The zero-shot dual method approaches the performance, within 2.2 BLEU points, of a comparable supervised setting. Our method can obtain improvements also on the setting where a small amount of parallel data for the zero-shot language pair is available. Adding Russian, to extend our experiments ...
GET-Zero: Graph Embodiment Transformer for Zero-shot Embodiment Generalization - real-stanford/get_zero
Disclosed implementations provide an unsupervised, zero-shot semantic segmentation of an input image. Zero-shot segmentation is desirable because it avoids the costs of labeling, which can be quite high and can limit scalability and usefulness. However, constructing a model capable of segmenting anythin...
Clough PD, Sanderson M (2013) Evaluating the performance of information retrieval systems using test collections. Inf Res 18:2 Google Scholar Condevaux C, Harispe S, Mussard S, Zambrano G (2019) Weakly supervised one-shot classification using recurrent neural networks with attention: application ...
Some prior works point out that syntactic structures could be regarded as the language-independent features and those methods have achieved promising performance. However, sometimes even the sentences in different languages express the same meaning, the syntactic parsing results are quite different. To ...
This demonstrates that a low-rank projection would benefit the zero-shot learning. Moreover, we evaluate the impact of sampling size K. Figure 5 (c) shows the performance would increase when enlarging K. Specifically, K = 1 denotes we only learn one semantic dictionary from seen classes. ...
Visual Word Sense Disambiguation shared task at SemEval-2023 aims to identify an image corresponding to the intended meaning of a given ambiguous word (wit... N Katyal,P Rajpoot,S Tamilarasu,... 被引量: 0发表: 2023年 Translate to Disambiguate: Zero-shot Multilingual Word Sense Disambiguation...
added performance testing (getomni-ai#119) Dec 6, 2024 poetry.lock Python SDK: Feat. process specific pages, Other fixes and improvements ( Sep 18, 2024 pyproject.toml increment python version: name too long error fix Oct 22, 2024
test_performance: Runs on the test set for model ablation (results in the state-of-the-art table (SOTA) and in the model ablation plot: Table 6, 7 and Figure 3). ablation: Runs on the test set for hyperparamer ablation (values in the$\beta$and$l$ablation plots made with the best...
A strong, correlative mapping between different embedding sources is essential to a model’s generalization performance.3 Some zero-shot learning models also use contrastive learning to better align semantic embeddings from different models or algorithms: using pairs of semantic embeddings, contrastive ...