Shafiq Joty

ConvKN at SemEval-2016 Task 3: Answer and Question Selection for Question Answering on Arabic and English Fora

2016

Alberto Barrón-Cedeño, Daniele Bonadiman, Giovanni Da San Martino, Shafiq Joty, Alessandro Moschitti, Fahad Al Obaidli, Salvatore Romeo, Kateryna Tymoshenko, Antonio Uva. Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016). 2016.

CohEval: Benchmarking Coherence Models

2020 · arXiv (Cornell University)

Although coherence modeling has come a long way in developing novel models, their evaluation on downstream applications has largely been neglected. With the advancements made by neural approaches in applications such as machine translation, text …

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Pre-trained models for Natural Languages (NL) like BERT and GPT have been recently shown to transfer well to Programming Languages (PL) and largely benefit a broad set of code-related tasks. Despite their success, most current …

GeDi: Generative Discriminator Guided Sequence Generation

2020 · arXiv (Cornell University)

While large-scale language models (LMs) are able to imitate the distribution of natural language well enough to generate realistic text, it is difficult to control which regions of the distribution they generate. This is especially …

Towards Summary Candidates Fusion

2022 · arXiv (Cornell University)

Sequence-to-sequence deep neural models fine-tuned for abstractive summarization can achieve great performance on datasets with enough human annotations. Yet, it has been shown that they have not reached their full potential, with a wide gap …

A Data-centric Framework for Improving Domain-specific Machine Reading Comprehension Datasets

2023 · arXiv (Cornell University)

Low-quality data can cause downstream problems in high-stakes applications. Data-centric approach emphasizes on improving dataset quality to enhance model performance. High-quality datasets are needed for general-purpose Large Language Models (LLMs) training, as well as for …

Modeling What-to-ask and How-to-ask for Answer-unaware Conversational Question Generation

2023 · arXiv (Cornell University)

Conversational Question Generation (CQG) is a critical task for machines to assist humans in fulfilling their information needs through conversations. The task is generally cast into two different settings: answer-aware and answer-unaware. While the former …

Contrastive Learning with Generated Representations for Inductive Knowledge Graph Embedding

2023

With the evolution of Knowledge Graphs (KGs), new entities emerge which are not seen before. Representation learning of KGs in such an inductive setting aims to capture and transfer the structural patterns from existing entities …

PromptSum: Parameter-Efficient Controllable Abstractive Summarization

2023 · arXiv (Cornell University)

Prompt tuning (PT), a parameter-efficient technique that only tunes the additional prompt embeddings while keeping the backbone pre-trained language model (PLM) frozen, has shown promising results in language understanding tasks, especially in low-resource scenarios. However, …

Benchmarking Generation and Evaluation Capabilities of Large Language Models for Instruction Controllable Summarization

2023 · arXiv (Cornell University)

While large language models (LLMs) can already achieve strong performance on standard generic summarization benchmarks, their performance on more complex summarization task settings is less studied. Therefore, we benchmark LLMs on instruction controllable text summarization, …

ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?

2023 · arXiv (Cornell University)

Upon its release in late 2022, ChatGPT has brought a seismic shift in the entire landscape of AI, both in research and commerce. Through instruction-tuning a large language model (LLM) with supervised fine-tuning and reinforcement …

On Positional Bias of Faithfulness for Long-form Summarization

2025

David Wan, Jesse Vig, Mohit Bansal, Shafiq Joty. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). 2025.

SegBot: A Generic Neural Text Segmentation Model with Pointer Network

2018

Text segmentation is a fundamental task in natural language processing that comes in two levels of granularity: (i) segmenting a document into a sequence of topical segments (topic segmentation), and (ii) segmenting a sentence into …

ANR

2018

Textual reviews, which are readily available on many e-commerce and review websites such as Amazon and Yelp, serve as an invaluable source of information for recommender systems. However, not all parts of the reviews are …

GeDi: Generative Discriminator Guided Sequence Generation

2021

Ben Krause, Akhilesh Deepak Gotmare, Bryan McCann, Nitish Shirish Keskar, Shafiq Joty, Richard Socher, Nazneen Fatema Rajani. Findings of the Association for Computational Linguistics: EMNLP 2021. 2021.

Is GPT-3 a Good Data Annotator?

2023

Bosheng Ding, Chengwei Qin, Linlin Liu, Yew Ken Chia, Boyang Li, Shafiq Joty, Lidong Bing. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2023.