# Zero-Shot Keyphrase Generation: Investigating Specialized Instructions and Multi-Sample Aggregation on Large Language Models

arXiv: https://arxiv.org/abs/2503.00597 · HTML: https://mlsanity.com/paper/2503.00597/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 34 of its 66 references that are in the map.
- First posted on arXiv 1 Mar 2025.

## Builds on (most cited first, 30 of 34)

- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [The Llama 3 Herd of Models](https://mlsanity.com/paper/2407.21783/) (2024)
- [LLaMA: Open and Efficient Foundation Language Models](https://mlsanity.com/paper/2302.13971/) (2023)
- [Self-Consistency Improves Chain of Thought Reasoning in Language Models](https://mlsanity.com/paper/2203.11171/) (2022)
- [Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone](https://mlsanity.com/paper/2404.14219/) (2024)
- [OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization](https://mlsanity.com/paper/2212.12017/) (2022)
- [SemEval 2017 Task 10: ScienceIE - Extracting Keyphrases and Relations from Scientific Publications](https://mlsanity.com/paper/1704.02853/) (2017)
- [Deep Keyphrase Generation](https://mlsanity.com/paper/1704.06879/) (2017)
- [Simple Unsupervised Keyphrase Extraction using Sentence Embeddings](https://mlsanity.com/paper/1801.04470/) (2018)
- [One Size Does Not Fit All: Generating and Evaluating Variable Number of Keyphrases](https://mlsanity.com/paper/1810.05241/) (2018)
- [Keyphrase Generation with Correlation Constraints](https://mlsanity.com/paper/1808.07185/) (2018)
- [Neural Keyphrase Generation via Reinforcement Learning with Adaptive Rewards](https://mlsanity.com/paper/1906.04106/) (2019)
- [KPTimes: A Large-Scale Dataset for Keyphrase Generation on News Documents](https://mlsanity.com/paper/1911.12559/) (2019)
- [One2Set: Generating Diverse Keyphrases as a Set](https://mlsanity.com/paper/2105.11134/) (2021)
- [Exclusive Hierarchical Decoding for Deep Keyphrase Generation](https://mlsanity.com/paper/2004.08511/) (2020)
- [Semi-Supervised Learning for Neural Keyphrase Generation](https://mlsanity.com/paper/1808.06773/) (2018)
- [Learning Rich Representation of Keyphrases from Text](https://mlsanity.com/paper/2112.08547/) (2021)
- [Keyphrase Generation for Scientific Document Retrieval](https://mlsanity.com/paper/2106.14726/) (2021)
- [Is ChatGPT A Good Keyphrase Generator? A Preliminary Study](https://mlsanity.com/paper/2303.13001/) (2023)
- [UniKeyphrase: A Unified Extraction and Generation Framework for Keyphrase Prediction](https://mlsanity.com/paper/2106.04847/) (2021)
- [Heterogeneous Graph Neural Networks for Keyphrase Generation](https://mlsanity.com/paper/2109.04703/) (2021)
- [Representation Learning for Resource-Constrained Keyphrase Generation](https://mlsanity.com/paper/2203.08118/) (2022)
- [Keyphrase Prediction With Pre-trained Language Model](https://mlsanity.com/paper/2004.10462/) (2020)
- [Pre-trained Language Models for Keyphrase Generation: A Thorough Empirical Study](https://mlsanity.com/paper/2212.10233/) (2022)
- [ChatGPT vs State-of-the-Art Models: A Benchmarking Study in Keyphrase Generation Task](https://mlsanity.com/paper/2304.14177/) (2023)
- [Keyphrase Extraction from Disaster-related Tweets](https://mlsanity.com/paper/1910.07897/) (2019)
- [Keyphrase Generation Beyond the Boundaries of Title and Abstract](https://mlsanity.com/paper/2112.06776/) (2021)
- [Data Augmentation for Low-Resource Keyphrase Generation](https://mlsanity.com/paper/2305.17968/) (2023)
- [Rethinking Model Selection and Decoding for Keyphrase Generation with Pre-trained Sequence-to-Sequence Models](https://mlsanity.com/paper/2310.06374/) (2023)
- [Conditional set generation using Seq2seq models](https://mlsanity.com/paper/2205.12485/) (2022)

## Abstract (arXiv)

Keyphrases are the essential topical phrases that summarize a document. Keyphrase generation is a long-standing NLP task for automatically generating keyphrases for a given document. While the task has been comprehensively explored in the past via various models, only a few works perform some preliminary analysis of Large Language Models (LLMs) for the task. Given the impact of LLMs in the field of NLP, it is important to conduct a more thorough examination of their potential for keyphrase generation. In this paper, we attempt to meet this demand with our research agenda. Specifically, we focus on the zero-shot capabilities of open-source instruction-tuned LLMs (Phi-3, Llama-3) and the closed-source GPT-4o for this task. We systematically investigate the effect of providing task-relevant specialized instructions in the prompt. Moreover, we design task-specific counterparts to self-consistency-style strategies for LLMs and show significant benefits from our proposals over the baselines.