78 citations · 164 across the 33 of their papers we have counts for
33 papers
Actions Speak Louder than Words: Measuring Cross-Lingual Policy Retention in Tool-Using Agents
Sourabrata Mukherjee, Kalika Bali, Sunayana Sitaram
When a tool-using agent is given the same task in a different language, does it still take the same steps? Multilingual evaluation rarely asks: it compares final answers and discar…
The Geometry of LLM-as-Judge: Why Inter-LLM Consensus Is Not Human Alignment
Sourabrata Mukherjee, Hamna Hamna, Kalika Bali +1
LLM judges now score most open-ended NLP output, and their mutual agreement is routinely read as evidence that the scores can be trusted. That reading is unsafe: judges may agree b…
ELR-1000: A Community-Generated Dataset for Endangered Indic Indigenous Languages
Neha Joshi, Pamir Gogoi, Aasim Mirza +7
We present a culturally-grounded multimodal dataset of 1,060 traditional recipes crowdsourced from rural communities across remote regions of Eastern India, spanning 10 endangered…
What's Not on the Plate? Rethinking Food Computing through Indigenous Indian Datasets
Pamir Gogoi, Neha Joshi, Ayushi Pandey +6
This paper presents a multimodal dataset of 1,000 indigenous recipes from remote regions of India, collected through a participatory model involving first-time digital workers from…
Building Benchmarks from the Ground Up: Community-Centered Evaluation of LLMs in Healthcare Chatbot Settings
Hamna Hamna, Gayatri Bhat, Sourabrata Mukherjee +5
Large Language Models (LLMs) are typically evaluated through general or domain-specific benchmarks testing capabilities that often lack grounding in the lived realities of end user…
How Deep Is Representational Bias in LLMs? The Cases of Caste and Religion
Agrima Seth, Monojit Choudhary, Sunayana Sitaram +3
Representational bias in large language models (LLMs) has predominantly been measured through single-response interactions and has focused on Global North-centric identities like r…
An Interdisciplinary Approach to Human-Centered Machine Translation
Marine Carpuat, Omri Asscher, Kalika Bali +17
Machine Translation (MT) tools are widely used today, often in contexts where professional translators are not present. Despite progress in MT technology, a gap persists between sy…
KAHANI: Culturally-Nuanced Visual Storytelling Tool for Non-Western Cultures
Hamna, Deepthi Sudharsan, Agrima Seth +6
Large Language Models (LLMs) and Text-To-Image (T2I) models have demonstrated the ability to generate compelling text and visual stories. However, their outputs are predominantly a…
Towards Inducing Long-Context Abilities in Multilingual Neural Machine Translation Models
Varun Gumma, Pranjal A. Chitale, Kalika Bali
Neural Machine Translation (NMT) models have traditionally used Sinusoidal Positional Embeddings (PEs), which often struggle to capture long-range dependencies and are inefficient…
Cultural Conditioning or Placebo? On the Effectiveness of Socio-Demographic Prompting
Sagnik Mukherjee, Muhammad Farid Adilazuarda, Sunayana Sitaram +3
Socio-demographic prompting is a commonly employed approach to study cultural biases in LLMs as well as for aligning models to certain cultures. In this paper, we systematically pr…
Beyond Metrics: Evaluating LLMs' Effectiveness in Culturally Nuanced, Low-Resource Real-World Scenarios
Millicent Ochieng, Varun Gumma, Sunayana Sitaram +5
The deployment of Large Language Models (LLMs) in real-world applications presents both opportunities and challenges, particularly in multilingual and code-mixed communication sett…
Akal Badi ya Bias: An Exploratory Study of Gender Bias in Hindi Language Technology
Rishav Hada, Safiya Husain, Varun Gumma +8
Existing research in measuring and mitigating gender bias predominantly centers on English, overlooking the intricate challenges posed by non-English languages and the Global South…
METAL: Towards Multilingual Meta-Evaluation
Rishav Hada, Varun Gumma, Mohamed Ahmed +2
With the rising human-like precision of Large Language Models (LLMs) in numerous tasks, their utilization in a variety of real-world applications is becoming more prevalent. Severa…
BEnQA: A Question Answering and Reasoning Benchmark for Bengali and English
Sheikh Shafayat, H M Quamran Hasan, Minhajur Rahman Chowdhury Mahim +3
In this study, we introduce BEnQA, a dataset comprising parallel Bengali and English exam questions for middle and high school levels in Bangladesh. Our dataset consists of approxi…
DOSA: A Dataset of Social Artifacts from Different Indian Geographical Subcultures
Agrima Seth, Sanchit Ahuja, Kalika Bali +1
Generative models are increasingly being used in various applications, such as text generation, commonsense reasoning, and question-answering. To be effective globally, these model…
MunTTS: A Text-to-Speech System for Mundari
Varun Gumma, Rishav Hada, Aditya Yadavalli +4
We present MunTTS, an end-to-end text-to-speech (TTS) system specifically for Mundari, a low-resource Indian language of the Austo-Asiatic family. Our work addresses the gap in lin…
MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks
Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma +8
There has been a surge in LLM evaluation research to understand LLM capabilities and limitations. However, much of this research has been confined to English, leaving LLM building…
''Fifty Shades of Bias'': Normative Ratings of Gender Bias in GPT Generated English Text
Rishav Hada, Agrima Seth, Harshita Diddee +1
Language serves as a powerful tool for the manifestation of societal belief systems. In doing so, it also perpetuates the prevalent biases in our society. Gender bias is one of the…
Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?
Rishav Hada, Varun Gumma, Adrian de Wynter +5
Large Language Models (LLMs) excel in various Natural Language Processing (NLP) tasks, yet their evaluation, particularly in languages beyond the top , remains inadequate due t…
X-RiSAWOZ: High-Quality End-to-End Multilingual Dialogue Datasets and Few-shot Agents
Mehrad Moradshahi, Tianhao Shen, Kalika Bali +16
Task-oriented dialogue research has mainly focused on a few popular languages like English and Chinese, due to the high dataset creation cost for a new language. To reduce the cost…
Bridging the Language Gap: Dynamic Learning Strategies for Improving Multilingual Performance in LLMs
Somnath Kumar, Vaibhav Balloli, Mercy Ranjit +5
Large language models (LLMs) have revolutionized various domains but still struggle with non-Latin scripts and low-resource languages. This paper addresses the critical challenge o…
MEGA: Multilingual Evaluation of Generative AI
Kabir Ahuja, Harshita Diddee, Rishav Hada +9
Generative AI models have shown impressive performance on many Natural Language Processing tasks such as language understanding, reasoning, and language generation. An important qu…
Learnings from Technological Interventions in a Low Resource Language: Enhancing Information Access in Gondi
Devansh Mehta, Harshita Diddee, Ananya Saxena +8
The primary obstacle to developing technologies for low-resource languages is the lack of representative, usable data. In this paper, we report the deployment of technology-driven…
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…