8 citations · 9 across the 11 of their papers we have counts for
10 papers · 1 filter
How Good is Zero-Shot MT Evaluation for Low Resource Indian Languages?
Anushka Singh, Ananya B. Sai, Raj Dabre +3
While machine translation evaluation has been studied primarily for high-resource languages, there has been a recent interest in evaluation for low-resource languages due to the in…
Language Models can Subtly Deceive Without Lying: A Case Study on Strategic Phrasing in Legislation
Atharvan Dogra, Krishna Pillutla, Ameet Deshpande +5
We explore the ability of large language models (LLMs) to engage in subtle deception through strategically phrasing and intentionally manipulating information. This harmful behavio…
BiPhone: Modeling Inter Language Phonetic Influences in Text
Abhirut Gupta, Ananya B. Sai, Richard Sproat +5
A large number of people are forced to use the Web in a language they have low literacy in due to technology asymmetries. Written text in the second language (L2) from such users o…
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
Perturbation CheckLists for Evaluating NLG Evaluation Metrics
Ananya B. Sai, Tanay Dixit, Dev Yashpal Sheth +2
Natural Language Generation (NLG) evaluation is a multifaceted task requiring assessment of multiple desirable criteria, e.g., fluency, coherency, coverage, relevance, adequacy, ov…
Improving Dialog Evaluation with a Multi-reference Adversarial Dataset and Large Scale Pretraining
Ananya B. Sai, Akash Kumar Mohankumar, Siddhartha Arora +1
There is an increasing focus on model-based dialog evaluation metrics such as ADEM, RUBER, and the more recent BERT-based metrics. These models aim to assign a high score to all re…