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Found 7 papers, 4 papers with code
Parrot: Enhancing Multi-Turn Chat Models by Learning to Ask Questions
In this paper, we address these challenges by introducing Parrot, a highly scalable solution designed to automatically generate high-quality instruction-tuning data, which are then used to enhance the effectiveness of chat models in multi-turn conversations.
ViCo: Engaging Video Comment Generation with Human Preference Rewards
Experiments on ViCo-20k show that the comments generated by our ViCo model exhibit the best performance in terms of both quantitative and qualitative results, particularly when engagement is considered.
TeViS:Translating Text Synopses to Video Storyboards
In this paper, we propose a new task called Text synopsis to Video Storyboard (TeViS) which aims to retrieve an ordered sequence of images as the video storyboard to visualize the text synopsis.
Long-Form Video-Language Pre-Training with Multimodal Temporal Contrastive Learning
Large-scale video-language pre-training has shown significant improvement in video-language understanding tasks.
Ranked #2 on
Video Retrieval
on QuerYD
(using extra training data)
CLIP-ViP: Adapting Pre-trained Image-Text Model to Video-Language Representation Alignment
and 2) how to mitigate the impact of these factors?
Ranked #2 on
Video Retrieval
on MSR-VTT-1kA
(using extra training data)
Advancing High-Resolution Video-Language Representation with Large-Scale Video Transcriptions
To enable VL pre-training, we jointly optimize the HD-VILA model by a hybrid Transformer that learns rich spatiotemporal features, and a multimodal Transformer that enforces interactions of the learned video features with diversified texts.
Ranked #16 on
Video Retrieval
on MSR-VTT
WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training
We further construct a large Chinese multi-source image-text dataset called RUC-CAS-WenLan for pre-training our BriVL model.
Ranked #1 on
Image Retrieval
on RUC-CAS-WenLan
