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JD Tech

Nov 12, 2024 · Artificial Intelligence

Prompt Engineering: Concepts, Evolution, Techniques, and JD Logistics Application

This article explains what Prompt Engineering is, traces its development from early NLP commands to modern adaptive and multimodal prompting techniques, describes various prompting strategies such as Zero‑shot, Few‑shot, Chain‑of‑Thought, Auto‑CoT, and showcases a JD Logistics case study using these methods to classify product types with code examples.

AI Prompt DesignChain-of-ThoughtPrompt Engineering

0 likes · 27 min read

Prompt Engineering: Concepts, Evolution, Techniques, and JD Logistics Application

Xiaohongshu Tech REDtech

Feb 27, 2024 · Artificial Intelligence

InstantID: Zero-shot Identity-Preserving Generation in Seconds

InstantID, an open‑source tool released by Xiaohongshu in early 2024, generates multiple stylized portraits that preserve a person’s facial identity from a single reference photo in seconds, eliminating fine‑tuning, large storage needs, and multi‑image requirements while seamlessly working with popular diffusion models like Stable Diffusion 1.5 and SDXL.

AIInstantIDZero-shot

0 likes · 6 min read

InstantID: Zero-shot Identity-Preserving Generation in Seconds

Rare Earth Juejin Tech Community

Jul 30, 2023 · Artificial Intelligence

ChatGPT Technical Analysis Series – Part 2: GPT1, GPT2, and GPT3 (Encoder vs Decoder, Zero‑Shot, and Scaling)

This article reviews the evolution of the GPT family from GPT‑1 to GPT‑3, comparing encoder‑decoder architectures, explaining the shift from supervised fine‑tuning to zero‑shot and few‑shot learning, and highlighting the architectural and training innovations that enabled large‑scale language models.

Artificial IntelligenceFine-tuningGPT

0 likes · 13 min read

ChatGPT Technical Analysis Series – Part 2: GPT1, GPT2, and GPT3 (Encoder vs Decoder, Zero‑Shot, and Scaling)

DataFunTalk

Jun 21, 2023 · Artificial Intelligence

Low‑Resource NLP Pretraining: Methodology, Experiments, and Zero‑Shot Applications

This article presents a low‑resource NLP pretraining approach that combines transformer‑based language modeling with contrastive vector learning, details the unsupervised sample‑pair construction, introduces a camel‑shaped masking distribution, and demonstrates through extensive experiments that the resulting model achieves strong zero‑shot NLU, NLG, and retrieval performance while requiring minimal compute and data.

NLPPretrainingTransformer

0 likes · 10 min read

Low‑Resource NLP Pretraining: Methodology, Experiments, and Zero‑Shot Applications

ByteFE

Jun 15, 2023 · Artificial Intelligence

Effective Prompt Engineering: Techniques, Prompt Injection Prevention, Hallucination Mitigation, and Advanced Prompting Strategies

This article explains how to craft efficient prompts by combining clear instructions and questions, discusses prompt injection risks and mitigation with delimiters, addresses hallucinations, and introduces zero‑shot, few‑shot, and chain‑of‑thought prompting techniques for large language models.

Chain-of-ThoughtLLMPrompt Engineering

0 likes · 16 min read

Effective Prompt Engineering: Techniques, Prompt Injection Prevention, Hallucination Mitigation, and Advanced Prompting Strategies

Python Programming Learning Circle

Jun 8, 2022 · Artificial Intelligence

Leveraging PaddleNLP UIE for Zero‑Shot Logistic Parcel Information Extraction

This article explains how PaddleNLP's Universal Information Extraction (UIE) model can dramatically reduce labeling effort and improve accuracy for logistics parcel data extraction, showcasing a five‑sample experiment that boosts F1 by 18 points to 93% and providing a zero‑shot Python example.

Information ExtractionNLPPaddleNLP

0 likes · 5 min read

Leveraging PaddleNLP UIE for Zero‑Shot Logistic Parcel Information Extraction

DaTaobao Tech

May 24, 2022 · Artificial Intelligence

GEN-VLKT: Simplify Association and Enhance Interaction Understanding for HOI Detection

GEN‑VLKT introduces a Guided‑Embedding Network with position‑ and instance‑guided embeddings to remove costly post‑processing and leverages CLIP‑based visual‑linguistic knowledge transfer for interaction understanding, achieving state‑of‑the‑art HOI detection performance and zero‑shot capability, now deployed in Alibaba’s Taobao services.

ClipComputer VisionHOI detection

0 likes · 7 min read

GEN-VLKT: Simplify Association and Enhance Interaction Understanding for HOI Detection

DataFunTalk

Jan 16, 2022 · Artificial Intelligence

DeltaLM: A Multilingual Pretrained Encoder‑Decoder Model for Neural Machine Translation and Zero‑Shot Transfer

DeltaLM is a new multilingual pretrained encoder‑decoder model that leverages a pretrained encoder and a novel decoder to improve multilingual neural machine translation, offering efficient training, strong cross‑language transfer, zero‑shot translation, and superior performance on various translation and summarization tasks.

DeltaLMNMTZero-shot

0 likes · 13 min read

DeltaLM: A Multilingual Pretrained Encoder‑Decoder Model for Neural Machine Translation and Zero‑Shot Transfer

DataFunSummit

Jan 13, 2022 · Artificial Intelligence

DeltaLM: A Multilingual Pretrained Encoder‑Decoder Model for Neural Machine Translation

DeltaLM is a multilingual pretrained encoder‑decoder model that leverages cross‑lingual transfer from a pretrained encoder and novel decoder architecture, employs span‑corruption and translation‑pair pretraining tasks, and uses a two‑stage fine‑tuning strategy to achieve strong zero‑shot and supervised translation performance across over 100 languages.

DeltaLMZero-shotcross-lingual transfer

0 likes · 12 min read

DeltaLM: A Multilingual Pretrained Encoder‑Decoder Model for Neural Machine Translation

DataFunTalk

Apr 7, 2021 · Artificial Intelligence

Alibaba's Advances in Multilingual Neural Machine Translation: Research and Practice

This article presents Alibaba's comprehensive research on multilingual neural machine translation, covering motivations, model architectures, intermediate language modules, data‑augmentation strategies such as repair translation, integration of pre‑trained models with adapters, and engineering optimizations that enable a production‑ready system supporting over 200 languages.

AlibabaPretrainingZero-shot

0 likes · 21 min read

Alibaba's Advances in Multilingual Neural Machine Translation: Research and Practice