Papers with coarse-to-fine mechanism
EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation (2021.findings-emnlp)
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| Challenge: | Pre-trained language models have shown remarkable results on various NLP tasks. |
| Approach: | They propose to improve the feed-forward network (FFN) in BERT with a higher computational cost than improving the multi-head attention (MHA). |
| Outcome: | The proposed model is 6.9 smaller and 4.4 faster than BERTBASE and has competitive performances on GLUE and SQuAD Benchmarks. |
CONE: An Efficient COarse-to-fiNE Alignment Framework for Long Video Temporal Grounding (2023.acl-long)
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Zhijian Hou, Wanjun Zhong, Lei Ji, Difei Gao, Kun Yan, W.k. Chan, Chong-Wah Ngo, Mike Zheng Shou, Nan Duan
| Challenge: | Existing work on video temporal grounding for long videos is limited by existing datasets. |
| Approach: | They propose a query-guided window selection strategy and a coarse-to-fine mechanism to speed up inference for long videos. |
| Outcome: | The proposed framework accelerates inference time by 2x on Ego4D-NLQ and 15x on MAD while keeping SOTA results. |