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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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Recent Articles

Latest from Data Party THU

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

From Reasoning to Physical Execution: Peking University Papers Push LLMs Toward Fully Automated Labs

The article analyzes how two Peking University papers presented at ICML 2026 and ACL 2026 introduce BioProBench and BioProAgent to benchmark and enable large language models to safely perform complex wet‑lab experiments, achieving high physical compliance and integrating into a multi‑agent AI4S LAB platform.

AI for ScienceBioProAgentBioProBench
0 likes · 7 min read
From Reasoning to Physical Execution: Peking University Papers Push LLMs Toward Fully Automated Labs
Data Party THU
Data Party THU
Jun 22, 2026 · Artificial Intelligence

Who Won the 2026 Big Data Challenge Monthly Star Awards? Winners Share Their Competition Insights

The 2026 China University Big Data Challenge announced its Monthly Star winners, each receiving a prize, and the top three teams detailed their data processing, feature engineering, model design, training strategies, and post‑processing techniques for cross‑sectional stock ranking.

Big Data CompetitionTime Seriesfeature engineering
0 likes · 10 min read
Who Won the 2026 Big Data Challenge Monthly Star Awards? Winners Share Their Competition Insights
Data Party THU
Data Party THU
Jun 21, 2026 · Industry Insights

Why AI Robotics Won’t See a Single “ChatGPT‑Style” Breakthrough

The IEEE Spectrum analysis argues that AI‑driven robots will not be transformed by a single breakthrough like ChatGPT; instead, progress will come from a suite of coordinated AI tools, massive data collection, hardware advances, and incremental real‑world deployments.

AI roboticsHardwareIEEE Spectrum
0 likes · 11 min read
Why AI Robotics Won’t See a Single “ChatGPT‑Style” Breakthrough
Data Party THU
Data Party THU
Jun 21, 2026 · Artificial Intelligence

Lance: A Lightweight 3B Multimodal AI Model that Handles Vision, Video, Generation, and Editing

Lance, an open‑source 3‑billion‑parameter multimodal model from ByteDance, unifies image and video understanding, generation, and editing in a single architecture, achieves top scores on VBench (85.11), MVBench (62.0), GenEval (0.90) and GEdit‑Bench (7.30), and demonstrates emergent cross‑task generalization.

LanceMaPEbenchmark results
0 likes · 9 min read
Lance: A Lightweight 3B Multimodal AI Model that Handles Vision, Video, Generation, and Editing
Data Party THU
Data Party THU
Jun 20, 2026 · Artificial Intelligence

Can Large Language Models Fall into a Silent Spiral? Uncovering AI Opinion Monopoly and Governance Solutions

This article examines how large language models can autonomously generate a digital “silence spiral,” suppressing minority viewpoints and creating opinion monopolies, outlines empirical evidence from recent ACL and arXiv studies, and proposes a three‑dimensional governance framework spanning technical, regulatory, and research interventions.

Large Language ModelsRAGgovernance framework
0 likes · 17 min read
Can Large Language Models Fall into a Silent Spiral? Uncovering AI Opinion Monopoly and Governance Solutions
Data Party THU
Data Party THU
Jun 19, 2026 · Artificial Intelligence

The Six Critical Choices Every AI Engineer Must Make

This article examines six production trade‑offs that AI engineers face—build vs. buy LLMs, model complexity vs. maintainability, data quantity vs. quality, batch vs. real‑time inference, prompt engineering vs. fine‑tuning, and automation vs. human‑in‑the‑loop—backed by surveys, research studies, and concrete cost analyses.

AI engineeringData QualityFine-tuning
0 likes · 15 min read
The Six Critical Choices Every AI Engineer Must Make
Data Party THU
Data Party THU
Jun 18, 2026 · Artificial Intelligence

Why Large Language Models Are Short‑Sighted and How Next‑ToBE Unlocks Anticipatory Reasoning

The article examines the short‑sighted nature of current next‑token prediction in LLMs, presents the Next‑ToBE (Next Token‑Bag Exploitation) method that reshapes the training objective to expose latent future‑token awareness, and shows through extensive experiments that this approach improves anticipatory reasoning and downstream task performance.

Anticipatory ReasoningFuture Token PredictionLLM evaluation
0 likes · 12 min read
Why Large Language Models Are Short‑Sighted and How Next‑ToBE Unlocks Anticipatory Reasoning
Data Party THU
Data Party THU
Jun 17, 2026 · Artificial Intelligence

Breakthrough or Hype? Over 2,000 Scholars Sign AI‑Mathematics Leiden Declaration Warning AI’s Limits in Fundamental Science

The AI‑Mathematics Leiden Declaration, signed by more than two thousand scholars, warns that unchecked AI hype and commercial motives risk distorting mathematical research, producing misleading proofs, and undermining the independent, rigorous nature of fundamental science despite recent AI breakthroughs.

AI EthicsAI HypeArtificial Intelligence
0 likes · 7 min read
Breakthrough or Hype? Over 2,000 Scholars Sign AI‑Mathematics Leiden Declaration Warning AI’s Limits in Fundamental Science
Data Party THU
Data Party THU
Jun 17, 2026 · Artificial Intelligence

Engineering Embodied AI Robots: Reusable Frameworks and Code Templates for Sim‑to‑Real Transfer

The article presents engineering approaches for embodied intelligent robots, focusing on reusable software frameworks and code templates that enable Sim‑to‑Real transfer, including ROS2 integration of active inference libraries (pymdp, spm), modular behavior‑tree control loops, and an intrinsic‑motivation engine with practical deployment and tuning guidelines.

Active InferenceBehavior TreeIntrinsic Motivation
0 likes · 17 min read
Engineering Embodied AI Robots: Reusable Frameworks and Code Templates for Sim‑to‑Real Transfer
Data Party THU
Data Party THU
Jun 16, 2026 · Artificial Intelligence

How a T‑Shaped Outfit Evades Both Visible‑Light and Thermal Detectors – Tsinghua’s New Multimodal Adversarial Method

Tsinghua researchers propose a non‑overlapping RGB‑T adversarial clothing that uses printable fabric for visible‑light patterns and aluminum film for thermal patterns, achieving over 90% attack success in digital simulations and about 60% success in real‑world tests across multiple fusion detectors.

3D ModelingRGB-Tadversarial attack
0 likes · 9 min read
How a T‑Shaped Outfit Evades Both Visible‑Light and Thermal Detectors – Tsinghua’s New Multimodal Adversarial Method