5 papers
ChartAgent: A Multimodal Agent for Visually Grounded Reasoning in Complex Chart Question Answering
Rachneet Kaur, Nishan Srishankar, Zhen Zeng +2
Recent multimodal LLMs have shown promise in chart-based visual question answering, but their performance declines sharply on unannotated charts-those requiring precise visual inte…
Is There No Such Thing as a Bad Question? H4R: HalluciBot For Ratiocination, Rewriting, Ranking, and Routing
William Watson, Nicole Cho, Nishan Srishankar
Hallucination continues to be one of the most critical challenges in the institutional adoption journey of Large Language Models (LLMs). While prior studies have primarily focused…
LAW: Legal Agentic Workflows for Custody and Fund Services Contracts
William Watson, Nicole Cho, Nishan Srishankar +7
Legal contracts in the custody and fund services domain govern critical aspects such as key provider responsibilities, fee schedules, and indemnification rights. However, it is cha…
AdaptAgent: Adapting Multimodal Web Agents with Few-Shot Learning from Human Demonstrations
Gaurav Verma, Rachneet Kaur, Nishan Srishankar +3
State-of-the-art multimodal web agents, powered by Multimodal Large Language Models (MLLMs), can autonomously execute many web tasks by processing user instructions and interacting…
FISHNET: Financial Intelligence from Sub-querying, Harmonizing, Neural-Conditioning, Expert Swarms, and Task Planning
Nicole Cho, Nishan Srishankar, Lucas Cecchi +1
Financial intelligence generation from vast data sources has typically relied on traditional methods of knowledge-graph construction or database engineering. Recently, fine-tuned f…