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Kuaishou Tech
Kuaishou Tech
Nov 14, 2025 · Artificial Intelligence

How GRPO‑Guard Stops Over‑Optimization in Flow‑Based Visual Generators

This article explains the over‑optimization problem in GRPO‑based flow models, analyzes why importance‑ratio clipping fails, and introduces GRPO‑Guard with RatioNorm and cross‑step gradient balancing, showing through extensive experiments that it stabilizes training and improves image quality across multiple diffusion backbones and tasks.

GRPO-Guardflow matchinggenerative AI
0 likes · 9 min read
How GRPO‑Guard Stops Over‑Optimization in Flow‑Based Visual Generators
Kuaishou Tech
Kuaishou Tech
Nov 13, 2025 · Artificial Intelligence

Unlocking Unusual Concept Combinations in Generative AI with IMBA Loss

The paper identifies imbalanced concept distributions as the main obstacle to arbitrary concept‑combination in text‑to‑image/video generation, proposes the token‑level IMBA Distance and a lightweight IMBA Loss that adaptively re‑weights training tokens, and demonstrates through extensive experiments and a new Inert‑CompBench benchmark that this loss dramatically improves compositional ability without extra data.

IMBA Lossbenchmarkconcept combination
0 likes · 9 min read
Unlocking Unusual Concept Combinations in Generative AI with IMBA Loss
Kuaishou Tech
Kuaishou Tech
Nov 12, 2025 · Artificial Intelligence

How KaiFG Lets Python Feature Engineering Run at C++ Speed

KaiFG, Kuaishou's self‑built AI Feature Generator, unifies fragmented feature extraction frameworks, replaces slow C++ compilation cycles with Python‑level development, and achieves near‑C++ performance through Codon‑based compilation, reference‑counted memory management, and aggressive LLVM optimizations, dramatically shortening iteration time.

AI infrastructureHigh Performance Computingfeature engineering
0 likes · 14 min read
How KaiFG Lets Python Feature Engineering Run at C++ Speed
Kuaishou Tech
Kuaishou Tech
Nov 5, 2025 · Artificial Intelligence

How HiPO Gives LLMs a Smart Thinking Switch to Cut Costs and Boost Accuracy

This article explains the overthinking problem of large language models, introduces the HiPO framework with hybrid data cold‑start and reinforcement‑learning reward mechanisms that let models decide when to think deeply or answer directly, and shows experimental results demonstrating significant efficiency gains and accuracy improvements across multiple benchmarks.

EfficiencyHybrid Policy OptimizationLLM
0 likes · 13 min read
How HiPO Gives LLMs a Smart Thinking Switch to Cut Costs and Boost Accuracy
Kuaishou Tech
Kuaishou Tech
Oct 30, 2025 · Artificial Intelligence

How EMER Revolutionizes Short‑Video Ranking with End‑to‑End Multi‑Objective Learning

This article details the EMER framework—a Transformer‑based, end‑to‑end multi‑objective ranking system that replaces handcrafted formulas with a learnable AI model, introduces relative‑satisfaction signals and dynamic loss weighting, and demonstrates significant offline and online performance gains in Kuaishou's short‑video recommendation pipeline.

AIRecommendation Systemsmulti-objective learning
0 likes · 16 min read
How EMER Revolutionizes Short‑Video Ranking with End‑to‑End Multi‑Objective Learning
Kuaishou Tech
Kuaishou Tech
Oct 11, 2025 · Artificial Intelligence

How KAT-Dev-72B-Exp Sets a New Record in Large‑Scale RL for Code Generation

The KAT‑Dev‑72B‑Exp model, an experimental reinforcement‑learning version of KAT‑Coder, achieves a 74.6% performance boost on the SWE‑Bench Verified benchmark, introduces Trie Packing and entropy‑aware advantage scaling, and showcases a decoupled training architecture that dramatically speeds up large‑scale agentic RL training.

AIagentic trainingcode generation
0 likes · 9 min read
How KAT-Dev-72B-Exp Sets a New Record in Large‑Scale RL for Code Generation
Kuaishou Tech
Kuaishou Tech
Sep 23, 2025 · Artificial Intelligence

How Generative Reinforcement Learning is Revolutionizing Real-Time Bidding

This article explains the core challenges of real‑time bidding, traces the evolution from PID to MPC to reinforcement learning, and details how generative reinforcement‑learning techniques such as GAVE and CBD combine diffusion models, value‑guided exploration, and score‑based return‑to‑go to dramatically improve ad‑bid efficiency and revenue.

CBDGAVEadvertising algorithms
0 likes · 15 min read
How Generative Reinforcement Learning is Revolutionizing Real-Time Bidding
Kuaishou Tech
Kuaishou Tech
Sep 17, 2025 · Artificial Intelligence

How MIDAS Achieves Real‑Time Multimodal Digital‑Human Video Generation

The MIDAS framework introduced by the Kling Team combines autoregressive video generation with a lightweight diffusion denoising head to deliver real‑time, high‑quality digital‑human synthesis under multimodal control, achieving sub‑500 ms latency, 64× compression, and robust performance across multilingual dialogue, singing, and interactive world modeling tasks.

AIReal-time Videoautoregressive
0 likes · 6 min read
How MIDAS Achieves Real‑Time Multimodal Digital‑Human Video Generation
Kuaishou Tech
Kuaishou Tech
Sep 16, 2025 · Artificial Intelligence

How Kling-Avatar Generates Long, Emotionally Rich Digital Human Videos with Multimodal LLMs

Kuaishou's Kling-Avatar leverages a multimodal large‑language‑model‑driven two‑stage generation framework to produce minute‑long digital‑human videos that synchronize lip movements, facial expressions, and body gestures with audio, achieving high visual quality, identity consistency, and controllable storytelling across diverse scenarios.

AI AvatarVideo Generationdigital human
0 likes · 9 min read
How Kling-Avatar Generates Long, Emotionally Rich Digital Human Videos with Multimodal LLMs