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Found 6 papers, 1 papers with code
Unsupervised Adaptation of Question Answering Systems via Generative Self-training
Nevertheless, additional pre-training closer to the end-task, such as training on synthetic QA pairs, has been shown to improve performance.
CNNBiF: CNN-based Bigram Features for Named Entity Recognition
More importantly our fine-tuned CoNLL2003 model displays significant gains in generalization to out of domain datasets: on the OntoNotes subset we achieve an F1 of 72. 67 which is 0. 49 points absolute better than the baseline, and on the WNUT16 set an F1 of 68. 22 which is a gain of 0. 48 points.
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.
Co-Occuring Directions Sketching for Approximate Matrix Multiply
We introduce co-occurring directions sketching, a deterministic algorithm for approximate matrix product (AMM), in the streaming model.
Asymmetrically Weighted CCA And Hierarchical Kernel Sentence Embedding For Image & Text Retrieval
Joint modeling of language and vision has been drawing increasing interest.
Deep Multimodal Learning for Audio-Visual Speech Recognition
In this paper, we present methods in deep multimodal learning for fusing speech and visual modalities for Audio-Visual Automatic Speech Recognition (AV-ASR).
Audio-Visual Speech Recognition
Automatic Speech Recognition
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