Copertina

State Space Models for Extractive Summarization in Low Resource Scenarios

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Khayi, Nisrine Ait
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computation and Language Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Efficient Extractive Summarization with MAMBA-Transformer Hybrids for Low-Resource Scenarios
di: Khayi, Nisrine Ait
Pubblicazione: (2026)

Unsupervised Extractive Dialogue Summarization in Hyperdimensional Space
di: Park, Seongmin, et al.
Pubblicazione: (2024)

Leveraging Discourse Structure for Extractive Meeting Summarization
di: Rennard, Virgile, et al.
Pubblicazione: (2024)

Fair Summarization: Bridging Quality and Diversity in Extractive Summaries
di: Nezhad, Sina Bagheri, et al.
Pubblicazione: (2024)

Towards Enhancing Coherence in Extractive Summarization: Dataset and Experiments with LLMs
di: Parmar, Mihir, et al.
Pubblicazione: (2024)

A New Sentence Extraction Strategy for Unsupervised Extractive Summarization Methods
di: Tao, Dehao, et al.
Pubblicazione: (2021)

Prompt-based Pseudo-labeling Strategy for Sample-Efficient Semi-Supervised Extractive Summarization
di: Sahu, Gaurav, et al.
Pubblicazione: (2023)

GraphLSS: Integrating Lexical, Structural, and Semantic Features for Long Document Extractive Summarization
di: Bugueño, Margarita, et al.
Pubblicazione: (2024)

Reliability Gated Multi-Teacher Distillation for Low Resource Abstractive Summarization
di: Sumit, Dipto, et al.
Pubblicazione: (2026)

Connecting Ideas in 'Lower-Resource' Scenarios: NLP for National Varieties, Creoles and Other Low-resource Scenarios
di: Joshi, Aditya, et al.
Pubblicazione: (2024)

Think Carefully and Check Again! Meta-Generation Unlocking LLMs for Low-Resource Cross-Lingual Summarization
di: Li, Zhecheng, et al.
Pubblicazione: (2024)

Towards Robust Extractive Question Answering Models: Rethinking the Training Methodology
di: Tran, Son Quoc, et al.
Pubblicazione: (2024)

A Guide To Effectively Leveraging LLMs for Low-Resource Text Summarization: Data Augmentation and Semi-supervised Approaches
di: Sahu, Gaurav, et al.
Pubblicazione: (2024)

Comparing Approaches to Automatic Summarization in Less-Resourced Languages
di: Palen-Michel, Chester, et al.
Pubblicazione: (2025)

Extractive Schema Linking for Text-to-SQL
di: Glass, Michael, et al.
Pubblicazione: (2025)

Domain-Specific Quality Estimation for Machine Translation in Low-Resource Scenarios
di: Gurav, Namrata Patil, et al.
Pubblicazione: (2026)

AdaComp: Extractive Context Compression with Adaptive Predictor for Retrieval-Augmented Large Language Models
di: Zhang, Qianchi, et al.
Pubblicazione: (2024)

`Keep it Together': Enforcing Cohesion in Extractive Summaries by Simulating Human Memory
di: Cardenas, Ronald, et al.
Pubblicazione: (2024)

Information Extraction in Low-Resource Scenarios: Survey and Perspective
di: Deng, Shumin, et al.
Pubblicazione: (2022)

Low-Resource Court Judgment Summarization for Common Law Systems
di: Liu, Shuaiqi, et al.
Pubblicazione: (2024)

Abstractive Summarization of Low resourced Nepali language using Multilingual Transformers
di: Dhakal, Prakash, et al.
Pubblicazione: (2024)

From Multiple-Choice to Extractive QA: A Case Study for English and Arabic
di: Lynn, Teresa, et al.
Pubblicazione: (2024)

Learning to Prioritize IT Tickets: A Comparative Evaluation of Embedding-based Approaches and Fine-Tuned Transformer Models
di: LÊ, Minh Tri, et al.
Pubblicazione: (2025)

Speech LLMs in Low-Resource Scenarios: Data Volume Requirements and the Impact of Pretraining on High-Resource Languages
di: Fong, Seraphina, et al.
Pubblicazione: (2025)

PreSumm: Predicting Summarization Performance Without Summarizing
di: Koniaev, Steven, et al.
Pubblicazione: (2025)

Unlocking the Potential of Model Merging for Low-Resource Languages
di: Tao, Mingxu, et al.
Pubblicazione: (2024)

SEMQA: Semi-Extractive Multi-Source Question Answering
di: Schuster, Tal, et al.
Pubblicazione: (2023)

Unraveling the Capabilities of Language Models in News Summarization
di: Odabaşı, Abdurrahman, et al.
Pubblicazione: (2025)

Polysemanticity or Polysemy? Lexical Identity Confounds Superposition Metrics
di: Hou, Iyad Ait, et al.
Pubblicazione: (2026)

Beyond Black-Box Labels: Interpretable Criteria for Diagnosing Subjective NLP Tasks
di: Rair, Nisrine, et al.
Pubblicazione: (2026)

Teaching-Assistant-in-the-Loop: Improving Knowledge Distillation from Imperfect Teacher Models in Low-Budget Scenarios
di: Zhou, Yuhang, et al.
Pubblicazione: (2024)

Low-Rank Adaptation for Multilingual Summarization: An Empirical Study
di: Whitehouse, Chenxi, et al.
Pubblicazione: (2023)

Exploring Iterative Controllable Summarization with Large Language Models
di: Ryu, Sangwon, et al.
Pubblicazione: (2024)

Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing
di: Jung, Jaehun, et al.
Pubblicazione: (2023)

Continual-learning for Modelling Low-Resource Languages from Large Language Models
di: K, Santosh Srinath, et al.
Pubblicazione: (2026)

An Adapter-Based Unified Model for Multiple Spoken Language Processing Tasks
di: Suresh, Varsha, et al.
Pubblicazione: (2024)

Generating Query-Focused Summarization Datasets from Query-Free Summarization Datasets
di: Chali, Yllias, et al.
Pubblicazione: (2026)

Leveraging Large Language Models for Accurate Sign Language Translation in Low-Resource Scenarios
di: Bulla, Luana, et al.
Pubblicazione: (2025)

LLMs for Translation: Historical, Low-Resourced Languages and Contemporary AI Models
di: Tekgurler, Merve
Pubblicazione: (2025)

An Empirical Study of Many-to-Many Summarization with Large Language Models
di: Wang, Jiaan, et al.
Pubblicazione: (2025)