Search Results for author: Sebastian Goodman

Found 7 papers, 2 papers with code

Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning

no code implementations NeurIPS 2021 Nan Ding, Xi Chen, Tomer Levinboim, Sebastian Goodman, Radu Soricut

Despite recent advances in its theoretical understanding, there still remains a significant gap in the ability of existing PAC-Bayesian theories on meta-learning to explain performance improvements in the few-shot learning setting, where the number of training examples in the target tasks is severely limited.

Few-Shot Learning

TeaForN: Teacher-Forcing with N-grams

no code implementations EMNLP 2020 Sebastian Goodman, Nan Ding, Radu Soricut

Sequence generation models trained with teacher-forcing suffer from issues related to exposure bias and lack of differentiability across timesteps.

Machine Translation Translation

Multi-Image Summarization: Textual Summary from a Set of Cohesive Images

no code implementations15 Jun 2020 Nicholas Trieu, Sebastian Goodman, Pradyumna Narayana, Kazoo Sone, Radu Soricut

Multi-sentence summarization is a well studied problem in NLP, while generating image descriptions for a single image is a well studied problem in Computer Vision.

Image Captioning Sentence Summarization

Multi-stage Pretraining for Abstractive Summarization

no code implementations23 Sep 2019 Sebastian Goodman, Zhenzhong Lan, Radu Soricut

Neural models for abstractive summarization tend to achieve the best performance in the presence of highly specialized, summarization specific modeling add-ons such as pointer-generator, coverage-modeling, and inferencetime heuristics.

Abstractive Text Summarization

Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning

1 code implementation ACL 2018 Piyush Sharma, Nan Ding, Sebastian Goodman, Radu Soricut

We present a new dataset of image caption annotations, Conceptual Captions, which contains an order of magnitude more images than the MS-COCO dataset (Lin et al., 2014) and represents a wider variety of both images and image caption styles.

Image Captioning

Understanding Image and Text Simultaneously: a Dual Vision-Language Machine Comprehension Task

no code implementations22 Dec 2016 Nan Ding, Sebastian Goodman, Fei Sha, Radu Soricut

We introduce a new multi-modal task for computer systems, posed as a combined vision-language comprehension challenge: identifying the most suitable text describing a scene, given several similar options.

Image Captioning Multi-Task Learning +1

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