Arun Iyer

According to our database, Arun Iyer authored at least 15 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

CodePlan: Repository-Level Coding using LLMs and Planning.

Ramakrishna Bairi, Atharv Sonwane, Aditya Kanade, Vageesh D. C., Arun Iyer, Suresh Parthasarathy, Sriram K. Rajamani, Balasubramanyan Ashok, Shashank Shet

Proc. ACM Softw. Eng., 2024

STACKFEED: Structured Textual Actor-Critic Knowledge Base Editing with FeedBack.

Naman Gupta, Shashank Kirtania, Priyanshu Gupta, Krishna K. Mehra, Sumit Gulwani, Arun Iyer, Suresh Parthasarathy, Arjun Radhakrishna, Sriram K. Rajamani, Gustavo Soares

CoRR, 2024

Class-Level Code Generation from Natural Language Using Iterative, Tool-Enhanced Reasoning over Repository.

Ajinkya Pankaj Deshpande, Anmol Agarwal, Shashank Shet, Arun Iyer, Aditya Kanade, Ramakrishna Bairi, Suresh Parthasarathy

CoRR, 2024

2023

FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations.

Chanakya Ekbote, Ajinkya Pankaj Deshpande, Arun Iyer, Sundararajan Sellamanickam, Ramakrishna Bairi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Promoting Topic Coherence and Inter-Document Consorts in Multi-Document Summarization via Simplicial Complex and Sheaf Graph.

Yash Kumar Atri, Arun Iyer, Tanmoy Chakraborty, Vikram Goyal

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

Landmarks and regions: a robust approach to data extraction.

Suresh Parthasarathy, Lincy Pattanaik, Anirudh Khatry, Arun Iyer, Arjun Radhakrishna, Sriram K. Rajamani, Mohammad Raza

Proceedings of the PLDI '22: 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation, San Diego, CA, USA, June 13, 2022

A Piece-Wise Polynomial Filtering Approach for Graph Neural Networks.

Vijay Lingam, Manan Sharma, Chanakya Ekbote, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Jigsaw: Large Language Models meet Program Synthesis.

Naman Jain, Skanda Vaidyanath, Arun Iyer, Nagarajan Natarajan, Suresh Parthasarathy, Sriram K. Rajamani, Rahul Sharma

Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022

2021

Effective Eigendecomposition based Graph Adaptation for Heterophilic Networks.

Vijay Lingam, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam

CoRR, 2021

Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs.

Vijay Lingam, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam

CoRR, 2021

GLAM: Graph Learning by Modeling Affinity to Labeled Nodes for Graph Neural Networks.

Vijay Lingam, Arun Iyer, Rahul Ragesh

CoRR, 2021

User Embedding based Neighborhood Aggregation Method for Inductive Recommendation.

Rahul Ragesh, Sundararajan Sellamanickam, Vijay Lingam, Arun Iyer, Ramakrishna Bairi

CoRR, 2021

HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification.

Rahul Ragesh, Sundararajan Sellamanickam, Arun Iyer, Ramakrishna Bairi, Vijay Lingam

Proceedings of the WSDM '21, 2021

2020

A Graph Convolutional Network Composition Framework for Semi-supervised Classification.

Rahul Ragesh, Sundararajan Sellamanickam, Vijay Lingam, Arun Iyer

CoRR, 2020

2019

Synthesis and machine learning for heterogeneous extraction.

Arun Iyer, Manohar Jonnalagedda, Suresh Parthasarathy, Arjun Radhakrishna, Sriram K. Rajamani

Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation, 2019