Papers by K. R. Jayaram
FLOW-BENCH: Towards Conversational Generation of Enterprise Workflows (2025.emnlp-industry)
Copied to clipboard
Evelyn Duesterwald, Siyu Huo, Vatche Isahagian, K. R. Jayaram, Ritesh Kumar, Vinod Muthusamy, Punleuk Oum, Debashish Saha, Gegi Thomas, Praveen Venkateswaran
| Challenge: | Large Language Models (LLMs) can be used to convert natural language (NL) instructions into structured business process automation (BPA) process artifacts. |
| Approach: | They propose to use large language models to convert natural language (NL) instructions into structured business process automation (BPA) process artifacts. |
| Outcome: | The proposed model can be used to translate NL into Python and convert it into widely adopted business process definition languages. |
OptiSeq: Ordering Examples On-The-Fly for In-Context Learning (2025.findings-emnlp)
Copied to clipboard
Rahul Atul Bhope, Praveen Venkateswaran, K. R. Jayaram, Vatche Isahagian, Vinod Muthusamy, Nalini Venkatasubramanian
| Challenge: | In-context-learning (ICL) is fragile and requires a lot of examples to perform. |
| Approach: | They propose a purely inference-time, dataset-free optimization method that efficiently determines the best example order. |
| Outcome: | The proposed method improves in-context-learning accuracy by 5.5 - 10.5 percentage points across multiple tasks. |