Search Results for author:
Found 12 papers, 5 papers with code
eC-Tab2Text: Aspect-Based Text Generation from e-Commerce Product Tables
Large Language Models (LLMs) have demonstrated exceptional versatility across diverse domains, yet their application in e-commerce remains underexplored due to a lack of domain-specific datasets.
LFOSum: Summarizing Long-form Opinions with Large Language Models
Traditional opinion summarization models face challenges in handling long inputs and large volumes of reviews, while newer Large Language Model (LLM) approaches often fail to generate accurate and faithful summaries.
KidLM: Advancing Language Models for Children -- Early Insights and Future Directions
Recent studies highlight the potential of large language models in creating educational tools for children, yet significant challenges remain in maintaining key child-specific properties such as linguistic nuances, cognitive needs, and safety standards.
XL-HeadTags: Leveraging Multimodal Retrieval Augmentation for the Multilingual Generation of News Headlines and Tags
Millions of news articles published online daily can overwhelm readers.
Are Large Vision Language Models up to the Challenge of Chart Comprehension and Reasoning? An Extensive Investigation into the Capabilities and Limitations of LVLMs
To bridge the gap, this paper presents the first comprehensive evaluation of the recently developed large vision language models (LVLMs) for chart understanding and reasoning tasks.
BenLLMEval: A Comprehensive Evaluation into the Potentials and Pitfalls of Large Language Models on Bengali NLP
Large Language Models (LLMs) have emerged as one of the most important breakthroughs in NLP for their impressive skills in language generation and other language-specific tasks.
Abstractive Text Summarization
Natural Language Inference
+6
On the Role of Reviewer Expertise in Temporal Review Helpfulness Prediction
Helpful reviews have been essential for the success of e-commerce services, as they help customers make quick purchase decisions and benefit the merchants in their sales.
Unsupervised Abstractive Summarization of Bengali Text Documents
We also provide a human-annotated dataset with document-summary pairs to evaluate our abstractive model and to support the comparison of future abstractive summarization systems of the Bengali Language.
Simple or Complex? Learning to Predict Readability of Bengali Texts
Determining the readability of a text is the first step to its simplification.
Abstractive Unsupervised Multi-Document Summarization using Paraphrastic Sentence Fusion
Furthermore, we apply our sentence level model to implement an abstractive multi-document summarization system where documents usually contain a related set of sentences.
Towards Abstractive Multi-Document Summarization Using Submodular Function-Based Framework, Sentence Compression and Merging
We propose a submodular function-based summarization system which integrates three important measures namely importance, coverage, and non-redundancy to detect the important sentences for the summary.
Extract with Order for Coherent Multi-Document Summarization
In this work, we aim at developing an extractive summarizer in the multi-document setting.
