Arun Iyer

Principal Researcher

Publications

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- Chow-Liu Ordering for Long-Context Reasoning in Chain-of-Agents
  
  Naman Gupta, Vaibhav Singh, Arun Iyer, Kirankumar Shiragur, Pratham Grover, Ramakrishna Bairi, Ritabrata Maiti, Sankarshan Damle, Shachee Mishra Gupta, Rishikesh Maurya, Vageesh D C
  
  International Conference on Learning Representations Workshop on Memory for LLM-Based Agentic Systems | April 2026
  
  Publication
- Continuous Benchmark Generation for Evaluating Enterprise-scale LLM Agents
  
  Divyanshu Saxena, Rishikesh Maurya, Xiaoxuan Ou, Gagan Somashekar, Shachee Mishra Gupta, Arun Iyer, Yu Kang, Chetan Bansal, Aditya Akella, Saravan Rajmohan
  
  International Conference on Software Engineering Workshop on Large Language Models for Code | April 2026
  
  DOI Publication Publication
- STACKFEED: Structured Textual Actor-Critic Knowledge Base Editing with Feedback
  
  Naman Gupta, Shashank Kirtania, Priyanshu Gupta, Krishna Kariya, Sumit Gulwani, Arun Iyer, Suresh Parthasarathy, Arjun Radhakrishna, Sriram Rajamani, Gustavo Soares
  
  Empirical Methods in Natural Language Processing (EMNLP) 2025 - Industry Track | September 2025
  
  Publication
- COSMIR: Chain Orchestrated Structured Memory for Iterative Reasoning over Long Context
  
  Naman Gupta, Shreeyash Gowaikar, Arun Iyer, Kiran Shiragur, Ramakrishna Bairi, Rishikesh Maurya, Ritabrata Maiti, Sankarshan Damle, Shachee Mishra Gupta
  
  Neural Information Processing Systems Workshop on Foundations of Reasoning in Language Models (FoRLM-NeurIPS) | September 2025
  
  Publication
- CodePlan: Repository-level Coding using LLMs and Planning
  
  Ramakrishna Bairi, Atharv Sonwane, Aditya Kanade, Vageesh D C, Arun Shankar Iyer, Suresh Parthasarathy, Sriram Rajamani, B. Ashok, Shashank Shet
  
  Proceedings of the ACM on Software Engineering | July 2024, Vol 1(FSE): pp. 675-698
  
  Publication Project
- Class-Level Code Generation from Natural Language Using Iterative, Tool-Enhanced Reasoning over Repository
  
  Ajinkya Deshpande, Anmol Agarwal, Shashank Shet, Arun Iyer, Aditya Kanade, Ramakrishna Bairi, Suresh Parthasarathy
  
  International Conference on Machine Learning Workshop on Data-Centric Machine Learning Research (DMLR-ICML) | July 2024
  
  Publication Github
- 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
  
  Empirical Methods in Natural Language Processing (EMNLP) | December 2023
  
  Publication
- FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations
  
  Chanakya Ekbote, Ajinkya Pankaj Deshpande, Arun Iyer, Ramakrishna Bairi, Sundararajan Sellamanickam
  
  Neural Information Processing Systems (NeurIPS) | October 2023
  
  Publication
- A Piece-wise Polynomial Filtering Approach for Graph Neural Networks
  
  Vijay Lingam, Manan Sharma, Chanakya Ekbote, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam
  
  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) | August 2022
  
  PDF Github
- Landmarks and Regions: A Robust Approach to Data Extraction
  
  Suresh Parthasarathy, Lincy Pattanaik, Anirudh Khatry, Arun Iyer, Arjun Radhakrishna, Sriram Rajamani, Mohammad Raza
  
  Programming Language Design and Implementation (PLDI) | June 2022
  
  Publication PDF
- Jigsaw: Large Language Models meet Program Synthesis
  
  Naman Jain, Skanda Vaidyanath, Arun Iyer, Nagarajan Natarajan, Suresh Parthasarathy, Sriram Rajamani, Rahul Sharma
  
  International Conference on Software Engineering (ICSE) | May 2022
  
  Publication Github Project Project
- ProLinguist: Program Synthesis for Linguistics and NLP
  
  Partho Sarthi, Monojit Choudhury, Arun Iyer, Suresh Parthasarathy, Arjun Radhakrishna, Sriram Rajamani
  
  International Joint Conference on Artificial Intelligence Workshop on Neuro-Symbolic Natural Language Inference (NSNLI-IJCAI) | August 2021
  
  Publication Project Project
- Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs
  
  Vijay Lingam, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam
  
  Knowledge Discovery and Data Mining Workshop on Deep Learning on Graphs: Method and Applications (DLG-KDD) | June 2021
  
  Publication
- GLAM: Graph Learning by Modeling Affinity to Labeled Nodes for Graph Neural Networks
  
  Vijay Lingam, Arun Iyer, Rahul Ragesh
  
  International Conference on Learning Representations Workshop on Geometrical and Topological Representation Learning (GTRL-ICLR) | May 2021
  
  PDF Publication
- HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification
  
  Rahul Ragesh, Sundararajan Sellamanickam, Arun Iyer, Ramakrishna Bairi, Vijay Lingam
  
  Web Search and Data Mining (WSDM) | March 2021
  
  DOI Publication
- Synthesis and machine learning for heterogeneous extraction
  
  Arun Iyer, Manohar Jonnalagedda, Suresh Parthasarathy, Arjun Radhakrishna, Sriram Rajamani
  
  Programming Language Design and Implementation (PLDI) | June 2019
  
  PDF DOI Project Project
- Privacy-preserving Class Ratio Estimation
  
  Arun Iyer, Saketha Nath, Sunita Sarawagi
  
  Knowledge Discovery and Data Mining (KDD) | August 2016
  
  Publication Publication
- Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection
  
  Arun Iyer, Saketha Nath, Sunita Sarawagi
  
  International Conference on Machine Learning (ICML) | June 2014
  
  Publication
- Active Evaluation of Classifiers on Large Datasets
  
  Namit Katariya, Arun Iyer, Sunita Sarawagi
  
  International Conference on Data Mining (ICDM) | December 2012
  
  Publication Publication
- Collective extraction from heterogeneous web lists
  
  Ashwin Machanavajjhala, Arun Iyer, Philip Bohannon , Srujana Merugu
  
  Web Search and Data Mining (WSDM) | February 2011
  
  Publication PDF

- Chow-Liu Ordering for Long-Context Reasoning in Chain-of-Agents
  
  Naman Gupta, Vaibhav Singh, Arun Iyer, Kirankumar Shiragur, Pratham Grover, Ramakrishna Bairi, Ritabrata Maiti, Sankarshan Damle, Shachee Mishra Gupta, Rishikesh Maurya, Vageesh D C
  
  International Conference on Learning Representations Workshop on Memory for LLM-Based Agentic Systems | April 2026
  
  Publication
- Continuous Benchmark Generation for Evaluating Enterprise-scale LLM Agents
  
  Divyanshu Saxena, Rishikesh Maurya, Xiaoxuan Ou, Gagan Somashekar, Shachee Mishra Gupta, Arun Iyer, Yu Kang, Chetan Bansal, Aditya Akella, Saravan Rajmohan
  
  International Conference on Software Engineering Workshop on Large Language Models for Code | April 2026
  
  DOI Publication Publication
- STACKFEED: Structured Textual Actor-Critic Knowledge Base Editing with Feedback
  
  Naman Gupta, Shashank Kirtania, Priyanshu Gupta, Krishna Kariya, Sumit Gulwani, Arun Iyer, Suresh Parthasarathy, Arjun Radhakrishna, Sriram Rajamani, Gustavo Soares
  
  Empirical Methods in Natural Language Processing (EMNLP) 2025 - Industry Track | September 2025
  
  Publication
- COSMIR: Chain Orchestrated Structured Memory for Iterative Reasoning over Long Context
  
  Naman Gupta, Shreeyash Gowaikar, Arun Iyer, Kiran Shiragur, Ramakrishna Bairi, Rishikesh Maurya, Ritabrata Maiti, Sankarshan Damle, Shachee Mishra Gupta
  
  Neural Information Processing Systems Workshop on Foundations of Reasoning in Language Models (FoRLM-NeurIPS) | September 2025
  
  Publication
- CodePlan: Repository-level Coding using LLMs and Planning
  
  Ramakrishna Bairi, Atharv Sonwane, Aditya Kanade, Vageesh D C, Arun Shankar Iyer, Suresh Parthasarathy, Sriram Rajamani, B. Ashok, Shashank Shet
  
  Proceedings of the ACM on Software Engineering | July 2024, Vol 1(FSE): pp. 675-698
  
  Publication Project
- Class-Level Code Generation from Natural Language Using Iterative, Tool-Enhanced Reasoning over Repository
  
  Ajinkya Deshpande, Anmol Agarwal, Shashank Shet, Arun Iyer, Aditya Kanade, Ramakrishna Bairi, Suresh Parthasarathy
  
  International Conference on Machine Learning Workshop on Data-Centric Machine Learning Research (DMLR-ICML) | July 2024
  
  Publication Github
- 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
  
  Empirical Methods in Natural Language Processing (EMNLP) | December 2023
  
  Publication
- FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations
  
  Chanakya Ekbote, Ajinkya Pankaj Deshpande, Arun Iyer, Ramakrishna Bairi, Sundararajan Sellamanickam
  
  Neural Information Processing Systems (NeurIPS) | October 2023
  
  Publication
- A Piece-wise Polynomial Filtering Approach for Graph Neural Networks
  
  Vijay Lingam, Manan Sharma, Chanakya Ekbote, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam
  
  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) | August 2022
  
  PDF Github
- Landmarks and Regions: A Robust Approach to Data Extraction
  
  Suresh Parthasarathy, Lincy Pattanaik, Anirudh Khatry, Arun Iyer, Arjun Radhakrishna, Sriram Rajamani, Mohammad Raza
  
  Programming Language Design and Implementation (PLDI) | June 2022
  
  Publication PDF
- Jigsaw: Large Language Models meet Program Synthesis
  
  Naman Jain, Skanda Vaidyanath, Arun Iyer, Nagarajan Natarajan, Suresh Parthasarathy, Sriram Rajamani, Rahul Sharma
  
  International Conference on Software Engineering (ICSE) | May 2022
  
  Publication Github Project Project
- ProLinguist: Program Synthesis for Linguistics and NLP
  
  Partho Sarthi, Monojit Choudhury, Arun Iyer, Suresh Parthasarathy, Arjun Radhakrishna, Sriram Rajamani
  
  International Joint Conference on Artificial Intelligence Workshop on Neuro-Symbolic Natural Language Inference (NSNLI-IJCAI) | August 2021
  
  Publication Project Project
- Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs
  
  Vijay Lingam, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam
  
  Knowledge Discovery and Data Mining Workshop on Deep Learning on Graphs: Method and Applications (DLG-KDD) | June 2021
  
  Publication
- GLAM: Graph Learning by Modeling Affinity to Labeled Nodes for Graph Neural Networks
  
  Vijay Lingam, Arun Iyer, Rahul Ragesh
  
  International Conference on Learning Representations Workshop on Geometrical and Topological Representation Learning (GTRL-ICLR) | May 2021
  
  PDF Publication
- HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification
  
  Rahul Ragesh, Sundararajan Sellamanickam, Arun Iyer, Ramakrishna Bairi, Vijay Lingam
  
  Web Search and Data Mining (WSDM) | March 2021
  
  DOI Publication
- Synthesis and machine learning for heterogeneous extraction
  
  Arun Iyer, Manohar Jonnalagedda, Suresh Parthasarathy, Arjun Radhakrishna, Sriram Rajamani
  
  Programming Language Design and Implementation (PLDI) | June 2019
  
  PDF DOI Project Project
- Privacy-preserving Class Ratio Estimation
  
  Arun Iyer, Saketha Nath, Sunita Sarawagi
  
  Knowledge Discovery and Data Mining (KDD) | August 2016
  
  Publication Publication
- Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection
  
  Arun Iyer, Saketha Nath, Sunita Sarawagi
  
  International Conference on Machine Learning (ICML) | June 2014
  
  Publication
- Active Evaluation of Classifiers on Large Datasets
  
  Namit Katariya, Arun Iyer, Sunita Sarawagi
  
  International Conference on Data Mining (ICDM) | December 2012
  
  Publication Publication
- Collective extraction from heterogeneous web lists
  
  Ashwin Machanavajjhala, Arun Iyer, Philip Bohannon , Srujana Merugu
  
  Web Search and Data Mining (WSDM) | February 2011
  
  Publication PDF
- CodePlan: Repository-level Coding using LLMs and Planning
  
  Ramakrishna Bairi, Atharv Sonwane, Aditya Kanade, Vageesh D C, Arun Shankar Iyer, Suresh Parthasarathy, Sriram Rajamani, B. Ashok, Shashank Shet
  
  Proceedings of the ACM on Software Engineering | July 2024, Vol 1(FSE): pp. 675-698
  
  Publication Project
- Class-Level Code Generation from Natural Language Using Iterative, Tool-Enhanced Reasoning over Repository
  
  Ajinkya Deshpande, Anmol Agarwal, Shashank Shet, Arun Iyer, Aditya Kanade, Ramakrishna Bairi, Suresh Parthasarathy
  
  International Conference on Machine Learning Workshop on Data-Centric Machine Learning Research (DMLR-ICML) | July 2024
  
  Publication Github
- Jigsaw: Large Language Models meet Program Synthesis
  
  Naman Jain, Skanda Vaidyanath, Arun Iyer, Nagarajan Natarajan, Suresh Parthasarathy, Sriram Rajamani, Rahul Sharma
  
  International Conference on Software Engineering (ICSE) | May 2022
  
  Publication Github Project Project
- Synthesis and machine learning for heterogeneous extraction
  
  Arun Iyer, Manohar Jonnalagedda, Suresh Parthasarathy, Arjun Radhakrishna, Sriram Rajamani
  
  Programming Language Design and Implementation (PLDI) | June 2019
  
  PDF DOI Project Project
- Privacy-preserving Class Ratio Estimation
  
  Arun Iyer, Saketha Nath, Sunita Sarawagi
  
  Knowledge Discovery and Data Mining (KDD) | August 2016
  
  Publication Publication

- Chow-Liu Ordering for Long-Context Reasoning in Chain-of-Agents
  
  Naman Gupta, Vaibhav Singh, Arun Iyer, Kirankumar Shiragur, Pratham Grover, Ramakrishna Bairi, Ritabrata Maiti, Sankarshan Damle, Shachee Mishra Gupta, Rishikesh Maurya, Vageesh D C
  
  International Conference on Learning Representations Workshop on Memory for LLM-Based Agentic Systems | April 2026
  
  Publication
- Continuous Benchmark Generation for Evaluating Enterprise-scale LLM Agents
  
  Divyanshu Saxena, Rishikesh Maurya, Xiaoxuan Ou, Gagan Somashekar, Shachee Mishra Gupta, Arun Iyer, Yu Kang, Chetan Bansal, Aditya Akella, Saravan Rajmohan
  
  International Conference on Software Engineering Workshop on Large Language Models for Code | April 2026
  
  DOI Publication Publication
- STACKFEED: Structured Textual Actor-Critic Knowledge Base Editing with Feedback
  
  Naman Gupta, Shashank Kirtania, Priyanshu Gupta, Krishna Kariya, Sumit Gulwani, Arun Iyer, Suresh Parthasarathy, Arjun Radhakrishna, Sriram Rajamani, Gustavo Soares
  
  Empirical Methods in Natural Language Processing (EMNLP) 2025 - Industry Track | September 2025
  
  Publication
- COSMIR: Chain Orchestrated Structured Memory for Iterative Reasoning over Long Context
  
  Naman Gupta, Shreeyash Gowaikar, Arun Iyer, Kiran Shiragur, Ramakrishna Bairi, Rishikesh Maurya, Ritabrata Maiti, Sankarshan Damle, Shachee Mishra Gupta
  
  Neural Information Processing Systems Workshop on Foundations of Reasoning in Language Models (FoRLM-NeurIPS) | September 2025
  
  Publication
- Class-Level Code Generation from Natural Language Using Iterative, Tool-Enhanced Reasoning over Repository
  
  Ajinkya Deshpande, Anmol Agarwal, Shashank Shet, Arun Iyer, Aditya Kanade, Ramakrishna Bairi, Suresh Parthasarathy
  
  International Conference on Machine Learning Workshop on Data-Centric Machine Learning Research (DMLR-ICML) | July 2024
  
  Publication Github
- 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
  
  Empirical Methods in Natural Language Processing (EMNLP) | December 2023
  
  Publication
- FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations
  
  Chanakya Ekbote, Ajinkya Pankaj Deshpande, Arun Iyer, Ramakrishna Bairi, Sundararajan Sellamanickam
  
  Neural Information Processing Systems (NeurIPS) | October 2023
  
  Publication
- A Piece-wise Polynomial Filtering Approach for Graph Neural Networks
  
  Vijay Lingam, Manan Sharma, Chanakya Ekbote, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam
  
  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) | August 2022
  
  PDF Github
- Landmarks and Regions: A Robust Approach to Data Extraction
  
  Suresh Parthasarathy, Lincy Pattanaik, Anirudh Khatry, Arun Iyer, Arjun Radhakrishna, Sriram Rajamani, Mohammad Raza
  
  Programming Language Design and Implementation (PLDI) | June 2022
  
  Publication PDF
- Jigsaw: Large Language Models meet Program Synthesis
  
  Naman Jain, Skanda Vaidyanath, Arun Iyer, Nagarajan Natarajan, Suresh Parthasarathy, Sriram Rajamani, Rahul Sharma
  
  International Conference on Software Engineering (ICSE) | May 2022
  
  Publication Github Project Project
- ProLinguist: Program Synthesis for Linguistics and NLP
  
  Partho Sarthi, Monojit Choudhury, Arun Iyer, Suresh Parthasarathy, Arjun Radhakrishna, Sriram Rajamani
  
  International Joint Conference on Artificial Intelligence Workshop on Neuro-Symbolic Natural Language Inference (NSNLI-IJCAI) | August 2021
  
  Publication Project Project
- Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs
  
  Vijay Lingam, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam
  
  Knowledge Discovery and Data Mining Workshop on Deep Learning on Graphs: Method and Applications (DLG-KDD) | June 2021
  
  Publication
- GLAM: Graph Learning by Modeling Affinity to Labeled Nodes for Graph Neural Networks
  
  Vijay Lingam, Arun Iyer, Rahul Ragesh
  
  International Conference on Learning Representations Workshop on Geometrical and Topological Representation Learning (GTRL-ICLR) | May 2021
  
  PDF Publication
- HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification
  
  Rahul Ragesh, Sundararajan Sellamanickam, Arun Iyer, Ramakrishna Bairi, Vijay Lingam
  
  Web Search and Data Mining (WSDM) | March 2021
  
  DOI Publication
- Synthesis and machine learning for heterogeneous extraction
  
  Arun Iyer, Manohar Jonnalagedda, Suresh Parthasarathy, Arjun Radhakrishna, Sriram Rajamani
  
  Programming Language Design and Implementation (PLDI) | June 2019
  
  PDF DOI Project Project
- Privacy-preserving Class Ratio Estimation
  
  Arun Iyer, Saketha Nath, Sunita Sarawagi
  
  Knowledge Discovery and Data Mining (KDD) | August 2016
  
  Publication Publication
- Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection
  
  Arun Iyer, Saketha Nath, Sunita Sarawagi
  
  International Conference on Machine Learning (ICML) | June 2014
  
  Publication
- Active Evaluation of Classifiers on Large Datasets
  
  Namit Katariya, Arun Iyer, Sunita Sarawagi
  
  International Conference on Data Mining (ICDM) | December 2012
  
  Publication Publication
- Collective extraction from heterogeneous web lists
  
  Ashwin Machanavajjhala, Arun Iyer, Philip Bohannon , Srujana Merugu
  
  Web Search and Data Mining (WSDM) | February 2011
  
  Publication PDF
- CodePlan: Repository-level Coding using LLMs and Planning
  
  Ramakrishna Bairi, Atharv Sonwane, Aditya Kanade, Vageesh D C, Arun Shankar Iyer, Suresh Parthasarathy, Sriram Rajamani, B. Ashok, Shashank Shet
  
  Proceedings of the ACM on Software Engineering | July 2024, Vol 1(FSE): pp. 675-698
  
  Publication Project

Arun Iyer

Publications

Chow-Liu Ordering for Long-Context Reasoning in Chain-of-Agents

Continuous Benchmark Generation for Evaluating Enterprise-scale LLM Agents

STACKFEED: Structured Textual Actor-Critic Knowledge Base Editing with Feedback

COSMIR: Chain Orchestrated Structured Memory for Iterative Reasoning over Long Context

CodePlan: Repository-level Coding using LLMs and Planning

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

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

FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations

A Piece-wise Polynomial Filtering Approach for Graph Neural Networks

Landmarks and Regions: A Robust Approach to Data Extraction

Jigsaw: Large Language Models meet Program Synthesis

ProLinguist: Program Synthesis for Linguistics and NLP

Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs

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

HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification

Synthesis and machine learning for heterogeneous extraction

Privacy-preserving Class Ratio Estimation

Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection

Active Evaluation of Classifiers on Large Datasets

Collective extraction from heterogeneous web lists

Chow-Liu Ordering for Long-Context Reasoning in Chain-of-Agents

Continuous Benchmark Generation for Evaluating Enterprise-scale LLM Agents

STACKFEED: Structured Textual Actor-Critic Knowledge Base Editing with Feedback

COSMIR: Chain Orchestrated Structured Memory for Iterative Reasoning over Long Context

CodePlan: Repository-level Coding using LLMs and Planning

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

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

FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations

A Piece-wise Polynomial Filtering Approach for Graph Neural Networks

Landmarks and Regions: A Robust Approach to Data Extraction

Jigsaw: Large Language Models meet Program Synthesis

ProLinguist: Program Synthesis for Linguistics and NLP

Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs

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

HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification

Synthesis and machine learning for heterogeneous extraction

Privacy-preserving Class Ratio Estimation

Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection

Active Evaluation of Classifiers on Large Datasets

Collective extraction from heterogeneous web lists

CodePlan: Repository-level Coding using LLMs and Planning

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

Jigsaw: Large Language Models meet Program Synthesis

Synthesis and machine learning for heterogeneous extraction

Privacy-preserving Class Ratio Estimation

Chow-Liu Ordering for Long-Context Reasoning in Chain-of-Agents

Continuous Benchmark Generation for Evaluating Enterprise-scale LLM Agents

STACKFEED: Structured Textual Actor-Critic Knowledge Base Editing with Feedback

COSMIR: Chain Orchestrated Structured Memory for Iterative Reasoning over Long Context

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

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

FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations

A Piece-wise Polynomial Filtering Approach for Graph Neural Networks

Landmarks and Regions: A Robust Approach to Data Extraction

Jigsaw: Large Language Models meet Program Synthesis

ProLinguist: Program Synthesis for Linguistics and NLP

Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs

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

HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification

Synthesis and machine learning for heterogeneous extraction

Privacy-preserving Class Ratio Estimation

Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection

Active Evaluation of Classifiers on Large Datasets

Collective extraction from heterogeneous web lists

CodePlan: Repository-level Coding using LLMs and Planning