Reward Modeling

JD Retail Technology

May 7, 2025 · Artificial Intelligence

Solving Technical Challenges with Large AI Models at JD Retail: Reward Modeling, Query Expansion, and Model Pruning

JD Retail’s engineering team tackles hard AI problems by replacing a monolithic reward model with specialized small models for ad‑image generation, deploying an LLM‑driven query‑expansion pipeline that lifts conversion rates, and pruning text‑to‑image transformers using FFT and RDP to boost throughput 40% without loss, while building comprehensive evaluation tools and a semantic smart‑assistant.

AILarge ModelsReward Modeling

0 likes · 14 min read

Solving Technical Challenges with Large AI Models at JD Retail: Reward Modeling, Query Expansion, and Model Pruning

Architect

Feb 25, 2025 · Artificial Intelligence

DeepSeek R1: Multi‑Stage Reinforcement Learning, Reward Modeling, and Distillation for a High‑Performance LLM

DeepSeek R1 builds on the DeepSeek V3 base model using a multi‑stage reinforcement learning pipeline—including GRPO optimization, rule‑based reward modeling, supervised fine‑tuning, language‑consistency rewards, rejection sampling, and distillation—to produce a high‑performing, aligned LLM capable of accurate reasoning.

DeepSeekLLM TrainingModel Distillation

0 likes · 24 min read

DeepSeek R1: Multi‑Stage Reinforcement Learning, Reward Modeling, and Distillation for a High‑Performance LLM