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Found 6 papers, 2 papers with code
Cloud-Based Real-Time Molecular Screening Platform with MolFormer
With the prospect of automating a number of chemical tasks with high fidelity, chemical language processing models are emerging at a rapid speed.
Image Captioning as an Assistive Technology: Lessons Learned from VizWiz 2020 Challenge
Image captioning has recently demonstrated impressive progress largely owing to the introduction of neural network algorithms trained on curated dataset like MS-COCO.
Alleviating Noisy Data in Image Captioning with Cooperative Distillation
Image captioning systems have made substantial progress, largely due to the availability of curated datasets like Microsoft COCO or Vizwiz that have accurate descriptions of their corresponding images.
Improved Adversarial Image Captioning
In this paper we study image captioning as a conditional GAN training, proposing both a context-aware LSTM captioner and co-attentive discriminator, which enforces semantic alignment between images and captions.
Adversarial Semantic Alignment for Improved Image Captions
When evaluated on OOC and MS-COCO benchmarks, we show that SCST-based training has a strong performance in both semantic score and human evaluation, promising to be a valuable new approach for efficient discrete GAN training.
Self-critical Sequence Training for Image Captioning
In this paper we consider the problem of optimizing image captioning systems using reinforcement learning, and show that by carefully optimizing our systems using the test metrics of the MSCOCO task, significant gains in performance can be realized.
