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Wasi Ahmad

10 accepted papers

2024

CoCoMIC: Code Completion by Jointly Modeling In-file and Cross-file Context

Yangruibo Ding, Zijian Wang, Wasi Ahmad, Murali Krishna Ramanathan, Ramesh Nallapati, Parminder Bhatia +2
COLING 2024main

While pre-trained language models (LM) for code have achieved great success in code completion, they generate code conditioned only on the contents within the file, i.e., in-file context, but ignore the rich semantics in other files within the same project, i.e., project-level cross-file context, a…

Cited by 76Source ↗PDF ↗code ↗Scholar ↗
2024

On Leveraging Encoder-only Pre-trained Language Models for Effective Keyphrase Generation

Di Wu, Wasi Ahmad, Kai-Wei Chang
COLING 2024main

This study addresses the application of encoder-only Pre-trained Language Models (PLMs) in keyphrase generation (KPG) amidst the broader availability of domain-tailored encoder-only models compared to encoder-decoder models. We investigate three core inquiries: (1) the efficacy of encoder-only PLMs…

Cited by 2Source ↗PDF ↗code ↗Scholar ↗
2022

BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla

Abhik Bhattacharjee, Tahmid Hasan, Wasi Ahmad, Kazi Samin Mubasshir, Md Saiful Islam, Anindya Iqbal +2
NAACL 2022findings

In this work, we introduce BanglaBERT, a BERT-based Natural Language Understanding (NLU) model pretrained in Bangla, a widely spoken yet low-resource language in the NLP literature. To pretrain BanglaBERT, we collect 27.5 GB of Bangla pretraining data (dubbed ‘Bangla2B+’) by crawling 110 popular Ban…

Cited by 190Source ↗PDF ↗code ↗Scholar ↗
2022

Representation Learning for Resource-Constrained Keyphrase Generation

Di Wu, Wasi Ahmad, Sunipa Dev, Kai-Wei Chang
EMNLP 2022finding

State-of-the-art keyphrase generation methods generally depend on large annotated datasets, limiting their performance in domains with limited annotated data. To overcome this challenge, we design a data-oriented approach that first identifies salient information using retrieval-based corpus-level s…

Cited by 14Source ↗PDF ↗code ↗Scholar ↗
2021

Improving Zero-Shot Cross-Lingual Transfer Learning via Robust Training

Kuan-Hao Huang, Wasi Ahmad, Nanyun Peng, Kai-Wei Chang
EMNLP 2021main

Pre-trained multilingual language encoders, such as multilingual BERT and XLM-R, show great potential for zero-shot cross-lingual transfer. However, these multilingual encoders do not precisely align words and phrases across languages. Especially, learning alignments in the multilingual embedding sp…

Cited by 45Source ↗PDF ↗code ↗Scholar ↗
2021

Intent Classification and Slot Filling for Privacy Policies

Wasi Ahmad, Jianfeng Chi, Tu Le, Thomas Norton, Yuan Tian, Kai-Wei Chang
ACL 2021long

Understanding privacy policies is crucial for users as it empowers them to learn about the information that matters to them. Sentences written in a privacy policy document explain privacy practices, and the constituent text spans convey further specific information about that practice. We refer to p…

Cited by 35Source ↗PDF ↗code ↗Scholar ↗
2021

Retrieval Augmented Code Generation and Summarization

Md Rizwan Parvez, Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang
EMNLP 2021finding

Software developers write a lot of source code and documentation during software development. Intrinsically, developers often recall parts of source code or code summaries that they had written in the past while implementing software or documenting them. To mimic developers’ code or summary generati…

Cited by 190Source ↗PDF ↗code ↗Scholar ↗
2021

Select, Extract and Generate: Neural Keyphrase Generation with Layer-wise Coverage Attention

Wasi Ahmad, Xiao Bai, Soomin Lee, Kai-Wei Chang
ACL 2021long

Natural language processing techniques have demonstrated promising results in keyphrase generation. However, one of the major challenges in neural keyphrase generation is processing long documents using deep neural networks. Generally, documents are truncated before given as inputs to neural network…

Cited by 47Source ↗PDF ↗code ↗Scholar ↗
2021

Syntax-augmented Multilingual BERT for Cross-lingual Transfer

Wasi Ahmad, Haoran Li, Kai-Wei Chang, Yashar Mehdad
ACL 2021long

In recent years, we have seen a colossal effort in pre-training multilingual text encoders using large-scale corpora in many languages to facilitate cross-lingual transfer learning. However, due to typological differences across languages, the cross-lingual transfer is challenging. Nevertheless, lan…

Cited by 39Source ↗PDF ↗code ↗Scholar ↗
2021

Unified Pre-training for Program Understanding and Generation

Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang
NAACL 2021long

Code summarization and generation empower conversion between programming language (PL) and natural language (NL), while code translation avails the migration of legacy code from one PL to another. This paper introduces PLBART, a sequence-to-sequence model capable of performing a broad spectrum of pr…

Cited by 924Source ↗PDF ↗code ↗Scholar ↗