Chain-of-Thought

Code Mala Tang

Jun 5, 2025 · Artificial Intelligence

Mastering LLM Prompts: Proven Techniques to Get Precise Answers

By rethinking how we interact with large language models—using role‑play, task decomposition, chain‑of‑thought, ReAct, and other advanced prompting strategies—readers can transform generic ChatGPT answers into precise, context‑aware responses, leveraging pattern recognition and context windows for superior AI assistance.

AI reasoningChain-of-ThoughtLLM techniques

0 likes · 21 min read

Mastering LLM Prompts: Proven Techniques to Get Precise Answers

Efficient Ops

May 29, 2025 · Artificial Intelligence

DeepSeek R1 0528 Update: New Features, Performance Gains Over OpenAI o3

DeepSeek quietly launched the R1 0528 model, which early testers report matches OpenAI’s o3 in benchmarks and style, while adding deeper chain‑of‑thought reasoning, better writing output, and extended thinking windows, and the announcement is followed by a promotion for the GOPS Global Ops Conference.

AI performanceChain-of-ThoughtDeepSeek

0 likes · 3 min read

DeepSeek R1 0528 Update: New Features, Performance Gains Over OpenAI o3

Alimama Tech

Apr 23, 2025 · Artificial Intelligence

Explainable LLM-driven Multi-dimensional Distillation for E-Commerce Relevance Learning

The paper introduces an explainable LLM framework (ELLM‑rele) that uses chain‑of‑thought reasoning and a multi‑dimensional knowledge distillation pipeline to compress large‑model relevance judgments into lightweight student models, achieving superior offline relevance scores and online click‑through and conversion improvements in Taobao’s search advertising.

Chain-of-ThoughtLLMe-commerce

0 likes · 17 min read

Explainable LLM-driven Multi-dimensional Distillation for E-Commerce Relevance Learning

Amap Tech

Apr 21, 2025 · Artificial Intelligence

Lenna: Language‑Enhanced Reasoning Detection Assistant and a Chain‑of‑Thought Image Editing Framework Using Multimodal Large Language Models

At ICASSP 2025, Gaode’s two accepted papers present Lenna, a language‑enhanced reasoning detection assistant that adds a DET token to multimodal LLMs and achieves state‑of‑the‑art accuracy on RefCOCO benchmarks, and a chain‑of‑thought image‑editing framework that converts complex prompts into segmented masks and repair prompts for diffusion‑based inpainting, surpassing existing methods.

AIChain-of-ThoughtComputer Vision

0 likes · 10 min read

Lenna: Language‑Enhanced Reasoning Detection Assistant and a Chain‑of‑Thought Image Editing Framework Using Multimodal Large Language Models

Cognitive Technology Team

Apr 4, 2025 · Artificial Intelligence

Reasoning Models Do Not Always Reveal Their Thoughts: Evaluating Chain‑of‑Thought Fidelity

The article examines how modern reasoning models like Claude 3.7 Sonnet display chain‑of‑thought explanations, but often hide or distort their true reasoning, presenting challenges for AI safety and alignment, and evaluates methods to test and improve fidelity.

AI alignmentAI safetyChain-of-Thought

0 likes · 13 min read

Reasoning Models Do Not Always Reveal Their Thoughts: Evaluating Chain‑of‑Thought Fidelity

DataFunTalk

Mar 24, 2025 · Artificial Intelligence

DeepSeek R1: Open‑Source Reasoning Model and Multi‑Stage Training Insights

The interview explores DeepSeek R1's open‑source weights, its multi‑stage training pipeline—including pre‑training, supervised fine‑tuning, and RLHF—alongside innovations such as self‑consistency, chain‑of‑thought prompting, distillation, MoE architectures, and cost considerations, highlighting its impact on the future of large language models.

AI trainingChain-of-ThoughtDeepSeek

0 likes · 20 min read

DeepSeek R1: Open‑Source Reasoning Model and Multi‑Stage Training Insights

Selected Java Interview Questions

Mar 15, 2025 · Artificial Intelligence

DeepSeek4j 1.4: Java Spring Boot Integration for DeepSeek with Full Chain‑of‑Thought and Streaming Support

DeepSeek4j 1.4 introduces a Java‑centric, Spring Boot‑compatible framework that fully preserves DeepSeek's chain‑of‑thought capabilities, adds reactive streaming, and provides simple one‑line API integration, addressing previous limitations in mainstream frameworks and offering ready‑to‑use configuration and code examples.

AI integrationChain-of-ThoughtDeepSeek

0 likes · 5 min read

DeepSeek4j 1.4: Java Spring Boot Integration for DeepSeek with Full Chain‑of‑Thought and Streaming Support

Java Architect Essentials

Mar 7, 2025 · Artificial Intelligence

Introducing DeepSeek4j 1.4: A Java Spring Boot Integration for DeepSeek AI with Chain‑of‑Thought and Streaming Support

The article introduces DeepSeek4j 1.4, a Java Spring Boot library that overcomes existing framework limitations by preserving DeepSeek's chain‑of‑thought capabilities, adding full reactive streaming, and providing a simple one‑line API along with quick‑start instructions and code examples.

AI integrationChain-of-ThoughtDeepSeek

0 likes · 5 min read

Introducing DeepSeek4j 1.4: A Java Spring Boot Integration for DeepSeek AI with Chain‑of‑Thought and Streaming Support

Code Mala Tang

Feb 27, 2025 · Artificial Intelligence

Do New AI Reasoning Models Really Think? Unpacking the Debate

The article examines whether the latest AI models that claim to perform true reasoning—by breaking problems into steps and using chain‑of‑thought—actually reason like humans, presenting skeptical and supportive expert viewpoints, and offering practical guidance on how to use such models responsibly.

AI reasoningAI safetyChain-of-Thought

0 likes · 14 min read

Do New AI Reasoning Models Really Think? Unpacking the Debate

Top Architect

Feb 21, 2025 · Artificial Intelligence

DeepSeek4j 1.4: Java Integration Framework for DeepSeek with Full Chain‑of‑Thought and Streaming Support

The article introduces DeepSeek4j 1.4, a Java‑based framework that overcomes Spring AI’s limitations by fully preserving DeepSeek’s chain‑of‑thought and billing features, adding reactive streaming, providing Spring Boot starter integration, and offering quick‑start code samples and configuration guidance.

AIChain-of-ThoughtDeepSeek

0 likes · 8 min read

DeepSeek4j 1.4: Java Integration Framework for DeepSeek with Full Chain‑of‑Thought and Streaming Support

Tencent Technical Engineering

Feb 17, 2025 · Artificial Intelligence

Prompt Engineering: Definitions, Frameworks, Principles, and Advanced Techniques

The guide defines prompts as structured queries that unlock large‑language‑model abilities, outlines five core frameworks (RTF, Chain‑of‑Thought, RISEN, RODES, Density‑Chain), presents two key principles—clear, delimited instructions and explicit reasoning steps—to reduce hallucinations, and surveys advanced techniques such as zero‑shot, few‑shot, RAG, Tree‑of‑Thought and automatic prompt engineering.

AIChain-of-ThoughtFew-Shot Prompting

0 likes · 29 min read

Prompt Engineering: Definitions, Frameworks, Principles, and Advanced Techniques

DevOps

Feb 7, 2025 · Artificial Intelligence

OpenAI Releases o3-mini Chain‑of‑Thought: First Tests, Community Reactions, and Critical Analysis

OpenAI has publicly disclosed the chain‑of‑thought reasoning of its o3‑mini model, prompting a wave of community experiments, critiques about authenticity, and discussions on the model’s limitations, prompting insights into AI interpretability and the trade‑offs of revealing internal reasoning.

Artificial IntelligenceChain-of-ThoughtO3-mini

0 likes · 6 min read

OpenAI Releases o3-mini Chain‑of‑Thought: First Tests, Community Reactions, and Critical Analysis

Java Architecture Diary

Feb 5, 2025 · Artificial Intelligence

Unlocking DeepSeek R1’s Chain‑of‑Thought: A Spring WebFlux Integration Guide

This article examines why mainstream AI frameworks like Spring AI and LangChain4j cannot fully support DeepSeek’s R1 model, explains its unique chain‑of‑thought response format and parameter constraints, and provides a complete Spring WebFlux‑based solution—including API calls, streaming handling, and response parsing—to preserve reasoning content.

AI integrationChain-of-ThoughtDeepSeek

0 likes · 8 min read

Unlocking DeepSeek R1’s Chain‑of‑Thought: A Spring WebFlux Integration Guide

DaTaobao Tech

Jan 24, 2025 · Artificial Intelligence

MktAI Assistant: AI‑Driven Marketing Data Query and Insight Platform

The MktAI Assistant combines LLM‑powered memory, skill planning, and tool‑calling with real‑time API data to replace slow, manual SQL dashboards, delivering sub‑minute, fresh, explainable marketing queries and attribution insights that boost decision speed, accuracy, and collaboration between data scientists and business users.

AI AgentChain-of-ThoughtFunction Calling

0 likes · 16 min read

MktAI Assistant: AI‑Driven Marketing Data Query and Insight Platform

DaTaobao Tech

Dec 9, 2024 · Artificial Intelligence

Analyzing LLM Failure Cases: Tokenization, Next‑Token Prediction, and Chain‑of‑Thought Prompting

The article explains how tokenization mismatches and biased next‑token prediction cause LLMs to miscount letters in “Strawberry” and incorrectly compare 9.9 versus 9.11, and shows that step‑by‑step Chain‑of‑Thought prompting with reason‑first output dramatically improves accuracy.

AIChain-of-ThoughtLLM

0 likes · 13 min read

Analyzing LLM Failure Cases: Tokenization, Next‑Token Prediction, and Chain‑of‑Thought Prompting

JD Tech

Nov 12, 2024 · Artificial Intelligence

Prompt Engineering: Concepts, Evolution, Techniques, and JD Logistics Application

This article explains what Prompt Engineering is, traces its development from early NLP commands to modern adaptive and multimodal prompting techniques, describes various prompting strategies such as Zero‑shot, Few‑shot, Chain‑of‑Thought, Auto‑CoT, and showcases a JD Logistics case study using these methods to classify product types with code examples.

AI Prompt DesignChain-of-ThoughtZero-shot

0 likes · 27 min read

Prompt Engineering: Concepts, Evolution, Techniques, and JD Logistics Application

JD Tech Talk

Nov 11, 2024 · Artificial Intelligence

Prompt Engineering: Concepts, Evolution, Techniques, and a Logistics Application Case

This article explains what Prompt Engineering is, traces its development from early command‑based interactions to modern adaptive and multimodal prompting, details various prompting techniques such as zero‑shot, few‑shot, Chain‑of‑Thought, hallucination‑reduction methods, and demonstrates their practical use in a JD Logistics SKU piece‑type classification case with code examples.

AI promptingChain-of-ThoughtLLM applications

0 likes · 26 min read

Prompt Engineering: Concepts, Evolution, Techniques, and a Logistics Application Case

DaTaobao Tech

Oct 30, 2024 · Artificial Intelligence

Understanding OpenAI o1: Chain‑of‑Thought, Scaling Laws, and Training Strategies

The article explains how OpenAI’s o1 model leverages chain‑of‑thought prompting, dual‑system cognitive theory, and new scaling laws—pre‑training on code/math and post‑training reinforcement with step‑wise reward models—to achieve superior reasoning, safety, and performance over GPT‑4, heralding a shift toward models that learn to think.

Chain-of-ThoughtLLMSafety

0 likes · 42 min read

Understanding OpenAI o1: Chain‑of‑Thought, Scaling Laws, and Training Strategies

iQIYI Technical Product Team

Sep 26, 2024 · Artificial Intelligence

AI-Powered Search in iQIYI: Techniques, Architecture, and Implementation

iQIYI’s AI‑powered search expands beyond title‑only queries by handling fuzzy role, plot, star, award, and semantic searches, using Chain‑of‑Thought‑generated TIPS, Retrieval‑Augmented Generation with sophisticated indexing, chunking, embedding, reranking, and prompt‑engineering to deliver personalized, accurate video recommendations that boost user engagement.

AI SearchChain-of-ThoughtQuery Guidance

0 likes · 15 min read

AI-Powered Search in iQIYI: Techniques, Architecture, and Implementation

Tencent Cloud Developer

Jul 30, 2024 · Artificial Intelligence

A Systematic Guide to Prompt Engineering: From Zero to One

This guide walks readers from beginner to proficient Prompt Engineer by outlining the evolution of prompting, introducing a universal four‑component template, and detailing a five‑step workflow—including refinement, retrieval‑augmented generation, chain‑of‑thought reasoning, and advanced tuning techniques—plus evaluation metrics for LLM performance.

AI promptingChain-of-ThoughtLLM optimization

0 likes · 51 min read

A Systematic Guide to Prompt Engineering: From Zero to One