Search Results for author:
Found 14 papers, 8 papers with code
Bitions@DravidianLangTech-EACL2021: Ensemble of Multilingual Language Models with Pseudo Labeling for offence Detection in Dravidian Languages
Our model is able to handle code-mixed data as well as instances where the script used is mixed (for instance, Tamil and Latin).
IndicLLMSuite: A Blueprint for Creating Pre-training and Fine-Tuning Datasets for Indian Languages
We hope that the datasets, tools, and resources released as a part of this work will not only propel the research and development of Indic LLMs but also establish an open-source blueprint for extending such efforts to other languages.
User Embedding Model for Personalized Language Prompting
Modeling long histories plays a pivotal role in enhancing recommendation systems, allowing to capture user's evolving preferences, resulting in more precise and personalized recommendations.
IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages
Prior to this work, there was (i) no parallel training data spanning all 22 languages, (ii) no robust benchmarks covering all these languages and containing content relevant to India, and (iii) no existing translation models which support all the 22 scheduled languages of India.
A Comprehensive Analysis of Adapter Efficiency
However, adapters have not been sufficiently analyzed to understand if PEFT translates to benefits in training/deployment efficiency and maintainability/extensibility.
Vārta: A Large-Scale Headline-Generation Dataset for Indic Languages
We present V\=arta, a large-scale multilingual dataset for headline generation in Indic languages.
Naamapadam: A Large-Scale Named Entity Annotated Data for Indic Languages
The dataset contains more than 400k sentences annotated with a total of at least 100k entities from three standard entity categories (Person, Location, and, Organization) for 9 out of the 11 languages.
Towards Leaving No Indic Language Behind: Building Monolingual Corpora, Benchmark and Models for Indic Languages
Across languages and tasks, IndicXTREME contains a total of 105 evaluation sets, of which 52 are new contributions to the literature.
Effectiveness of Mining Audio and Text Pairs from Public Data for Improving ASR Systems for Low-Resource Languages
Significantly, we show that adding Shrutilipi to the training set of Wav2Vec models leads to an average decrease in WER of 5. 8\% for 7 languages on the IndicSUPERB benchmark.
Optical Character Recognition (OCR)
Self-Supervised Learning
+3
A Survey of Adversarial Defences and Robustness in NLP
In the past few years, it has become increasingly evident that deep neural networks are not resilient enough to withstand adversarial perturbations in input data, leaving them vulnerable to attack.
Offense Detection in Dravidian Languages using Code-Mixing Index based Focal Loss
To summarize, our model can handle offensive language detection in a low-resource, class imbalanced, multilingual and code-mixed setting.
Towards Building ASR Systems for the Next Billion Users
Second, using this raw speech data we pretrain several variants of wav2vec style models for 40 Indian languages.
A Primer on Pretrained Multilingual Language Models
Multilingual Language Models (\MLLMs) such as mBERT, XLM, XLM-R, \textit{etc.}
Joint Multilingual Sentence Representations
Multilingual text classification
+4
Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages
We mine the parallel sentences from the web by combining many corpora, tools, and methods: (a) web-crawled monolingual corpora, (b) document OCR for extracting sentences from scanned documents, (c) multilingual representation models for aligning sentences, and (d) approximate nearest neighbor search for searching in a large collection of sentences.
