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Akhilesh Deepak Gotmare

3 accepted papers

2023

CodeT5+: Open Code Large Language Models for Code Understanding and Generation

EMNLP 2023long main

Large language models (LLMs) pretrained on vast source code have achieved prominent progress in code intelligence. However, existing code LLMs have two main limitations. First, they often adopt a specific architecture (encoder-only or decoder-only) or rely on a unified encoder-decoder network for d…

Cited by 0SourcecodeScholar
2022

CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning

NeurIPS 2022accept

Program synthesis or code generation aims to generate a program that satisfies a problem specification. Recent approaches using large-scale pretrained language models (LMs) have shown promising results, yet they have some critical limitations. In particular, they often follow a standard supervised f…

2021

Align before Fuse: Vision and Language Representation Learning with Momentum Distillation

NeurIPS 2021spotlight

Large-scale vision and language representation learning has shown promising improvements on various vision-language tasks. Most existing methods employ a transformer-based multimodal encoder to jointly model visual tokens (region-based image features) and word tokens. Because the visual tokens and w…