2 citations · 3 across the 11 of their papers we have counts for
11 papers
BharatBBQ: A Multilingual Bias Benchmark for Question Answering in the Indian Context
Aditya Tomar, Nihar Ranjan Sahoo, Pushpak Bhattacharyya
Evaluating social biases in language models (LMs) is crucial for ensuring fairness and minimizing the reinforcement of harmful stereotypes in AI systems. Existing benchmarks, such…
Stereotype Detection as a Catalyst for Enhanced Bias Detection: A Multi-Task Learning Approach
Aditya Tomar, Rudra Murthy, Pushpak Bhattacharyya
Bias and stereotypes in language models can cause harm, especially in sensitive areas like content moderation and decision-making. This paper addresses bias and stereotype detectio…
Mathematics Isn't Culture-Free: Probing Cultural Gaps via Entity and Scenario Perturbations
Aditya Tomar, Nihar Ranjan Sahoo, Ashish Mittal +2
Although mathematics is often considered culturally neutral, the way mathematical problems are presented can carry implicit cultural context. Existing benchmarks like GSM8K are pre…
Reconsidering SMT Over NMT for Closely Related Languages: A Case Study of Persian-Hindi Pair
Waisullah Yousofi, Pushpak Bhattacharyya
This paper demonstrates that Phrase-Based Statistical Machine Translation (PBSMT) can outperform Transformer-based Neural Machine Translation (NMT) in moderate-resource scenarios,…
Are Language Models Agnostic to Linguistically Grounded Perturbations? A Case Study of Indic Languages
Poulami Ghosh, Raj Dabre, Pushpak Bhattacharyya
Pre-trained language models (PLMs) are known to be susceptible to perturbations to the input text, but existing works do not explicitly focus on linguistically grounded attacks, wh…
How effective is Multi-source pivoting for Translation of Low Resource Indian Languages?
Pranav Gaikwad, Meet Doshi, Raj Dabre +1
Machine Translation (MT) between linguistically dissimilar languages is challenging, especially due to the scarcity of parallel corpora. Prior works suggest that pivoting through a…
Precision Empowers, Excess Distracts: Visual Question Answering With Dynamically Infused Knowledge In Language Models
Manas Jhalani, Annervaz K M, Pushpak Bhattacharyya
In the realm of multimodal tasks, Visual Question Answering (VQA) plays a crucial role by addressing natural language questions grounded in visual content. Knowledge-Based Visual Q…
Unveiling the Invisible: Captioning Videos with Metaphors
Abisek Rajakumar Kalarani, Pushpak Bhattacharyya, Sumit Shekhar
Metaphors are a common communication tool used in our day-to-day life. The detection and generation of metaphors in textual form have been studied extensively but metaphors in othe…
A Morphology-Based Investigation of Positional Encodings
Poulami Ghosh, Shikhar Vashishth, Raj Dabre +1
Contemporary deep learning models effectively handle languages with diverse morphology despite not being directly integrated into them. Morphology and word order are closely linked…
Pretraining Language Models Using Translationese
Meet Doshi, Raj Dabre, Pushpak Bhattacharyya
In this paper, we explore the utility of translationese as synthetic data created using machine translation for pre-training language models (LMs) for low-resource languages (LRLs)…
PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics Capabilities
Settaluri Lakshmi Sravanthi, Meet Doshi, Tankala Pavan Kalyan +3
LLMs have demonstrated remarkable capability for understanding semantics, but they often struggle with understanding pragmatics. To demonstrate this fact, we release a Pragmatics U…