Search Results for author:
Found 8 papers, 4 papers with code
''Fifty Shades of Bias'': Normative Ratings of Gender Bias in GPT Generated English Text
Next, we systematically analyze the variation of themes of gender biases in the observed ranking and show that identity-attack is most closely related to gender bias.
Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?
Large Language Models (LLMs) excel in various Natural Language Processing (NLP) tasks, yet their evaluation, particularly in languages beyond the top $20$, remains inadequate due to existing benchmarks and metrics limitations.
MEGA: Multilingual Evaluation of Generative AI
Most studies on generative LLMs have been restricted to English and it is unclear how capable these models are at understanding and generating text in other languages.
Learnings from Technological Interventions in a Low Resource Language: Enhancing Information Access in Gondi
The primary obstacle to developing technologies for low-resource languages is the lack of representative, usable data.
Too Brittle To Touch: Comparing the Stability of Quantization and Distillation Towards Developing Lightweight Low-Resource MT Models
Leveraging shared learning through Massively Multilingual Models, state-of-the-art machine translation models are often able to adapt to the paucity of data for low-resource languages.
Towards Quantifying the Carbon Emissions of Differentially Private Machine Learning
In recent years, machine learning techniques utilizing large-scale datasets have achieved remarkable performance.
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.
PsuedoProp at SemEval-2020 Task 11: Propaganda Span Detection Using BERT-CRF and Ensemble Sentence Level Classifier
This paper explains our teams{'} submission to the Shared Task of Fine-Grained Propaganda Detection in which we propose a sequential BERT-CRF based Span Identification model where the fine-grained detection is carried out only on the articles that are flagged as containing propaganda by an ensemble SLC model.
