knowledge hallucination

Alimama Tech

Oct 18, 2023 · Artificial Intelligence

Technical Challenges and Directions for Large‑Model Applications in E‑commerce

Taobao Group’s ten large‑model challenges target e‑commerce AI by demanding domain‑specific pre‑training, multi‑step reasoning, extended context handling, factual reliability, intelligent tool orchestration, robust retrieval integration, fuzzy‑intent tool selection, scalable multi‑objective RLHF, improved query rewriting, and knowledge‑driven recommendation.

E-commerceLarge Language ModelsRLHF

0 likes · 16 min read

Technical Challenges and Directions for Large‑Model Applications in E‑commerce

DaTaobao Tech

Oct 18, 2023 · Artificial Intelligence

Large Model Application Challenges for E-commerce

Taobao Group’s ten large‑model e‑commerce challenges call for researchers to build domain‑specific data pipelines, mitigate forgetting, balance expertise with generality, enable multi‑step reasoning, handle long contexts, reduce hallucinations, integrate tool use, improve fuzzy intent detection, apply multi‑objective RLHF, and generate cognitively novel recommendations.

E-commerceLarge Language ModelsRLHF

0 likes · 14 min read

Large Model Application Challenges for E-commerce

DataFunSummit

Sep 23, 2023 · Artificial Intelligence

Personalized Large Models: Technical Practice, Challenges, and Future Directions

This article presents a comprehensive overview of personalized large models, covering their definition, four‑fold capabilities (knowledge, personality, emotion, memory), practical applications, challenges such as knowledge hallucination, retrieval‑augmented solutions, and detailed discussions on persona consistency and controllable language style.

AI dialogue systemsknowledge hallucinationlanguage style control

0 likes · 13 min read

Personalized Large Models: Technical Practice, Challenges, and Future Directions