Ecomgpt: Instruction-tuning large language models with chain-of-task tasks for e-commerce
Recently, instruction-following Large Language Models (LLMs), represented by ChatGPT,
have exhibited exceptional performance in general Natural Language Processing (NLP) …
have exhibited exceptional performance in general Natural Language Processing (NLP) …
Towards multi-intent spoken language understanding via hierarchical attention and optimal transport
X Cheng, Z Zhu, H Li, Y Li, X Zhuang… - Proceedings of the AAAI …, 2024 - ojs.aaai.org
Multi-Intent spoken language understanding (SLU) can handle complicated utterances
expressing multiple intents, which has attracted increasing attention from researchers …
expressing multiple intents, which has attracted increasing attention from researchers …
Learning from the dictionary: Heterogeneous knowledge guided fine-tuning for chinese spell checking
Chinese Spell Checking (CSC) aims to detect and correct Chinese spelling errors. Recent
researches start from the pretrained knowledge of language models and take multimodal …
researches start from the pretrained knowledge of language models and take multimodal …
Vision, deduction and alignment: An empirical study on multi-modal knowledge graph alignment
Entity alignment (EA) for knowledge graphs (KGs) plays a critical role in knowledge
engineering. Existing EA methods mostly focus on utilizing the graph structures and entity …
engineering. Existing EA methods mostly focus on utilizing the graph structures and entity …
MESED: A multi-modal entity set expansion dataset with fine-grained semantic classes and hard negative entities
The Entity Set Expansion (ESE) task aims to expand a handful of seed entities with new
entities belonging to the same semantic class. Conventional ESE methods are based on …
entities belonging to the same semantic class. Conventional ESE methods are based on …
Active relation discovery: Towards general and label-aware open relation extraction
Abstract Open Relation Extraction (OpenRE) aims to discover novel relations from open
domains. Previous OpenRE methods mainly suffer from two problems:(1) Insufficient …
domains. Previous OpenRE methods mainly suffer from two problems:(1) Insufficient …
Automatic context pattern generation for entity set expansion
Entity Set Expansion (ESE) is a valuable task that aims to find entities of the target semantic
class described by given seed entities. Various Natural Language Processing (NLP) and …
class described by given seed entities. Various Natural Language Processing (NLP) and …
Towards real-world writing assistance: A chinese character checking benchmark with faked and misspelled characters
Writing assistance is an application closely related to human life and is also a fundamental
Natural Language Processing (NLP) research field. Its aim is to improve the correctness and …
Natural Language Processing (NLP) research field. Its aim is to improve the correctness and …
A Frustratingly Easy Plug-and-Play Detection-and-Reasoning Module for Chinese Spelling Check
In recent years, Chinese Spelling Check (CSC) has been greatly improved by designing
task-specific pre-training methods or introducing auxiliary tasks, which mostly solve this task …
task-specific pre-training methods or introducing auxiliary tasks, which mostly solve this task …
Embracing ambiguity: Improving similarity-oriented tasks with contextual synonym knowledge
Contextual synonym knowledge is crucial for those similarity-oriented tasks whose core
challenge lies in capturing semantic similarity between entities in their contexts, such as …
challenge lies in capturing semantic similarity between entities in their contexts, such as …