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Latest from Xiaohongshu Tech REDtech

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Xiaohongshu Tech REDtech

Sep 23, 2024 · Artificial Intelligence

AlignRec: A Joint Training Framework for Aligning Multimodal Representations with Personalized Recommendation

AlignRec is a joint‑training framework that synchronizes multimodal encoders with personalized recommendation models through a staged alignment strategy and three specialized loss functions, preserving both content and ID signals, and achieving state‑of‑the‑art performance on multiple datasets while releasing superior Amazon multimodal features.

AIevaluation metricsjoint training

0 likes · 11 min read

AlignRec: A Joint Training Framework for Aligning Multimodal Representations with Personalized Recommendation

Xiaohongshu Tech REDtech

Sep 19, 2024 · Artificial Intelligence

Target-Driven Distillation (TDD): A Multi‑Goal Distillation Method for Accelerating Diffusion Models

Target‑Driven Distillation (TDD) is a multi‑goal distillation method that flexibly selects short‑range target steps and decouples guidance during training, enabling 4‑to‑8‑step diffusion generation that preserves high‑resolution detail, works with LoRA, ControlNet, InstantID, and outperforms existing consistency distillation techniques in speed and quality.

AI accelerationdiffusion modelsdistillation

0 likes · 9 min read

Target-Driven Distillation (TDD): A Multi‑Goal Distillation Method for Accelerating Diffusion Models

Xiaohongshu Tech REDtech

Sep 9, 2024 · Cloud Native

Applying eBPF for Cloud‑Native Observability and Continuous Profiling

By deploying eBPF agents as DaemonSets that hook kernel network and performance events, the Xiaohongshu observability team extended cloud‑native monitoring from the application to the kernel, delivering real‑time traffic analysis and low‑overhead continuous profiling for C++ services, aggregating data into centralized collectors for dashboards, flame‑graphs, and rapid root‑cause diagnosis.

KubernetesObservabilityProfiling

0 likes · 37 min read

Applying eBPF for Cloud‑Native Observability and Continuous Profiling

Xiaohongshu Tech REDtech

Sep 2, 2024 · Artificial Intelligence

How AIGC Transforms Advertising Material Creation on Xiaohongshu

This article analyzes how large‑model AIGC reshapes the production, evaluation, and deployment of advertising creatives on Xiaohongshu, detailing the business motivations, technical pipeline, controllable generation, reward‑model filtering, and experimental results that balance commercial efficiency with community tone.

AIGCAdvertisingLarge Language Model

0 likes · 14 min read

How AIGC Transforms Advertising Material Creation on Xiaohongshu

Xiaohongshu Tech REDtech

Aug 23, 2024 · Artificial Intelligence

Xiaohongshu REDtech Live: Presentation of Recent Top‑Conference Papers (Recruitment Session)

On August 24, 2024, Xiaohongshu’s technical team will livestream a four‑hour REDtech session across WeChat Channels, its recruitment account, and Bilibili, showcasing recent top‑conference papers—from ACL and CVPR to ICLR and AAAI—covering innovations such as KV‑cache compression, zero‑shot image generation, early‑stopping self‑consistency, negative‑sample‑aware distillation, and real‑time nearest‑neighbor search, while allowing live interaction and offering surprise merchandise.

AIConference PapersMachine Learning

0 likes · 18 min read

Xiaohongshu REDtech Live: Presentation of Recent Top‑Conference Papers (Recruitment Session)

Xiaohongshu Tech REDtech

Aug 1, 2024 · Artificial Intelligence

Xiaohongshu Search Advertising Recall: Practices, Metrics, and Large‑Model Integration

Xiaohongshu’s search advertising recall system evolves from keyword bidding to BERT‑based vector retrieval and LLM‑enhanced query rewriting, using dual semantic and efficiency models, water‑level metrics, and GPU‑accelerated engineering to achieve 80 % click coverage, 60 % conversion coverage and a 5 % CPM lift.

Artificial Intelligenceefficiency optimizationlarge language models

0 likes · 33 min read

Xiaohongshu Search Advertising Recall: Practices, Metrics, and Large‑Model Integration

Xiaohongshu Tech REDtech

Jul 29, 2024 · Artificial Intelligence

Scaling Laws for Dense Retrieval: Empirical Study of Model Size, Training Data, and Annotation Quality

The award‑winning study shows that dense retrieval performance follows precise power‑law scaling with model size, training data quantity, and annotation quality, introduces contrast entropy for evaluation, validates joint scaling formulas on MS MARCO and T2Ranking, and uses cost models to guide budget‑optimal resource allocation.

Model Sizeannotation qualitycontrast entropy

0 likes · 13 min read

Scaling Laws for Dense Retrieval: Empirical Study of Model Size, Training Data, and Annotation Quality

Xiaohongshu Tech REDtech

Jun 24, 2024 · Databases

Distributed Parallel Multi‑Hop Query Optimization in REDgraph Graph Database

To meet Xiaohongshu’s strict P99 latency targets for multi‑hop graph queries, the REDgraph team built a distributed parallel execution framework that eliminates global barriers, pushes operators to storage nodes, uses routing operators and a NeighborCache, cutting three‑hop query latency by over 50 % and enabling production deployment.

Graph DatabaseREDgraphdistributed parallel

0 likes · 29 min read

Distributed Parallel Multi‑Hop Query Optimization in REDgraph Graph Database

Xiaohongshu Tech REDtech

Jun 20, 2024 · Artificial Intelligence

Xiaohongshu 2024 Large Model Frontier Paper Sharing Live Event

On June 27, 2024, Xiaohongshu’s technical team will livestream a two‑hour session across WeChat Channels, Bilibili, Douyin and Xiaohongshu, showcasing six top‑conference papers on large‑model advances—including early‑stopping and fine‑grained self‑consistency, novel evaluation methods, negative‑sample‑assisted distillation, and LLM‑based note recommendation—followed by a Q&A and recruitment briefing.

AI researchKnowledge DistillationRecommendation Systems

0 likes · 12 min read

Xiaohongshu 2024 Large Model Frontier Paper Sharing Live Event

Xiaohongshu Tech REDtech

Jun 17, 2024 · Artificial Intelligence

Xiaohongshu Audio-Video Architecture Team Wins Top Awards in CVPR NTIRE 2024 Challenges

Xiaohongshu’s audio‑video architecture team secured second place in the RAIM challenge and first in the S‑UGC VQA challenge at CVPR NTIRE 2024 by improving generative image restoration with SUPIR, DeSRA and a Fusion model, and enhancing video quality assessment using LIQE, Q‑Align and FAST‑VQA, then deploying these methods for live‑stream denoising, intelligent transcoding and cloud‑based super‑resolution, achieving high PLCC/SROCC scores and up to 33 % bandwidth savings.

AICVPR NTIRE 2024Denoising

0 likes · 25 min read

Xiaohongshu Audio-Video Architecture Team Wins Top Awards in CVPR NTIRE 2024 Challenges