.
Controllable Text Generation with Residual Memory Transformer
Large-scale Causal Language Models (CLMs), e. g., GPT3 and ChatGPT, have brought great success in text generation.
DisCup: Discriminator Cooperative Unlikelihood Prompt-tuning for Controllable Text Generation
Prompt learning with immensely large Casual Language Models (CLMs) has been shown promising for attribute-controllable text generation (CTG).
A Survey of Controllable Text Generation using Transformer-based Pre-trained Language Models
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.
Mengzi: Towards Lightweight yet Ingenious Pre-trained Models for Chinese
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.
ToxTrac: a fast and robust software for tracking organisms
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.
UmUTracker: A versatile MATLAB program for automated particle tracking of 2D light microscopy or 3D digital holography data
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.
A robust particle detection algorithm based on symmetry
Particle tracking is common in many biophysical, ecological, and micro-fluidic applications.
Circle detection using isosceles triangles sampling
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.
