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Wu Shixiong's Large Model Academy
Wu Shixiong's Large Model Academy
Apr 20, 2026 · Artificial Intelligence

How to Build Multi‑Step Reasoning Training Data for Deep Research Agents

Standard QA datasets fall short for deep research tasks because they lack the multi‑step, dynamic reasoning required; this article explains why, outlines four data‑construction techniques—SailorFog‑QA, WebFrontier, WebShaper, E2HQA—details trajectory sampling, filtering, scale considerations, and interview‑ready explanations.

AI AgentsLLM trainingMulti-step Reasoning
0 likes · 16 min read
How to Build Multi‑Step Reasoning Training Data for Deep Research Agents
DataFunSummit
DataFunSummit
Sep 18, 2025 · Artificial Intelligence

Boosting LLM Function Call: Data, Training, and Agent Optimization Strategies

This presentation by Yao Yitong of China Telecom AI Research Institute explains why Function Call is essential for LLM deployment, outlines data‑centric and training‑centric optimization methods, discusses common pitfalls and reward‑function design for reinforcement learning, and showcases practical Agent application patterns for real‑world tasks.

AgentLLMTraining Optimization
0 likes · 36 min read
Boosting LLM Function Call: Data, Training, and Agent Optimization Strategies
Dada Group Technology
Dada Group Technology
Sep 5, 2022 · Operations

Design and Implementation of JD.com Data Construction Platform for Testing Efficiency

This article describes the motivation, design, architecture, key features, and outcomes of JD.com's data construction platform, which automates test data creation using a Springboot‑Mybatis‑Vue stack, significantly reducing manual effort and improving testing efficiency across multiple business lines.

OperationsTesting Automationdata construction
0 likes · 9 min read
Design and Implementation of JD.com Data Construction Platform for Testing Efficiency
转转QA
转转QA
Aug 12, 2022 · Backend Development

Improving Test Efficiency through Data Construction: Practices and Insights

This article explains how systematic data construction, using a low‑code front‑end and Java back‑end platform, streamlines complex test scenarios, reduces manual effort, and enhances both testing efficiency and code quality across multiple business systems.

Backend DevelopmentJavaQA
0 likes · 9 min read
Improving Test Efficiency through Data Construction: Practices and Insights
转转QA
转转QA
Aug 27, 2021 · Game Development

Improving Game Business Data Construction to Reduce Cost and Increase Efficiency

This article describes the challenges of custom‑heavy game business workflows and manual data‑construction testing, then presents an initial and a refined solution that automates data generation across multiple game titles, reduces coupling, and improves efficiency and cost for backend operations.

Backend automationCost reductionGame Development
0 likes · 5 min read
Improving Game Business Data Construction to Reduce Cost and Increase Efficiency
转转QA
转转QA
May 13, 2020 · Operations

QA Transformation: Applying HTTP DIFF and Visual UI Automation to Operational and Order‑Related Requirements

This article describes how the QA team at ZuanZuan YouPin shifted from traditional functional testing to an assisted model by introducing HTTP DIFF for short‑flow operational features and visual UI automation for dynamic pages, as well as data‑construction and online order inspection techniques for complex order‑related scenarios.

HTTP DIFFOperationsQA
0 likes · 7 min read
QA Transformation: Applying HTTP DIFF and Visual UI Automation to Operational and Order‑Related Requirements
Efficient Ops
Efficient Ops
Jan 30, 2018 · Operations

Scaling Event Operations for Ten‑Million Online Securities Users

This article details how Ping An Securities built a technology‑first event‑handling team, created new reporting channels, developed a data‑construction platform, and implemented proactive monitoring to efficiently support over ten million internet securities users.

ITSMService Centerdata construction
0 likes · 21 min read
Scaling Event Operations for Ten‑Million Online Securities Users
转转QA
转转QA
Oct 22, 2017 · Backend Development

Evolution and Architecture of a Transaction Service Testing Framework

This article details the evolution of a transaction‑related testing framework, describing its background, objectives, development stages—including all‑in‑one code, method extraction, project separation, data construction, checklist and performance testing—and outlines various test case categories and the lightweight release workflow.

AutomationBackendchecklist
0 likes · 11 min read
Evolution and Architecture of a Transaction Service Testing Framework