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Found 13 papers, 6 papers with code
A Preliminary Empirical Study on Prompt-based Unsupervised Keyphrase Extraction
Pre-trained large language models can perform natural language processing downstream tasks by conditioning on human-designed prompts.
Counting-Stars: A Multi-evidence, Position-aware, and Scalable Benchmark for Evaluating Long-Context Large Language Models
While recent research endeavors have focused on developing Large Language Models (LLMs) with robust long-context capabilities, due to the lack of long-context benchmarks, relatively little is known about how well the performance of long-context LLMs.
Large Language Models as Zero-Shot Keyphrase Extractors: A Preliminary Empirical Study
Zero-shot keyphrase extraction aims to build a keyphrase extractor without training by human-annotated data, which is challenging due to the limited human intervention involved.
Revitalizing Legacy Video Content: Deinterlacing with Bidirectional Information Propagation
Our proposed method supports bidirectional spatio-temporal information propagation across multiple scales to leverage information in both space and time.
Recognizable Information Bottleneck
The recent PAC-Bayes IB uses information complexity instead of information compression to establish a connection with the mutual information generalization bound.
Is ChatGPT A Good Keyphrase Generator? A Preliminary Study
Based on our findings, we conclude that ChatGPT has great potential for keyphrase generation.
A Generative Model for Digital Camera Noise Synthesis
To this end, we propose an effective generative model which utilizes clean features as guidance followed by noise injections into the network.
Hyperbolic Relevance Matching for Neural Keyphrase Extraction
Meanwhile, considering the hierarchical structure hidden in the document, HyperMatch embeds both phrases and documents in the same hyperbolic space via a hyperbolic phrase encoder and a hyperbolic document encoder.
Topic-Aware Encoding for Extractive Summarization
Specifically, a neural topic model is added in the neural-based sentence-level representation learning to adequately consider the central topic information for capturing the critical content in the original document.
Reinforcing Semantic-Symmetry for Document Summarization
Among them, the extractor identifies the salient sentences from the input document, and the abstractor generates a summary from the salient sentences.
Reinforced Abstractive Summarization with Adaptive Length Controlling
Document summarization, as a fundamental task in natural language generation, aims to generate a short and coherent summary for a given document.
Importance Estimation from Multiple Perspectives for Keyphrase Extraction
Keyphrase extraction is a fundamental task in Natural Language Processing, which usually contains two main parts: candidate keyphrase extraction and keyphrase importance estimation.
Does Head Label Help for Long-Tailed Multi-Label Text Classification
To address the challenge of insufficient training data on tail label classification, we propose a Head-to-Tail Network (HTTN) to transfer the meta-knowledge from the data-rich head labels to data-poor tail labels.
