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Found 23 papers, 9 papers with code
Moses and the Character-Based Random Babbling Baseline: CoAStaL at AmericasNLP 2021 Shared Task
We evaluated a range of neural machine translation techniques developed specifically for low-resource scenarios.
How far can we get with one GPU in 100 hours? CoAStaL at MultiIndicMT Shared Task
This work shows that competitive translation results can be obtained in a constrained setting by incorporating the latest advances in memory and compute optimization.
Multilingual Compositional Wikidata Questions
Semantic parsing allows humans to leverage vast knowledge resources through natural interaction.
Itihasa: A large-scale corpus for Sanskrit to English translation
This work introduces Itihasa, a large-scale translation dataset containing 93, 000 pairs of Sanskrit shlokas and their English translations.
Ranked #1 on
Machine Translation
on Itihasa
Minimax and Neyman-Pearson Meta-Learning for Outlier Languages
In fact, under a decision-theoretic framework, MAML can be interpreted as minimising the expected risk across training languages (with a uniform prior), which is known as Bayes criterion.
Focus Attention: Promoting Faithfulness and Diversity in Summarization
Professional summaries are written with document-level information, such as the theme of the document, in mind.
Joint Semantic Analysis with Document-Level Cross-Task Coherence Rewards
Coreference resolution and semantic role labeling are NLP tasks that capture different aspects of semantics, indicating respectively, which expressions refer to the same entity, and what semantic roles expressions serve in the sentence.
Compositional Generalization in Image Captioning
Image captioning models are usually evaluated on their ability to describe a held-out set of images, not on their ability to generalize to unseen concepts.
Rewarding Coreference Resolvers for Being Consistent with World Knowledge
Unresolved coreference is a bottleneck for relation extraction, and high-quality coreference resolvers may produce an output that makes it a lot easier to extract knowledge triples.
Ellipsis Resolution as Question Answering: An Evaluation
Most, if not all forms of ellipsis (e. g., so does Mary) are similar to reading comprehension questions (what does Mary do), in that in order to resolve them, we need to identify an appropriate text span in the preceding discourse.
X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension
Although the vast majority of knowledge bases KBs are heavily biased towards English, Wikipedias do cover very different topics in different languages.
Model-based annotation of coreference
Humans do not make inferences over texts, but over models of what texts are about.
A Visual Programming Paradigm for Abstract Deep Learning Model Development
Deep learning is one of the fastest growing technologies in computer science with a plethora of applications.
Adversarial Black-Box Attacks on Automatic Speech Recognition Systems using Multi-Objective Evolutionary Optimization
Fooling deep neural networks with adversarial input have exposed a significant vulnerability in the current state-of-the-art systems in multiple domains.
Sanskrit Sandhi Splitting using seq2(seq)2
In Sanskrit, small words (morphemes) are combined to form compound words through a process known as Sandhi.
DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension
We propose DuoRC, a novel dataset for Reading Comprehension (RC) that motivates several new challenges for neural approaches in language understanding beyond those offered by existing RC datasets.
DeepTriage: Exploring the Effectiveness of Deep Learning for Bug Triaging
Using an attention mechanism enables the model to learn the context representation over a long word sequence, as in a bug report.
Sanskrit Sandhi Splitting using seq2(seq)^2
In Sanskrit, small words (morphemes) are combined to form compound words through a process known as Sandhi.
Hi, how can I help you?: Automating enterprise IT support help desks
Question answering is one of the primary challenges of natural language understanding.
mAnI: Movie Amalgamation using Neural Imitation
Cross-modal data retrieval has been the basis of various creative tasks performed by Artificial Intelligence (AI).
Fault in your stars: An Analysis of Android App Reviews
Further, we developed three systems; two of which were based on traditional machine learning and one on deep learning to automatically identify reviews whose rating did not match with the opinion expressed in the review.
Phoenix: A Self-Optimizing Chess Engine
With the advent of deep learning, chess playing agents can surpass human ability with relative ease.
