Search Results for author:
Found 8 papers, 6 papers with code
Meet Your Favorite Character: Open-domain Chatbot Mimicking Fictional Characters with only a Few Utterances
To better reflect the style of the character, PDP builds the prompts in the form of dialog that includes the character's utterances as dialog history.
Understanding and Improving the Exemplar-based Generation for Open-domain Conversation
Extensive experiments demonstrate that our proposed training method alleviates the drawbacks of the existing exemplar-based generative models and significantly improves the performance in terms of appropriateness and informativeness.
Distilling the Knowledge of Large-scale Generative Models into Retrieval Models for Efficient Open-domain Conversation
G2R consists of two distinct techniques of distillation: the data-level G2R augments the dialogue dataset with additional responses generated by the large-scale generative model, and the model-level G2R transfers the response quality score assessed by the generative model to the score of the retrieval model by the knowledge distillation loss.
Disentangling Label Distribution for Long-tailed Visual Recognition
Although this method surpasses state-of-the-art methods on benchmark datasets, it can be further improved by directly disentangling the source label distribution from the model prediction in the training phase.
Ranked #20 on
Long-tail Learning
on Places-LT
MarioNETte: Few-shot Face Reenactment Preserving Identity of Unseen Targets
When there is a mismatch between the target identity and the driver identity, face reenactment suffers severe degradation in the quality of the result, especially in a few-shot setting.
Temporal Convolution for Real-time Keyword Spotting on Mobile Devices
In addition, we release the implementation of the proposed and the baseline models including an end-to-end pipeline for training models and evaluating them on mobile devices.
Ranked #14 on
Keyword Spotting
on Google Speech Commands
(Google Speech Commands V2 12 metric)
Towards Real-Time Automatic Portrait Matting on Mobile Devices
We tackle the problem of automatic portrait matting on mobile devices.
Hybrid Approach of Relation Network and Localized Graph Convolutional Filtering for Breast Cancer Subtype Classification
In this paper, we proposed a hybrid model, which integrates two key components 1) graph convolution neural network (graph CNN) and 2) relation network (RN).
