22 citations · 29 across the 16 of their papers we have counts for
16 papers · 1 filter
Litmus (Re)Agent: A Benchmark and Agentic System for Predictive Evaluation of Multilingual Models
Avni Mittal, Shanu Kumar, Sandipan Dandapat +1
We study predictive multilingual evaluation: estimating how well a model will perform on a task in a target language when direct benchmark results are missing. This problem is comm…
Socio-Culturally Aware Evaluation Framework for LLM-Based Content Moderation
Shanu Kumar, Gauri Kholkar, Saish Mendke +3
With the growth of social media and large language models, content moderation has become crucial. Many existing datasets lack adequate representation of different groups, resulting…
Enhancing Zero-shot Chain of Thought Prompting via Uncertainty-Guided Strategy Selection
Shanu Kumar, Saish Mendke, Karody Lubna Abdul Rahman +3
Chain-of-thought (CoT) prompting has significantly enhanced the capability of large language models (LLMs) by structuring their reasoning processes. However, existing methods face…
DiTTO: A Feature Representation Imitation Approach for Improving Cross-Lingual Transfer
Shanu Kumar, Abbaraju Soujanya, Sandipan Dandapat +2
Zero-shot cross-lingual transfer is promising, however has been shown to be sub-optimal, with inferior transfer performance across low-resource languages. In this work, we envision…
Too Brittle To Touch: Comparing the Stability of Quantization and Distillation Towards Developing Lightweight Low-Resource MT Models
Harshita Diddee, Sandipan Dandapat, Monojit Choudhury +2
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 langua…
On the Calibration of Massively Multilingual Language Models
Kabir Ahuja, Sunayana Sitaram, Sandipan Dandapat +1
Massively Multilingual Language Models (MMLMs) have recently gained popularity due to their surprising effectiveness in cross-lingual transfer. While there has been much work in ev…
"Diversity and Uncertainty in Moderation" are the Key to Data Selection for Multilingual Few-shot Transfer
Shanu Kumar, Sandipan Dandapat, Monojit Choudhury
Few-shot transfer often shows substantial gain over zero-shot transfer~\cite{lauscher2020zero}, which is a practically useful trade-off between fully supervised and unsupervised le…
Multi Task Learning For Zero Shot Performance Prediction of Multilingual Models
Kabir Ahuja, Shanu Kumar, Sandipan Dandapat +1
Massively Multilingual Transformer based Language Models have been observed to be surprisingly effective on zero-shot transfer across languages, though the performance varies from…
Beyond Static Models and Test Sets: Benchmarking the Potential of Pre-trained Models Across Tasks and Languages
Kabir Ahuja, Sandipan Dandapat, Sunayana Sitaram +1
Although recent Massively Multilingual Language Models (MMLMs) like mBERT and XLMR support around 100 languages, most existing multilingual NLP benchmarks provide evaluation data i…
On the Economics of Multilingual Few-shot Learning: Modeling the Cost-Performance Trade-offs of Machine Translated and Manual Data
Kabir Ahuja, Monojit Choudhury, Sandipan Dandapat
Borrowing ideas from {\em Production functions} in micro-economics, in this paper we introduce a framework to systematically evaluate the performance and cost trade-offs between ma…
Multilingual CheckList: Generation and Evaluation
Karthikeyan K, Shaily Bhatt, Pankaj Singh +4
Multilingual evaluation benchmarks usually contain limited high-resource languages and do not test models for specific linguistic capabilities. CheckList is a template-based evalua…
Predicting the Performance of Multilingual NLP Models
Anirudh Srinivasan, Sunayana Sitaram, Tanuja Ganu +3
Recent advancements in NLP have given us models like mBERT and XLMR that can serve over 100 languages. The languages that these models are evaluated on, however, are very few in nu…
On the Universality of Deep Contextual Language Models
Shaily Bhatt, Poonam Goyal, Sandipan Dandapat +2
Deep Contextual Language Models (LMs) like ELMO, BERT, and their successors dominate the landscape of Natural Language Processing due to their ability to scale across multiple task…
GLUECoS : An Evaluation Benchmark for Code-Switched NLP
Simran Khanuja, Sandipan Dandapat, Anirudh Srinivasan +2
Code-switching is the use of more than one language in the same conversation or utterance. Recently, multilingual contextual embedding models, trained on multiple monolingual corpo…
A New Dataset for Natural Language Inference from Code-mixed Conversations
Simran Khanuja, Sandipan Dandapat, Sunayana Sitaram +1
Natural Language Inference (NLI) is the task of inferring the logical relationship, typically entailment or contradiction, between a premise and hypothesis. Code-mixing is the use…
Translating Web Search Queries into Natural Language Questions
Adarsh Kumar, Sandipan Dandapat, Sushil Chordia
Users often query a search engine with a specific question in mind and often these queries are keywords or sub-sentential fragments. For example, if the users want to know the answ…