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Found 15 papers, 6 papers with code
A Data Bootstrapping Recipe for Low-Resource Multilingual Relation Classification
Data collection is challenging for Indian languages, because they are syntactically and morphologically diverse, as well as different from resource-rich languages like English.
LLM Augmented LLMs: Expanding Capabilities through Composition
Foundational models with billions of parameters which have been trained on large corpora of data have demonstrated non-trivial skills in a variety of domains.
XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages
We evaluate commonly used models on the benchmark.
CrysGNN : Distilling pre-trained knowledge to enhance property prediction for crystalline materials
To leverage these untapped data, this paper presents CrysGNN, a new pre-trained GNN framework for crystalline materials, which captures both node and graph level structural information of crystal graphs using a huge amount of unlabelled material data.
Bootstrapping Multilingual Semantic Parsers using Large Language Models
Despite cross-lingual generalization demonstrated by pre-trained multilingual models, the translate-train paradigm of transferring English datasets across multiple languages remains to be a key mechanism for training task-specific multilingual models.
A Data Bootstrapping Recipe for Low Resource Multilingual Relation Classification
Relation classification (sometimes called 'extraction') requires trustworthy datasets for fine-tuning large language models, as well as for evaluation.
A Hierarchical VAE for Calibrating Attributes while Generating Text using Normalizing Flow
In this digital age, online users expect personalized content.
Fine-grained Sentiment Controlled Text Generation
DE-VAE achieves better control of sentiment as an attribute while preserving the content by learning a suitable lossless transformation network from the disentangled sentiment space to the desired entangled representation.
A Deep Generative Model for Code-Switched Text
Code-switching, the interleaving of two or more languages within a sentence or discourse is pervasive in multilingual societies.
Improved Sentiment Detection via Label Transfer from Monolingual to Synthetic Code-Switched Text
Consequently, the best monolingual methods perform relatively poorly on code-switched text.
NeVAE: A Deep Generative Model for Molecular Graphs
Moreover, in contrast with the state of the art, our decoder is able to provide the spatial coordinates of the atoms of the molecules it generates.
All that is English may be Hindi: Enhancing language identification through automatic ranking of the likeliness of word borrowing in social media
Based on this likeliness estimate we asked annotators to re-annotate the language tags of foreign words in predominantly native contexts.
All that is English may be Hindi: Enhancing language identification through automatic ranking of likeliness of word borrowing in social media
Based on this likeliness estimate we asked annotators to re-annotate the language tags of foreign words in predominantly native contexts.
Is this word borrowed? An automatic approach to quantify the likeliness of borrowing in social media
We first propose context based clustering method to sample a set of candidate words from the social media data. Next, we propose three novel and similar metrics based on the usage of these words by the users in different tweets; these metrics were used to score and rank the candidate words indicating their borrowed likeliness.
