Tagged articles

Semantic ID

13 articles · Page 1 of 1

Oct 2, 2026 · Artificial Intelligence

Xiaohongshu's GR-Inference: Custom Engine for 3.6x Faster Generative Retrieval

Xiaohongshu built a custom inference engine GR-Inference for generative search retrieval, addressing unique load characteristics — long context, short decode, large dynamic beam, and constrained generation — that break general frameworks, achieving 1.5–3.6x throughput over SGLang and improving recall and click-through rates.

GR-InferenceLLM servingSGLang

0 likes · 7 min read

Xiaohongshu's GR-Inference: Custom Engine for 3.6x Faster Generative Retrieval

Alibaba International Intelligent Technology

Sep 3, 2026 · Artificial Intelligence

Masked Diffusion Challenges Left-to-Right Decoding in Generative Recommendation (Recsys'26)

This paper introduces MDGR, a masked diffusion framework for generative recommendation that replaces autoregressive left-to-right decoding with a parallel mask-denoising process, achieving up to 6.56% relative improvement offline and significant online gains in Alibaba's advertising platform.

AlibabaMasked DiffusionOnline A/B Testing

0 likes · 17 min read

Masked Diffusion Challenges Left-to-Right Decoding in Generative Recommendation (Recsys'26)

JD Retail Technology

May 25, 2026 · Artificial Intelligence

How Adaptive Semantic IDs Enable Precise and Generalizable Generative Retrieval

The article introduces the SA²CRQ framework, which adaptively allocates semantic ID length and transfers residual knowledge to resolve head‑item ID collisions and tail‑item generalization gaps in large‑scale e‑commerce generative retrieval, achieving stable gains on both industrial and public datasets.

Adaptive QuantizationLong-tail DistributionResidual Knowledge Transfer

0 likes · 19 min read

How Adaptive Semantic IDs Enable Precise and Generalizable Generative Retrieval

Ximalaya Technology Team

Feb 11, 2026 · Artificial Intelligence

How Ximalaya Used Generative AI to Revolutionize Audio Recommendations

This article details Ximalaya's journey from traditional multi‑stage recommendation pipelines to generative AI‑driven models, covering business challenges, architectural and model differences, phased deployments, knowledge distillation, semantic ID encoding, decoder‑only strategies, extensive offline and online evaluations, and future research directions.

Encoder-DecoderSemantic IDaudio recommendation

0 likes · 24 min read

How Ximalaya Used Generative AI to Revolutionize Audio Recommendations

Alibaba International Intelligent Technology

Nov 21, 2025 · Artificial Intelligence

MMQ Advances Multimodal Fusion and Aligns Behavior for Large-Scale Recommendation Models

The paper introduces MMQ, a multimodal mixture‑of‑quantization semantic‑ID framework that compresses item multimodal features via shared‑specific expert networks and behavior‑aware fine‑tuning, achieving lower reconstruction loss, superior recall and ranking performance, and online gains of +1.29% REV, +4.33% CVR, +2.61% GMV, and +1.18% ROI.

MMQSemantic IDbehavior-aware fine-tuning

0 likes · 14 min read

MMQ Advances Multimodal Fusion and Aligns Behavior for Large-Scale Recommendation Models

Amap Tech

Oct 27, 2025 · Artificial Intelligence

Turning Maps into a Living Map: Amap’s G-Where Generative AI Recommendation

Amap upgrades its homepage recommendation by integrating large‑model capabilities—G‑Where, G‑Action, and G‑Plan—through semantic ID generation, item tokenization, and multi‑stage LLM training, achieving significant offline and online performance gains while illustrating a scalable generative recommendation framework.

AIMap ServicesSemantic ID

0 likes · 21 min read

Turning Maps into a Living Map: Amap’s G-Where Generative AI Recommendation

JD Tech

Dec 14, 2024 · Artificial Intelligence

Generative Retrieval for E‑commerce Search: Lexical and Semantic ID Approaches

This article presents a comprehensive study of generative retrieval for large‑scale e‑commerce search, comparing lexical‑based and Semantic‑ID‑based methods, introducing a Query‑to‑MultiSpan framework, analyzing the sand‑glass distribution problem in residual quantization, and proposing heuristic and adaptive solutions to improve recall and efficiency.

AISemantic IDe-commerce search

0 likes · 20 min read

Generative Retrieval for E‑commerce Search: Lexical and Semantic ID Approaches

JD Retail Technology

Dec 9, 2024 · Artificial Intelligence

Generative Retrieval for E‑commerce Search: Lexical‑Based and Semantic‑ID Approaches

This article presents a comprehensive study of generative retrieval in large‑scale e‑commerce search, detailing lexical‑based and SemanticID‑based methods, their challenges such as long‑tail distribution and token length, experimental evaluations, the discovered "sandglass" effect, and proposed solutions to improve recall and efficiency.

AISemantic IDe-commerce search

0 likes · 20 min read

Generative Retrieval for E‑commerce Search: Lexical‑Based and Semantic‑ID Approaches

DataFunSummit

Nov 28, 2024 · Artificial Intelligence

Generative Retrieval for E‑commerce Search: Lexical and SemanticID Approaches

This article presents a comprehensive study of generative retrieval for large‑scale e‑commerce search, detailing background challenges, the advantages of generative methods, two concrete strategies—Lexical‑based and SemanticID‑based—along with task redesign, preference optimization, constrained beam search, extensive experiments, and future research directions.

Semantic IDe-commerce searchgenerative retrieval

0 likes · 21 min read

JD Tech

Jul 5, 2024 · Artificial Intelligence

Generative Recommendation Systems for JD Alliance Advertising: Architecture, Implementation, and Experimental Evaluation

This article surveys how large language models reshape recommendation systems, presents a generative RS framework tailored for JD Alliance advertising, details material representation, model input, training and inference pipelines, and reports extensive offline and online experiments demonstrating its effectiveness on sparse user data.

LLMSemantic IDe-commerce advertising

0 likes · 27 min read

Generative Recommendation Systems for JD Alliance Advertising: Architecture, Implementation, and Experimental Evaluation

JD Retail Technology

Jul 1, 2024 · Artificial Intelligence

Generative Recommendation Systems for JD Alliance Advertising: Design, Implementation, and Evaluation

This article surveys how large language models reshape recommendation systems, details a generative recommender framework for JD Alliance ads—including item representation, model input, training, and inference—presents extensive offline and online experiments, and discusses future optimization directions.

JD AllianceLLMOffline Evaluation

0 likes · 25 min read

Generative Recommendation Systems for JD Alliance Advertising: Design, Implementation, and Evaluation

JD Cloud Developers

Jun 13, 2024 · Artificial Intelligence

How LLMs Are Redefining Recommender Systems for JD Union Ads

This article surveys the impact of large language models on recommendation systems, outlines generative recommender architectures, discusses challenges of JD Union advertising, presents a semantic‑ID based solution with training and inference details, and reports offline and online experimental results.

AILLMSemantic ID

0 likes · 22 min read

How LLMs Are Redefining Recommender Systems for JD Union Ads

JD Tech Talk

Jun 13, 2024 · Artificial Intelligence

Generative Recommender Systems for JD Affiliate Advertising: Architecture, Methods, and Experimental Evaluation

This article surveys how large language models can reshape recommendation systems, describes the four-stage generative pipeline, details item representation techniques such as semantic IDs, presents a JD affiliate advertising use case with offline and online experiments, and outlines future optimization directions.

LLMOffline EvaluationSemantic ID

0 likes · 25 min read

Generative Recommender Systems for JD Affiliate Advertising: Architecture, Methods, and Experimental Evaluation