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Data Party THU

Official platform of Tsinghua Big Data Research Center, sharing the team's latest research, teaching updates, and big data news.

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Recent Articles

Latest from Data Party THU

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Data Party THU
Data Party THU
Apr 29, 2026 · Artificial Intelligence

How Far Can Unsupervised RL for Large Models Go? A Systematic Answer from a Tsinghua Team

The article analyzes the scaling limits of unsupervised reinforcement learning for large language models, revealing that intrinsic‑reward methods initially boost performance but inevitably collapse, proposes a unified theory and a model‑collapse metric to predict trainability, and argues that external‑reward approaches are the scalable path forward.

AI researchRL scalingexternal rewards
0 likes · 11 min read
How Far Can Unsupervised RL for Large Models Go? A Systematic Answer from a Tsinghua Team
Data Party THU
Data Party THU
Apr 29, 2026 · Artificial Intelligence

Claude Opus 4.7 System Prompt Leak: Decoding Its 10 Core Design Decisions

The article dissects the leaked Claude Opus 4.7 system prompt, revealing ten intertwined design decisions—from treating psychological reconstruction as a danger signal to dynamic safety‑policy upgrades—that together shape the model’s self‑restraint, tool‑use, memory handling, and risk‑aware behavior.

AI safetyClaudeSystem Design
0 likes · 8 min read
Claude Opus 4.7 System Prompt Leak: Decoding Its 10 Core Design Decisions
Data Party THU
Data Party THU
Apr 28, 2026 · Artificial Intelligence

Mathematicians Declare an AI Turning Point in Mathematics

The article surveys recent observations from leading mathematicians who report that AI breakthroughs—ranging from solving most IMO problems in 2025 to accelerating research with systems like AlphaEvolve—signal a decisive turning point in how mathematics is explored, proved, and taught.

AIAlphaEvolveMathematical Research
0 likes · 14 min read
Mathematicians Declare an AI Turning Point in Mathematics
Data Party THU
Data Party THU
Apr 28, 2026 · Artificial Intelligence

How MiniMax Drives Joint Evolution of Models and Harnesses

The article analyzes MiniMax’s strategy of co‑evolving large language models with a Harness framework, contrasting product philosophies, detailing a live MaxHermes demo that creates and refines reusable Skills, and explaining how this dual evolution reshapes the competitive focus from single‑turn Q&A to sustained, self‑improving agent workflows.

AI agentsHermesMiniMax
0 likes · 14 min read
How MiniMax Drives Joint Evolution of Models and Harnesses
Data Party THU
Data Party THU
Apr 27, 2026 · Artificial Intelligence

Three Overlooked Failure Points in RAG Pipelines and How to Build a Feedback Loop

The article analyzes silent failures in Retrieval‑Augmented Generation pipelines, identifies three gaps—retrieval relevance, LLM confidence masking uncertainty, and missing fault signals—and presents a practical feedback‑loop architecture with relevance gating, post‑generation evaluation, session tracing, and user‑signal logging to make production RAG systems trustworthy.

LLMObservabilityRAG
0 likes · 13 min read
Three Overlooked Failure Points in RAG Pipelines and How to Build a Feedback Loop
Data Party THU
Data Party THU
Apr 26, 2026 · Artificial Intelligence

Meta-Encoder Unleashes Pathology Model Cluster Power, Sets New Records on International Datasets

Researchers from Shanghai Jiao Tong University introduce the Meta‑Encoder, a unified integration framework that dynamically combines multiple pathological foundation models, achieving superior cancer detection performance across diverse tasks and datasets while maintaining low computational cost.

Cancer DetectionComputational EfficiencyMeta-Encoder
0 likes · 8 min read
Meta-Encoder Unleashes Pathology Model Cluster Power, Sets New Records on International Datasets
Data Party THU
Data Party THU
Apr 26, 2026 · Industry Insights

Multimodal Perception and AI Fusion: Highlights from Tsinghua’s 9th Big Data Intelligent Lecture

The 9th Tsinghua Big Data Intelligent Lecture gathered leading scholars and industry experts to showcase cutting‑edge research on multimodal perception, embodied intelligence, spatial AI, large‑model multimodal systems, and industrial time‑series databases, emphasizing their technical depth and real‑world impact.

Artificial IntelligenceGLM5V TurboSenseNova
0 likes · 8 min read
Multimodal Perception and AI Fusion: Highlights from Tsinghua’s 9th Big Data Intelligent Lecture
Data Party THU
Data Party THU
Apr 25, 2026 · Artificial Intelligence

Google & Microsoft Harnesses: Core LLM Post‑Training Methods and 2025‑2026 Trends

These two recent papers—Microsoft’s M⋆, which evolves task‑specific memory harnesses, and Google’s AutoHarness, which automatically generates code‑level constraints—demonstrate reflective code evolution and tree‑search synthesis, achieving state‑of‑the‑art performance across diverse benchmarks and outlining LLM post‑training directions for 2025‑2026.

AgentAutoHarnessHarness
0 likes · 10 min read
Google & Microsoft Harnesses: Core LLM Post‑Training Methods and 2025‑2026 Trends
Data Party THU
Data Party THU
Apr 24, 2026 · Artificial Intelligence

OpenAI Unveils GPT‑Rosalind: A New AI Model for Accelerating Life‑Science Research

OpenAI introduced GPT‑Rosalind, a purpose‑built reasoning model for biology, drug discovery and translational medicine that streamlines evidence synthesis, hypothesis generation and experiment planning, and demonstrates leading performance on benchmarks such as BixBench and LABBench2 while offering free plugins that connect to over fifty scientific tools and data sources.

BixBenchGPT‑RosalindLABBench2
0 likes · 8 min read
OpenAI Unveils GPT‑Rosalind: A New AI Model for Accelerating Life‑Science Research
Data Party THU
Data Party THU
Apr 23, 2026 · Artificial Intelligence

The Complete 2026 Agentic AI Engineer Roadmap: A Systematic Learning Path

This guide presents a step‑by‑step roadmap for becoming an Agentic AI engineer in 2026, covering Python fundamentals, LLM concepts, framework selection, advanced memory management, tool integration, production deployment, and interview preparation with concrete examples and best‑practice recommendations.

LLMLangGraphPython
0 likes · 10 min read
The Complete 2026 Agentic AI Engineer Roadmap: A Systematic Learning Path