Search Results for author:
Found 8 papers, 5 papers with code
How Do Seq2Seq Models Perform on End-to-End Data-to-Text Generation?
With the rapid development of deep learning, Seq2Seq paradigm has become prevalent for end-to-end data-to-text generation, and the BLEU scores have been increasing in recent years.
EAMA : Entity-Aware Multimodal Alignment Based Approach for News Image Captioning
News image captioning requires model to generate an informative caption rich in entities, with the news image and the associated news article.
Benchmarking Knowledge Boundary for Large Language Model: A Different Perspective on Model Evaluation
In recent years, substantial advancements have been made in the development of large language models, achieving remarkable performance across diverse tasks.
History Matters: Temporal Knowledge Editing in Large Language Model
The imperative task of revising or updating the knowledge stored within large language models arises from two distinct sources: intrinsic errors inherent in the model which should be corrected and outdated knowledge due to external shifts in the real world which should be updated.
ALCUNA: Large Language Models Meet New Knowledge
With the rapid development of NLP, large-scale language models (LLMs) excel in various tasks across multiple domains now.
A Comprehensive Evaluation and Analysis Study for Chinese Spelling Check
With the development of pre-trained models and the incorporation of phonetic and graphic information, neural models have achieved high scores in Chinese Spelling Check (CSC).
Human-like Summarization Evaluation with ChatGPT
Evaluating text summarization is a challenging problem, and existing evaluation metrics are far from satisfactory.
Error-Robust Retrieval for Chinese Spelling Check
Chinese Spelling Check (CSC) aims to detect and correct error tokens in Chinese contexts, which has a wide range of applications.
