2 citations · 5 across the 15 of their papers we have counts for
16 papers
Last Translation Benchmark
Vilém Zouhar, Niyati Bafna, Mukund Choudhary +263
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…
SN-WER: Script-Normalized WER for Multi-Script Indic ASR Evaluation
Priyaranjan Pattnayak
Word Error Rate (WER) is the dominant metric for automatic speech recognition (ASR), but it can overestimate errors when references and hypotheses encode the same words in differen…
Anthropogenic Regional Adaptation in Multimodal Vision-Language Model
Samuel Cahyawijaya, Peerat Limkonchotiwat, Tack Hwa Wong +45
While the field of vision-language (VL) has achieved remarkable success in integrating visual and textual information across multiple languages and domains, there is still no dedic…
IndicSafe: A Benchmark for Evaluating Multilingual LLM Safety in South Asia
Priyaranjan Pattnayak, Sanchari Chowdhuri
As large language models (LLMs) are deployed in multilingual settings, their safety behavior in culturally diverse, low-resource languages remains poorly understood. We present the…
IndicJR: A Judge-Free Benchmark of Jailbreak Robustness in South Asian Languages
Priyaranjan Pattnayak, Sanchari Chowdhuri
Safety alignment of large language models (LLMs) is mostly evaluated in English and contract-bound, leaving multilingual vulnerabilities understudied. We introduce \textbf{Indic Ja…
LLM-Guided Lifecycle-Aware Clustering of Multi-Turn Customer Support Conversations
Priyaranjan Pattnayak, Sanchari Chowdhuri, Amit Agarwal +1
Clustering customer chat data is vital for cloud providers handling multi service queries. Traditional methods struggle with overlapping concerns and create broad, static clusters…
Review of Tools for Zero-Code LLM Based Application Development
Priyaranjan Pattnayak, Hussain Bohra
Large Language Models (LLMs) are transforming software creation by enabling zero code development platforms. Our survey reviews recent platforms that let users build applications w…
Hybrid AI for Responsive Multi-Turn Online Conversations with Novel Dynamic Routing and Feedback Adaptation
Priyaranjan Pattnayak, Amit Agarwal, Hansa Meghwani +2
Retrieval-Augmented Generation (RAG) systems and large language model (LLM)-powered chatbots have significantly advanced conversational AI by combining generative capabilities with…
Hard Negative Mining for Domain-Specific Retrieval in Enterprise Systems
Hansa Meghwani, Amit Agarwal, Priyaranjan Pattnayak +2
Enterprise search systems often struggle to retrieve accurate, domain-specific information due to semantic mismatches and overlapping terminologies. These issues can degrade the pe…
SweEval: Do LLMs Really Swear? A Safety Benchmark for Testing Limits for Enterprise Use
Hitesh Laxmichand Patel, Amit Agarwal, Arion Das +6
Enterprise customers are increasingly adopting Large Language Models (LLMs) for critical communication tasks, such as drafting emails, crafting sales pitches, and composing casual…
Tokenization Matters: Improving Zero-Shot NER for Indic Languages
Priyaranjan Pattnayak, Hitesh Laxmichand Patel, Amit Agarwal
Tokenization is a critical component of Natural Language Processing (NLP), especially for low resource languages, where subword segmentation influences vocabulary structure and dow…
Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia
Samuel Cahyawijaya, Holy Lovenia, Joel Ruben Antony Moniz +89
Southeast Asia (SEA) is a region of extraordinary linguistic and cultural diversity, yet it remains significantly underrepresented in vision-language (VL) research. This often resu…
Clinical QA 2.0: Multi-Task Learning for Answer Extraction and Categorization
Priyaranjan Pattnayak, Hitesh Laxmichand Patel, Amit Agarwal +3
Clinical Question Answering (CQA) plays a crucial role in medical decision-making, enabling physicians to extract relevant information from Electronic Medical Records (EMRs). While…
Survey of Large Multimodal Model Datasets, Application Categories and Taxonomy
Priyaranjan Pattnayak, Hitesh Laxmichand Patel, Bhargava Kumar +4
Multimodal learning, a rapidly evolving field in artificial intelligence, seeks to construct more versatile and robust systems by integrating and analyzing diverse types of data, i…
LLM for Barcodes: Generating Diverse Synthetic Data for Identity Documents
Hitesh Laxmichand Patel, Amit Agarwal, Bhargava Kumar +2
Accurate barcode detection and decoding in Identity documents is crucial for applications like security, healthcare, and education, where reliable data extraction and verification…
Enhancing Document AI Data Generation Through Graph-Based Synthetic Layouts
Amit Agarwal, Hitesh Patel, Priyaranjan Pattnayak +3
The development of robust Document AI models has been constrained by limited access to high-quality, labeled datasets, primarily due to data privacy concerns, scarcity, and the hig…