Prompt-Based Reinforcement Learning for Next Item Recommendation Systems

Prompt-Based Reinforcement Learning for Next Item Recommendation Systems

Introduction The Next item recommendation system is one of the core components of modern online services, embedded in applications such as music, video, and e-commerce websites, helping users navigate and discover new content. Generally, the system is modeled as a sequence prediction task, often implemented over recurrent neural networks or other generative sequence models. Its … Read more

Integrating Knowledge into Text Classification with KPT

Integrating Knowledge into Text Classification with KPT

Source: TsinghuaNLP, Deep Learning Natural Language Processing This article is about 2400 words long and is recommended to be read in 5 minutes. This article uses a knowledge base to expand and improve label words, achieving better text classification results. Background Using Prompt Learning for text classification tasks is an emerging method that leverages pre-trained … Read more

PromptCLUE: Large-Scale Multi-Task Prompt Pre-Trained Chinese Open Source Model

PromptCLUE: Large-Scale Multi-Task Prompt Pre-Trained Chinese Open Source Model

MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP master’s and PhD students, university teachers, and corporate researchers. The vision of the community is to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning at home and abroad, … Read more

CMU Liu Pengfei: The Fourth Paradigm of NLP

CMU Liu Pengfei: The Fourth Paradigm of NLP

Written by | Liu Pengfei Edited by | Jia Wei Source | AI Technology Review In the past two years, the research paradigm based on pre-training + fine-tuning has rapidly swept the entire field of NLP. This research paradigm is widely recognized as a revolutionary paradigm in NLP research, with previous paradigms including “expert systems,” … Read more

An Overview of Prompt Learning Techniques

An Overview of Prompt Learning Techniques

MLNLP Community is a well-known machine learning and natural language processing community at home and abroad, covering NLP master’s and doctoral students, university teachers, and corporate researchers. Community Vision is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning at home and abroad, especially for the … Read more

Prompt Learning Models for Collaborative Problem Solving

Prompt Learning Models for Collaborative Problem Solving

Results Introduction πŸ’‘ Paper Title: Application of Prompt Learning Models in Identifying the Collaborative Problem Solving Skills in an Online Task. πŸ“š Journal: Computer-Supported Cooperative Work and Social Computing (CSCW), 2024 πŸ”— Paper Link: http://arxiv.org/abs/2407.12487 1. Background and Motivation Collaborative abilities, innovation capabilities, communication skills, and critical thinking are recognized as core skills that individuals … Read more

Prompt Learning in Recommender Systems

Prompt Learning in Recommender Systems

MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP master’s and doctoral students, university teachers, and corporate researchers. The vision of the community is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning, especially for beginners. Source: … Read more

Prompt-Based Contrastive Learning for Sentence Representation

Prompt-Based Contrastive Learning for Sentence Representation

This article is approximately 1100 words long and is recommended to be read in 5 minutes. This article proposes using prompts to capture sentence representations. Although language models like BERT have achieved significant results, they still perform poorly in terms of sentence embeddings due to issues of sentence bias and anisotropy; We found that using … Read more

In-Depth Guide to Prompt Learning and Tuning

In-Depth Guide to Prompt Learning and Tuning

MLNLP community is a well-known machine learning and natural language processing community in China and abroad, targeting NLP graduate students, university teachers, and corporate researchers. The vision of the community is to promote communication and progress between the academia and industry of natural language processing and machine learning, especially for the advancement of beginners. Reprinted … Read more

Has Prompt Tuning Surpassed Fine Tuning?

Has Prompt Tuning Surpassed Fine Tuning?

MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP graduate and doctoral students, university teachers, and corporate researchers. The community’s vision is to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning, especially for beginners. Reprinted from | … Read more