Papers by Arun Iyer
STACKFEED: Structured Textual Actor-Critic Knowledge base editing with FEEDback (2025.emnlp-industry)
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Shashank Kirtania, Naman Gupta, Priyanshu Gupta, Sumit Gulwani, Arun Iyer, Suresh Parthasarathy Iyengar, Arjun Radhakrishna, Sriram K. Rajamani, Gustavo Soares
| Challenge: | Large Language Models (LLMs) often generate incorrect or outdated information, especially in low-resource settings or when dealing with private data. |
| Approach: | They propose a framework that iteratively refines the knowledge base based on expert feedback . they define a ReACT actor agent on each document to perform structured edits . |
| Outcome: | The proposed framework improves the quality and performance of the RAG system on low-resource programming problems, modified Python packages, and factual question-answering tasks. |
Promoting Topic Coherence and Inter-Document Consorts in Multi-Document Summarization via Simplicial Complex and Sheaf Graph (2023.emnlp-main)
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| Challenge: | Existing systems that generate summaries from multiple sources often lack accuracy and accuracy due to the length of tokens used in encoding. |
| Approach: | They propose a novel encoder-decoder model that uses pre-trained BART to analyze linguistic nuances, simplicial complex layer to apprehend inherent properties that transcend pairwise associations and sheaf graph attention to effectively capture heterophilic properties. |
| Outcome: | The proposed model achieves consistent performance improvement across all evaluation metrics (syntactical, semantical and faithfulness). |