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Data Party THU
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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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Latest from Data Party THU

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Data Party THU
Data Party THU
Sep 22, 2026 · Artificial Intelligence

Why Your Multi-Agent System Is Costlier, Slower, and Worse Than a Single Agent

The article analyzes why multi-agent systems often underperform single agents, identifying context isolation as the key benefit only when tasks exceed a single context window, detailing six architectural patterns, cost multipliers up to 15x tokens, and a decision framework for choosing between multi-agent and single-agent approaches with proper engineering practices.

AI engineeringContext WindowLLM agents
0 likes · 19 min read
Why Your Multi-Agent System Is Costlier, Slower, and Worse Than a Single Agent
Data Party THU
Data Party THU
Sep 21, 2026 · Artificial Intelligence

When AI Talks Back: Why We Stop Seeing It as a Tool and Start Seeing It as a 'He'

This article explores how AI's human-like responses trigger anthropomorphism, detailing five cues (language, emotion, memory, style, proactive queries) that shift our perception from tool to social entity, the two dimensions of mind perception (experience and agency), the role of loneliness in social projection, and four signals (naming, attribution, emotional impact, boundary surrender) indicating AI has become a social object in our lives.

AI psychologyHeider-Simmel experimentLaMDA
0 likes · 25 min read
When AI Talks Back: Why We Stop Seeing It as a Tool and Start Seeing It as a 'He'
Data Party THU
Data Party THU
Sep 18, 2026 · Artificial Intelligence

Google AI Cyclone Model Outperforms High-Res Systems at 28km Resolution

Google's WeatherNext Cyclones (WN-C) AI model, published in Nature, achieves state-of-the-art tropical cyclone track and intensity forecasts using coarse 0.25° resolution data, outperforming specialized high-resolution models like HAFS and global systems like ENS and GenCast, with ensemble forecasts providing calibrated uncertainty and economic value, now operational at NHC.

AI weather modelingGoogle ResearchIBTrACS
0 likes · 7 min read
Google AI Cyclone Model Outperforms High-Res Systems at 28km Resolution
Data Party THU
Data Party THU
Sep 17, 2026 · Artificial Intelligence

TTTIR: Instance-Specific State Evolution for Image Restoration via Test-Time Training

TTTIR introduces a test-time training framework that models image restoration as progressive instance-specific state evolution, using a Progressive State Sequence Generator for target trajectories and a State Transition Evolver for adaptive operator updates, achieving state-of-the-art results on low-light enhancement, deraining, and dehazing benchmarks with minimal parameters.

DehazingDerainingInstance-Specific Adaptation
0 likes · 9 min read
TTTIR: Instance-Specific State Evolution for Image Restoration via Test-Time Training
Data Party THU
Data Party THU
Sep 16, 2026 · Artificial Intelligence

Anthropic Reveals Systemic Failures in Multi-Agent AI Collaboration

Anthropic's research exposes three systemic failure modes in multi-agent AI systems: escalating coordination costs, collective herd behavior causing resource contention and collusion, and information cascades that drown out critical minority insights, demonstrating that multi-agent risks require new governance infrastructure beyond individual agent alignment.

AI collaborationAI governanceAnthropic
0 likes · 13 min read
Anthropic Reveals Systemic Failures in Multi-Agent AI Collaboration
Data Party THU
Data Party THU
Sep 15, 2026 · Artificial Intelligence

RTWI: Reliable Multimodal Reasoning by Filtering Noisy Thinking

Sichuan University researchers propose RTWI, a plug-and-play test-time scaling framework that models reasoning reliability to filter noisy thinking in multimodal chain-of-thought, achieving higher accuracy and efficiency on benchmarks like Qwen3-VL and DeepEyes.

DeepEyesICML 2026Multimodal Reasoning
0 likes · 13 min read
RTWI: Reliable Multimodal Reasoning by Filtering Noisy Thinking
Data Party THU
Data Party THU
Sep 13, 2026 · Artificial Intelligence

Agentic AI Systems: Reasoning Loops, Tools & Guardrails Explained

This article contrasts traditional RAG pipelines with agentic AI systems, detailing the four core components—orchestrator, tool calling, memory, and guardrails—and demonstrates how reasoning loops enable multi-step problem solving for system design interviews.

Agentic AIGuardrailsMemory Management
0 likes · 16 min read
Agentic AI Systems: Reasoning Loops, Tools & Guardrails Explained
Data Party THU
Data Party THU
Sep 12, 2026 · Artificial Intelligence

Quantifying Neural Network Simplicity with Effective Degree: A Polynomial Approach

Tsinghua researchers propose Effective Degree (ED), a differentiable measure of neural network simplicity based on polynomial representations along data interpolation paths, which correlates strongly with generalization gap and can be used as a regularizer to improve performance across vision, language, and RL tasks.

Deep Learning TheoryEffective DegreeICML 2026
0 likes · 18 min read
Quantifying Neural Network Simplicity with Effective Degree: A Polynomial Approach
Data Party THU
Data Party THU
Sep 11, 2026 · Industry Insights

China's MIIT Unveils AI+Software Action Plan: 2028 Targets for Intelligent Programming & Agent Software

China's Ministry of Industry and Information Technology has issued a comprehensive implementation plan for AI-software integration, setting 2028 targets including intelligent programming tools for 20,000 enterprises, 100 intelligent agent applications, and 5 quality open-source projects, with a 2030 vision for global leadership in AI-driven software development and services.

AI+SoftwareChina MIITIntelligent Programming
0 likes · 21 min read
China's MIIT Unveils AI+Software Action Plan: 2028 Targets for Intelligent Programming & Agent Software