6 papers · 1 filter
Bridging the Semantic Gap: Contrastive Rewards for Multilingual Text-to-SQL with GRPO
Ashish Kattamuri, Ishita Prasad, Meetu Malhotra +3
Current Text-to-SQL methods are evaluated and only focused on executable queries, overlooking the semantic alignment challenge -- both in terms of the semantic meaning of the query…
Equilibrium Dynamics and Mitigation of Gender Bias in Synthetically Generated Data
Ashish Kattamuri, Arpita Vats, Harshwardhan Fartale +3
Recursive prompting with large language models enables scalable synthetic dataset generation but introduces the risk of bias amplification. We investigate gender bias dynamics acro…
FUSE : A Ridge and Random Forest-Based Metric for Evaluating MT in Indigenous Languages
Rahul Raja, Arpita Vats
This paper presents the winning submission of the RaaVa team to the AmericasNLP 2025 Shared Task 3 on Automatic Evaluation Metrics for Machine Translation (MT) into Indigenous Lang…
Multilingual State Space Models for Structured Question Answering in Indic Languages
Arpita Vats, Rahul Raja, Mrinal Mathur +2
The diversity and complexity of Indic languages present unique challenges for natural language processing (NLP) tasks, particularly in the domain of question answering (QA).To addr…
Alignment Quality Index (AQI) : Beyond Refusals: AQI as an Intrinsic Alignment Diagnostic via Latent Geometry, Cluster Divergence, and Layer wise Pooled Representations
Abhilekh Borah, Chhavi Sharma, Danush Khanna +12
Alignment is no longer a luxury, it is a necessity. As large language models (LLMs) enter high-stakes domains like education, healthcare, governance, and law, their behavior must r…
Parallel Corpora for Machine Translation in Low-resource Indic Languages: A Comprehensive Review
Rahul Raja, Arpita Vats
Parallel corpora play an important role in training machine translation (MT) models, particularly for low-resource languages where high-quality bilingual data is scarce. This revie…