TTIDA: Controllable Generative Data Augmentation via Text-to-Text and Text-to-Image Models
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Updated
Mar 7, 2024 - Python
TTIDA: Controllable Generative Data Augmentation via Text-to-Text and Text-to-Image Models
[ACL2023] NeuroStructural Decoding: Neural Text Generation with Structural Constraints
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Generative Modeling using GANs, DCGANs, WGAN, WGAN-GP, ProGAN, Conditional GANs and Controllable Generation.
[EMNLP2022] BioNLI: Generating a Biomedical NLI Dataset Using Lexico-semantic Constraints for Adversarial Examples
Code for my Bachelor thesis on Semantic Image Synthesis with Score-Based Generative Models
This repository contains the implementation of the project: "Controlling DDPMs and VAEs through EBMs" for the Deep Generative Models class @ UIC
Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled, TMLR 2024
Code for CHARD: Clinical Health-Aware Reasoning Across Dimensions for Text Generation Models
Controllable mage captioning model with unsupervised modes
Code for SMERTI for Semantic Text Exchange.
Code for SAPPHIRE: Approaches for Enhanced Concept-to-Text Generation (https://aclanthology.org/2021.inlg-1.21/) INLG 2021 Best Long Paper.
Source code of our TACL paper "Controllable Summarization with Constrained Markov Decision Process"
[Paperlist] Awesome paper list of controllable text generation via latent auto-encoders. Contributions of any kind are welcome.
[KBS] PCAE: A Framework of Plug-in Conditional Auto-Encoder for Controllable Text Generation PyTorch Implementation
Implementation of Collage Diffusion (https://arxiv.org/abs/2303.00262)
Implementing a Wassertein GAN with gradient penalty in pytorch
This is the official implementation of CCLAP for Controllable Chinese Landscape Painting generation. (ICME2023, oral)
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