7 citations · 17 across the 9 of their papers we have counts for
10 papers
VERDICT: Visual Extraction-Result Decoder with Integrated Confidence and Traceable Evidence
Harikrishnan P M, Goutham Vignesh, Siva Prasad +5
Enterprises run schema-guided structured field extraction on documents with frontier multimodal models, and accuracy keeps improving as new models and systems arrive. Two things ha…
Can a Lightweight Multimodal Model Estimate LLM Reasoning Performance? A Study for Compute-Optimal Document Inference
Zishan Ahmad, Vishal Vaddina
Uniformly allocating inference reasoning budgets to LLMs is expensive and prone to over-thinking penalties; especially in document tasks where visual layouts drive complexity. To a…
Stop Thinking, Start Looking: Efficient Post-Training for Multimodal Document Question Answering via Reasoning-Free Alignment
Harikrishnan P M, Goutham Vignesh, Ganesh Parab +4
Efficient multimodal document question answering with explicit visual grounding, locating the precise document region that supports each answer remains an open challenge. Current a…
DocAnnot -- Accelerating the Creation of Key Information Extraction Datasets with GenAI-Powered Auto-annotation
Siddartha Reddy, Harikrishnan P M, Goutham Vignesh +2
Key Information Extraction (KIE) is vital for many document applications, but creating training datasets is traditionally a time-consuming manual process. We introduce DocAnnot, a…
ACT: Bridging the Gap in Code Translation through Synthetic Data Generation & Adaptive Training
Shreya Saxena, Siva Prasad, Zishan Ahmad +1
Code translation is a crucial process in software development and migration projects, enabling interoperability between different programming languages and enhancing software adapt…
Knowledge Graph Based Repository-Level Code Generation
Mihir Athale, Vishal Vaddina
Recent advancements in Large Language Models (LLMs) have transformed code generation from natural language queries. However, despite their extensive knowledge and ability to produc…
Leveraging Latent Evolutionary Optimization for Targeted Molecule Generation
Siddartha Reddy N, Sai Prakash MV, Varun V +2
Lead optimization is a pivotal task in the drug design phase within the drug discovery lifecycle. The primary objective is to refine the lead compound to meet specific molecular pr…
Minimizing Factual Inconsistency and Hallucination in Large Language Models
Muneeswaran I, Shreya Saxena, Siva Prasad +5
Large Language Models (LLMs) are widely used in critical fields such as healthcare, education, and finance due to their remarkable proficiency in various language-related tasks. Ho…
Synergistic Fusion of Graph and Transformer Features for Enhanced Molecular Property Prediction
M V Sai Prakash, Siddartha Reddy N, Ganesh Parab +3
Molecular property prediction is a critical task in computational drug discovery. While recent advances in Graph Neural Networks (GNNs) and Transformers have shown to be effective…
Large-Scale Knowledge Synthesis and Complex Information Retrieval from Biomedical Documents
Shreya Saxena, Raj Sangani, Siva Prasad +4
Recent advances in the healthcare industry have led to an abundance of unstructured data, making it challenging to perform tasks such as efficient and accurate information retrieva…