DE eng

Search in the Catalogues and Directories

Page: 1 2
Hits 1 – 20 of 34

1
Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction ...
BASE
Show details
2
Cross-lingual Representation Learning for Natural Language Processing
Ahmad, Wasi Uddin. - : eScholarship, University of California, 2021
BASE
Show details
3
Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions? ...
BASE
Show details
4
Improving Zero-Shot Cross-Lingual Transfer Learning via Robust Training ...
BASE
Show details
5
Societal Biases in Language Generation: Progress and Challenges ...
BASE
Show details
6
Socially Aware Bias Measurements for Hindi Language Representations ...
BASE
Show details
7
Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution ...
BASE
Show details
8
Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification ...
BASE
Show details
9
Intent Classification and Slot Filling for Privacy Policies ...
BASE
Show details
10
Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.162/ Abstract: Commonsense is defined as the knowledge that is shared by everyone. However, certain types of commonsense knowledge are correlated with culture and geographic locations and they are only shared locally. For example, the scenarios of wedding ceremonies vary across regions due to different customs influenced by historical and religious factors. Such regional characteristics, however, are generally omitted in prior work. In this paper, we construct a Geo-Diverse Visual Commonsense Reasoning dataset (GD-VCR) to test vision-and-language models' ability to understand cultural and geo-location-specific commonsense. In particular, we study two state-of-the-art Vision-and-Language models, VisualBERT and ViLBERT trained on VCR, a standard multimodal commonsense benchmark with images primarily from Western regions. We then evaluate how well the trained models can generalize to answering the questions in GD-VCR. We find that the performance of ...
Keyword: Computational Linguistics; Language Models; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
URL: https://dx.doi.org/10.48448/2j0n-jf43
https://underline.io/lecture/37514-broaden-the-vision-geo-diverse-visual-commonsense-reasoning
BASE
Hide details
11
Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions? ...
BASE
Show details
12
Defense against Synonym Substitution-based Adversarial Attacks via Dirichlet Neighborhood Ensemble ...
BASE
Show details
13
Improving Zero-Shot Cross-Lingual Transfer Learning via Robust Training ...
BASE
Show details
14
Syntax-augmented Multilingual BERT for Cross-lingual Transfer ...
BASE
Show details
15
Syntax-augmented Multilingual BERT for Cross-lingual Transfer ...
BASE
Show details
16
BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation ...
BASE
Show details
17
"The Boating Store Had Its Best Sail Ever": Pronunciation-attentive Contextualized Pun Recognition ...
BASE
Show details
18
Gender Bias in Multilingual Embeddings and Cross-Lingual Transfer ...
BASE
Show details
19
On the Robustness of Language Encoders against Grammatical Errors ...
Yin, Fan; Long, Quanyu; Meng, Tao. - : arXiv, 2020
BASE
Show details
20
GATE: Graph Attention Transformer Encoder for Cross-lingual Relation and Event Extraction ...
BASE
Show details

Page: 1 2

Catalogues
0
0
0
0
0
0
0
Bibliographies
0
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
34
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern