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ORCIDRamakrishna Bairi
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2020 – today
- 2024
[j1]Ramakrishna Bairi
, Atharv Sonwane, Aditya Kanade, Vageesh D. C., Arun Iyer, Suresh Parthasarathy, Sriram K. Rajamani, Balasubramanyan Ashok, Shashank Shet:
CodePlan: Repository-Level Coding using LLMs and Planning. Proc. ACM Softw. Eng. 1(FSE): 675-698 (2024)- [i6]Ajinkya Pankaj Deshpande, Anmol Agarwal, Shashank Shet, Arun Iyer, Aditya Kanade, Ramakrishna Bairi, Suresh Parthasarathy:
Class-Level Code Generation from Natural Language Using Iterative, Tool-Enhanced Reasoning over Repository. CoRR abs/2405.01573 (2024) - [i5]Daman Arora, Atharv Sonwane, Nalin Wadhwa, Abhav Mehrotra, Saiteja Utpala, Ramakrishna Bairi, Aditya Kanade, Nagarajan Natarajan:
MASAI: Modular Architecture for Software-engineering AI Agents. CoRR abs/2406.11638 (2024) - 2023
- [c11]Chanakya Ekbote, Ajinkya Pankaj Deshpande, Arun Iyer, Sundararajan Sellamanickam, Ramakrishna Bairi:
FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations. NeurIPS 2023 - [i4]Ramakrishna Bairi, Atharv Sonwane, Aditya Kanade, Vageesh D. C., Arun Iyer, Suresh Parthasarathy, Sriram K. Rajamani, Balasubramanyan Ashok, Shashank Shet:
CodePlan: Repository-level Coding using LLMs and Planning. CoRR abs/2309.12499 (2023) - [i3]Chanakya Ekbote, Ajinkya Pankaj Deshpande, Arun Iyer, Ramakrishna Bairi, Sundararajan Sellamanickam:
FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations. CoRR abs/2310.01892 (2023) - 2021
- [c10]Rahul Ragesh, Sundararajan Sellamanickam, Arun Iyer, Ramakrishna Bairi, Vijay Lingam:
HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification. WSDM 2021: 860-868 - [i2]Rahul Ragesh, Sundararajan Sellamanickam, Vijay Lingam, Arun Iyer, Ramakrishna Bairi:
User Embedding based Neighborhood Aggregation Method for Inductive Recommendation. CoRR abs/2102.07575 (2021) - 2020
- [i1]Rahul Ragesh, Sundararajan Sellamanickam, Arun Iyer, Ramakrishna Bairi, Vijay Lingam:
HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification. CoRR abs/2008.12842 (2020)
2010 – 2019
- 2018
- [b1]Ramakrishna Bairi:
Adaptive Organization of Digital Documents using Knowledge Graphs. Monash University, Australia, 2018 - 2016
- [c9]Ramakrishna B. Bairi, Raghavendra Udupa, Ganesh Ramakrishnan:
A Framework for Task-specific Short Document Expansion. CIKM 2016: 791-800 - [c8]Ramakrishna B. Bairi, Mark James Carman, Ganesh Ramakrishnan:
Beyond Clustering: Sub-DAG Discovery for Categorising Documents. CIKM 2016: 801-810 - 2015
- [c7]Ramakrishna Bairi, Rishabh K. Iyer, Ganesh Ramakrishnan, Jeff A. Bilmes:
Summarization of Multi-Document Topic Hierarchies using Submodular Mixtures. ACL (1) 2015: 553-563 - [c6]Ramakrishna B. Bairi, Ankit Vani, Pooja Ahuja, Ganesh Ramakrishnan:
Categorising videos using a personalised category catalogue. CODS 2015: 49-58 - 2014
- [c5]Ramakrishna B. Bairi, Ganesh Ramakrishnan, Vikas Sindhwani:
Personalized classifiers: evolving a classifier from a large reference knowledge graph. IDEAS 2014: 132-141 - [c4]Ramakrishna Bairi, Ganesh Ramakrishnan:
Labeling Documents in Search Collection: Evolving Classifiers on a Semantically Relevant Label Space. SMIR@SIGIR 2014: 8-15 - 2013
- [c3]Ramakrishna Bairi, Ambha A, Ganesh Ramakrishnan:
Learning to Generate Diversified Query Interpretations using Biconvex Optimization. IJCNLP 2013: 733-739 - [c2]Ramakrishna Bairi, A. Ambha, Ganesh Ramakrishnan:
Rel-Div: Generating Diversified Query Interpretations from Semantic Relations. PReMI 2013: 726-732 - [c1]Satyabrata Behera, Upasana Gaikwad, Ramakrishna Bairi, Ganesh Ramakrishnan:
SATTY : Word Sense Induction Application in Web Search Clustering. SemEval@NAACL-HLT 2013: 207-211
Coauthor Index
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