Akhilesh Gotmare
I am an AI Researcher with Salesforce Research in Singapore where I work on deep learning and its
applications in processing natural language and code. My current focus is on training CodeLLMs to improving the software development cycle.
I lead AI research on ApexGuru, which improves Apex code quality by identifying anti-patterns and generates optimizations for fixing them, and has been featured at Dreamforce's keynote
sessions for developers and
architects .
I completed my MSc at the Department of Computer Science at EPFL, Switzerland,
where I was working with Prof. Martin Jaggi's
Machine Learning and Optimization laboratory for my thesis project on model parallel training of deep neural nets. Prior to EPFL,
I completed my undergraduate studies in Electrical Engineering (with a CSE minor) from IIT Gandhinagar,
where among other things I had the fun experience of organizing the maiden TEDx event on campus!
Email  | 
Google Scholar |
LinkedIn |
GitHub
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CodeT5+: Open Code LLMs for Code Understanding and Generation
Yue Wang, Hung Le, Akhilesh Gotmare, Nghi Bui, Junnan Li, Steven Hoi
EMNLP 2023
[ arXiv,
Blog,
Code ]
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CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning
Hung Le, Yue Wang, Akhilesh Gotmare, Silvio Savarese, Steven Hoi
NeurIPS 2022
[ arXiv,
Blog,
Code,
Media]
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Cascaded Fast and Slow Models for Efficient Semantic Code Search
Akhilesh Gotmare, Junnan Li, Shafiq Joty, Steven Hoi
Foundations of Software Engineering 2023
[ FSE 2023 ]
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Align before fuse: Vision and language representation learning with momentum distillation
Junnan Li, Ramprasaath Selvaraju, Akhilesh Gotmare, Shafiq Joty, Caiming Xiong, Steven Hoi
NeurIPS 2021 (Spotlight)
[ arXiv,
Blog,
Code ]
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GeDi: Generative Discriminator Guided Sequence Generation
Ben Krause*, Akhilesh Gotmare*, Bryan McCann, Nitish Shirish Keskar, Shafiq Joty, Richard Socher, Nazneen Fatema Rajani
EMNLP 2021 (Findings)
[ arXiv,
Blog,
VB coverage,
Import AI,
Code,
Demo ]
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A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation
Akhilesh Gotmare, Nitish Shirish Keskar, Caiming Xiong and Richard Socher
ICLR 2019 (partial results presented at CRACT Workshop, NeurIPS 2018)
[ arXiv,
OpenReview,
Poster ]
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Using Mode Connectivity for Loss Landscape Analysis
Akhilesh Gotmare, Nitish Shirish Keskar, Caiming Xiong and Richard Socher
Workshop on Modern Trends in Nonconvex Optimization for Machine Learning, ICML 2018.
[ arXiv,
Poster ]
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Decoupling Backpropagation using Constrained Optimization Methods
Akhilesh Gotmare*, Valentin Thomas*, Johanni Brea and Martin Jaggi
Workshop on Efficient Credit Assignment in Deep Learning and Deep Reinforement Learning, ICML 2018.
[ OpenReview,
Poster ]
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Unsupervised robust nonparametric learning of hidden community properties
Mikhail Langovoy, Akhilesh Gotmare, Martin Jaggi, Suvrit Sra
Mathematical Foundations of Computing 2 (2), 127-147
[ arXiv,
AIMS MFC journal ]
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Swarm and evolutionary computing algorithms for system identification and filter
design: A comprehensive review
Akhilesh Gotmare, Sankha Subhra Bhattacharjee, Rohan Patidar, Nithin V. George
Swarm and Evolutionary Computation, 32, 68-84.
[ Elsevier SWEC journal ]
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Nonlinear system identification using a cuckoo search optimized adaptive Hammerstein model
Akhilesh Gotmare, Rohan Patidar, Nithin V. George
Expert systems with applications, 42(5), 2538-2546.
[ Elsevier ESWA journal ]
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