Tagged articles

Knowledge Integration

11 articles · Page 1 of 1

Jun 17, 2026 · Artificial Intelligence

How a 1.5B Parameter Model Can Add External Knowledge to Any Frozen LLM

The article analyzes MEMO, a framework that equips a frozen large language model with a lightweight 1.5B‑parameter memory model fine‑tuned on a target corpus, detailing its architecture, five‑step data synthesis pipeline, structured inference protocol, experimental advantages over RAG and fine‑tuning, as well as its limitations and future research directions.

Knowledge IntegrationLLMMemory Model

0 likes · 19 min read

How a 1.5B Parameter Model Can Add External Knowledge to Any Frozen LLM

AsiaInfo Technology: New Tech Exploration

Oct 10, 2025 · Artificial Intelligence

How Ontologies Boost Large Language Models: A Comprehensive Review

This review examines how formal knowledge representations (ontologies) can be integrated with large language models to enhance reasoning, reduce hallucinations, and improve factual reliability, outlining three roles—information provider, reasoner, validator—while analyzing recent frameworks, open‑source projects, and future research challenges.

AIKnowledge IntegrationOntology

0 likes · 29 min read

How Ontologies Boost Large Language Models: A Comprehensive Review

AI Frontier Lectures

Jul 2, 2025 · Artificial Intelligence

Can Language Models Self‑Edit? Inside the SEAL Framework for Self‑Adapting LLMs

This article reviews recent AI self‑evolution research and provides an in‑depth analysis of the SEAL (Self‑Adapting Language) framework, which enables large language models to generate and learn from their own synthetic data through a nested reinforcement‑learning and fine‑tuning loop, with experimental results on few‑shot and knowledge‑integration tasks.

Knowledge IntegrationMeta LearningSEAL

0 likes · 11 min read

Can Language Models Self‑Edit? Inside the SEAL Framework for Self‑Adapting LLMs

DataFunSummit

Sep 20, 2024 · Artificial Intelligence

Exploring and Applying Large Language Models in Recommendation Systems

Professor Wang Yichao from Huawei Noah's Ark Lab presents a comprehensive exploration of large language models in recommendation systems, covering background, challenges, two key projects (LLM4Rec and Uni-CTR), experimental results, and future directions for open, knowledge‑enhanced, generative recommendation pipelines.

AIKnowledge IntegrationLLM4Rec

0 likes · 13 min read

Exploring and Applying Large Language Models in Recommendation Systems

DataFunTalk

Jan 15, 2023 · Artificial Intelligence

Advances in Dialogue Systems: Baidu PLATO Large‑Scale Conversational Models

This article reviews the evolution of dialogue systems from modular task‑oriented designs to end‑to‑end large‑scale models, detailing Baidu's PLATO series, their technical innovations, real‑world deployments, challenges such as inference efficiency and safety, and future research directions in conversational AI.

AI safetyConversational AIDialogue Systems

0 likes · 13 min read

Advances in Dialogue Systems: Baidu PLATO Large‑Scale Conversational Models

DataFunTalk

Dec 1, 2022 · Artificial Intelligence

Advances and Challenges in Controllable Text Generation with Pretrained Language Models

This report reviews the background, recent research progress, practical applications, and future directions of controllable text generation using transformer‑based pretrained language models, highlighting methods such as decoding strategies, prompt learning, memory networks, continual learning, contrastive training, and knowledge integration.

Continual LearningKnowledge Integrationcontrastive training

0 likes · 13 min read

Advances and Challenges in Controllable Text Generation with Pretrained Language Models

DataFunSummit

Jul 18, 2022 · Artificial Intelligence

Advances in Natural Language Generation: ProphetNet, Knowledge‑Enhanced Generation, Non‑Autoregressive Pre‑training, Long‑Text Modeling, and Efficient Attention

This talk presents recent year’s research on natural language generation, covering the ProphetNet pre‑trained generation model, external‑knowledge integration for generation, non‑autoregressive pre‑training (BANG), the Poolingformer long‑text architecture, EL‑attention for faster decoding, and a new multi‑task generation benchmark.

Efficient AttentionKnowledge Integrationlong‑text modeling

0 likes · 22 min read

Advances in Natural Language Generation: ProphetNet, Knowledge‑Enhanced Generation, Non‑Autoregressive Pre‑training, Long‑Text Modeling, and Efficient Attention

DataFunTalk

Nov 5, 2021 · Artificial Intelligence

End-to-End Entity Extraction for Tmall Genie: Speech2Slot Model and Unsupervised Pre‑Training

This article presents the business background of Tmall Genie’s voice‑driven content‑on‑demand service, critiques the traditional pipeline for entity extraction, and details an end‑to‑end speech‑semantic model—including the Speech2Slot architecture, knowledge‑enhanced encoding, and Phoneme‑BERT unsupervised pre‑training—demonstrating significant performance gains in both generation and classification tasks.

Knowledge IntegrationVoice Assistantend-to-end model

0 likes · 14 min read

End-to-End Entity Extraction for Tmall Genie: Speech2Slot Model and Unsupervised Pre‑Training

JD Tech

Feb 2, 2021 · Artificial Intelligence

Advances and Trends in Multimodal Digital Content Generation and Automatic Text Summarization

The article reviews recent research on multimodal digital content generation and automatic text summarization, outlining the evolution from extractive to abstractive methods, highlighting four key technology trends such as pretrained language models, transformer dominance, knowledge‑enhanced generation, and multimodal‑knowledge joint modeling, and describing an industrial e‑commerce application built on these advances.

Knowledge IntegrationMultimodal AIe-commerce

0 likes · 12 min read

Advances and Trends in Multimodal Digital Content Generation and Automatic Text Summarization

DataFunTalk

Apr 16, 2020 · Artificial Intelligence

Comprehensive Survey of Pre-trained Models for Natural Language Processing

This article provides a detailed survey of pre‑trained models (PTMs) for natural language processing, classifying them into shallow embeddings and contextual encoders, discussing training paradigms such as knowledge integration and model compression, and offering guidance on transfer learning and future challenges.

Knowledge IntegrationPretrained Modelsmodel compression

0 likes · 25 min read

Comprehensive Survey of Pre-trained Models for Natural Language Processing

Alibaba Cloud Developer

Nov 7, 2019 · Artificial Intelligence

Boosting Task-Oriented Dialogue with Heterogeneous Memory Networks

This paper introduces Heterogeneous Memory Networks (HMNs), combining context‑free and context‑aware memory modules to jointly process user queries, dialogue history, and knowledge bases, achieving state‑of‑the‑art performance on three task‑oriented dialogue datasets in both BLEU and F1 metrics.

Dialogue SystemsKnowledge Integrationmemory networks

0 likes · 17 min read

Boosting Task-Oriented Dialogue with Heterogeneous Memory Networks