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Found 26 papers, 8 papers with code
Text Graph Transformer for Document Classification
Text classification is a fundamental problem in natural language processing.
DomainSum: A Hierarchical Benchmark for Fine-Grained Domain Shift in Abstractive Text Summarization
Most research on abstractive summarization focuses on single-domain applications, often neglecting how domain shifts between documents affect performance and the generalization ability of summarization models.
A Structure-aware Generative Model for Biomedical Event Extraction
In this paper, we propose an event structure-aware generative model named GenBEE, which can capture complex event structures in biomedical text for biomedical event extraction.
Intermediate Distillation: Data-Efficient Distillation from Black-Box LLMs for Information Retrieval
Moreover, our distilled retriever model significantly boosts performance in question-answering tasks within the RAG framework, demonstrating the potential of LLMs to economically and effectively train smaller models.
A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Models
Text summarization research has undergone several significant transformations with the advent of deep neural networks, pre-trained language models (PLMs), and recent large language models (LLMs).
MIPI 2024 Challenge on Nighttime Flare Removal: Methods and Results
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems.
Unveiling the Magic: Investigating Attention Distillation in Retrieval-augmented Generation
Retrieval-augmented generation framework can address the limitations of large language models by enabling real-time knowledge updates for more accurate answers.
A Revisit of Fake News Dataset with Augmented Fact-checking by ChatGPT
The proliferation of fake news has emerged as a critical issue in recent years, requiring significant efforts to detect it.
Convolution and Attention Mixer for Synthetic Aperture Radar Image Change Detection
In this letter, we explore Transformer-like architecture for SAR change detection to incorporate global attention.
XATU: A Fine-grained Instruction-based Benchmark for Explainable Text Updates
Text editing is a crucial task of modifying text to better align with user intents.
Unsupervised Multi-document Summarization with Holistic Inference
SRI balances the importance and diversity of a subset of sentences from the source documents and can be calculated in unsupervised and adaptive manners.
Contrastive Hierarchical Discourse Graph for Scientific Document Summarization
The extended structural context has made scientific paper summarization a challenging task.
SummIt: Iterative Text Summarization via ChatGPT
Text summarization systems have made significant progress in recent years, but typically generate summaries in one single step.
DiffuSum: Generation Enhanced Extractive Summarization with Diffusion
This paper proposes DiffuSum, a novel paradigm for extractive summarization, by directly generating the desired summary sentence representations with diffusion models and extracting sentences based on sentence representation matching.
Extractive Summarization via ChatGPT for Faithful Summary Generation
In addition, we explore the effectiveness of in-context learning and chain-of-thought reasoning for enhancing its performance.
HEGEL: Hypergraph Transformer for Long Document Summarization
Extractive summarization for long documents is challenging due to the extended structured input context.
A Rotation Meanout Network with Invariance for Dermoscopy Image Classification and Retrieval
As such they have made great improvements in many tasks of dermoscopy images.
Improving the Faithfulness of Abstractive Summarization via Entity Coverage Control
Abstractive summarization systems leveraging pre-training language models have achieved superior results on benchmark datasets.
Histopathology WSI Encoding based on GCNs for Scalable and Efficient Retrieval of Diagnostically Relevant Regions
While, it is challenging and yet significant in clinical applications to retrieve diagnostically relevant regions from a database that consists of histopathological whole slide images (WSIs) for a query ROI.
Centrality Meets Centroid: A Graph-based Approach for Unsupervised Document Summarization
Unsupervised document summarization has re-acquired lots of attention in recent years thanks to its simplicity and data independence.
High-α-Metal-Rich stars in the LAMOST-MRS survey and its connection with the galactic bulge
A tentative interpretation of this special group is that its stars were formed in the X-shaped bar/bulge region, close to its corotation radius, where radial migration is the most intense, and brings them to present locations at 9 kpc and beyond.
Astrophysics of Galaxies Solar and Stellar Astrophysics
Graph-Bert: Only Attention is Needed for Learning Graph Representations
We have tested the effectiveness of GRAPH-BERT on several graph benchmark datasets.
Ranked #30 on
Node Classification
on Cora
Factorization of View-Object Manifolds for Joint Object Recognition and Pose Estimation
Due to large variations in shape, appearance, and viewing conditions, object recognition is a key precursory challenge in the fields of object manipulation and robotic/AI visual reasoning in general.
Shape Primitive Histogram: A Novel Low-Level Face Representation for Face Recognition
We further exploit the representational power of Haar wavelet and present a novel low-level face representation named Shape Primitives Histogram (SPH) for face recognition.
Semistability-Based Convergence Analysis for Paracontracting Multiagent Coordination Optimization
This sequential technical report extends some of the previous results we posted at arXiv:1306. 0225.
Convergence Analysis and Parallel Computing Implementation for the Multiagent Coordination Optimization Algorithm
In this report, a novel variation of Particle Swarm Optimization (PSO) algorithm, called Multiagent Coordination Optimization (MCO), is implemented in a parallel computing way for practical use by introducing MATLAB built-in function "parfor" into MCO.
