Search Results for author: Yen-Chun Chen

Found 17 papers, 10 papers with code

Multimodal Adaptive Distillation for Leveraging Unimodal Encoders for Vision-Language Tasks

no code implementations22 Apr 2022 Zhecan Wang, Noel Codella, Yen-Chun Chen, Luowei Zhou, Xiyang Dai, Bin Xiao, Jianwei Yang, Haoxuan You, Kai-Wei Chang, Shih-Fu Chang, Lu Yuan

Experiments demonstrate that MAD leads to consistent gains in the low-shot, domain-shifted, and fully-supervised conditions on VCR, SNLI-VE, and VQA, achieving SOTA performance on VCR compared to other single models pretrained with image-text data.

Question Answering Visual Commonsense Reasoning +3

CLIP-TD: CLIP Targeted Distillation for Vision-Language Tasks

no code implementations15 Jan 2022 Zhecan Wang, Noel Codella, Yen-Chun Chen, Luowei Zhou, Jianwei Yang, Xiyang Dai, Bin Xiao, Haoxuan You, Shih-Fu Chang, Lu Yuan

Experiments demonstrate that our proposed CLIP-TD leads to exceptional gains in the low-shot (up to 51. 9%) and domain-shifted (up to 71. 3%) conditions of VCR, while simultaneously improving performance under standard fully-supervised conditions (up to 2%), achieving state-of-art performance on VCR compared to other single models that are pretrained with image-text data only.

Question Answering Visual Commonsense Reasoning +3

Behind the Scene: Revealing the Secrets of Pre-trained Vision-and-Language Models

no code implementations ECCV 2020 Jize Cao, Zhe Gan, Yu Cheng, Licheng Yu, Yen-Chun Chen, Jingjing Liu

To reveal the secrets behind the scene of these powerful models, we present VALUE (Vision-And-Language Understanding Evaluation), a set of meticulously designed probing tasks (e. g., Visual Coreference Resolution, Visual Relation Detection, Linguistic Probing Tasks) generalizable to standard pre-trained V+L models, aiming to decipher the inner workings of multimodal pre-training (e. g., the implicit knowledge garnered in individual attention heads, the inherent cross-modal alignment learned through contextualized multimodal embeddings).

Coreference Resolution

Distilling Knowledge Learned in BERT for Text Generation

1 code implementation ACL 2020 Yen-Chun Chen, Zhe Gan, Yu Cheng, Jingzhou Liu, Jingjing Liu

Experiments show that the proposed approach significantly outperforms strong Transformer baselines on multiple language generation tasks such as machine translation and text summarization.

Language Modelling Machine Translation +4

UNITER: UNiversal Image-TExt Representation Learning

5 code implementations ECCV 2020 Yen-Chun Chen, Linjie Li, Licheng Yu, Ahmed El Kholy, Faisal Ahmed, Zhe Gan, Yu Cheng, Jingjing Liu

Different from previous work that applies joint random masking to both modalities, we use conditional masking on pre-training tasks (i. e., masked language/region modeling is conditioned on full observation of image/text).

Language Modelling Masked Language Modeling +9

UNITER: Learning UNiversal Image-TExt Representations

no code implementations25 Sep 2019 Yen-Chun Chen, Linjie Li, Licheng Yu, Ahmed El Kholy, Faisal Ahmed, Zhe Gan, Yu Cheng, Jingjing Liu

Joint image-text embedding is the bedrock for most Vision-and-Language (V+L) tasks, where multimodality inputs are jointly processed for visual and textual understanding.

Language Modelling Masked Language Modeling +7

Explore, Propose, and Assemble: An Interpretable Model for Multi-Hop Reading Comprehension

1 code implementation ACL 2019 Yichen Jiang, Nitish Joshi, Yen-Chun Chen, Mohit Bansal

Multi-hop reading comprehension requires the model to explore and connect relevant information from multiple sentences/documents in order to answer the question about the context.

Multi-Hop Reading Comprehension

Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting

2 code implementations ACL 2018 Yen-Chun Chen, Mohit Bansal

Inspired by how humans summarize long documents, we propose an accurate and fast summarization model that first selects salient sentences and then rewrites them abstractively (i. e., compresses and paraphrases) to generate a concise overall summary.

Abstractive Text Summarization Sentence ReWriting

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