BestHub
Sign in
Data Party THU
Author

Data Party THU

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

507
Articles
0
Likes
2.4k
Views
0
Comments
Recent Articles

Latest from Data Party THU

100 recent articles max
Data Party THU
Data Party THU
Aug 30, 2026 · Artificial Intelligence

Foundations and Frontiers of Multimodal Agentic Frameworks: A Comprehensive Survey

This survey systematically maps the core modules, technical lineage, and emerging applications of multimodal agentic frameworks, detailing perception, orchestration, and action components, taxonomy of multimodal fusion strategies, performance bottlenecks, efficiency tricks, scalability challenges, latency sources, safety risks, current limitations, and promising future research directions.

Agentic FrameworksEfficiencyaction
0 likes · 21 min read
Foundations and Frontiers of Multimodal Agentic Frameworks: A Comprehensive Survey
Data Party THU
Data Party THU
Aug 26, 2026 · Artificial Intelligence

How ‘Good’ Adversarial Attacks Can Safeguard Visual Content Throughout Its Lifecycle

This survey examines proactive protection methods—ranging from privacy filters and non‑learnable samples to generative safeguards, adversarial captchas, and traceability mechanisms—that embed adversarial perturbations before visual content is shared, trained, generated, accessed, or disputed, and evaluates them across transferability, adaptability, and deployment maturity.

AI securityadversarial attacksadversarial captcha
0 likes · 19 min read
How ‘Good’ Adversarial Attacks Can Safeguard Visual Content Throughout Its Lifecycle
Data Party THU
Data Party THU
Aug 23, 2026 · Artificial Intelligence

How DeepMind’s WeatherNext Gives AI a One‑Day Head‑Start on Superstorm Intensity Forecasts

Google DeepMind’s WeatherNext AI model, trained on 20 TB of global atmospheric data and a curated historical cyclone database, can predict tropical cyclone tracks, intensity and structure up to a day earlier than traditional systems, generating ensemble forecasts up to 15 days ahead with competitive accuracy.

AI forecastingDeep LearningNature
0 likes · 7 min read
How DeepMind’s WeatherNext Gives AI a One‑Day Head‑Start on Superstorm Intensity Forecasts
Data Party THU
Data Party THU
Aug 22, 2026 · Artificial Intelligence

RL‑100 Merges Imitation and Reinforcement Learning for High‑Performance Robot Manipulation

The RL‑100 framework combines imitation learning from human tele‑operation with offline and online reinforcement learning to refine diffusion‑based control policies, achieving 100 % success across eight real‑world robot tasks, matching or surpassing human operators in speed while maintaining stability and low latency.

Imitation LearningRL-100diffusion models
0 likes · 7 min read
RL‑100 Merges Imitation and Reinforcement Learning for High‑Performance Robot Manipulation
Data Party THU
Data Party THU
Aug 21, 2026 · Artificial Intelligence

Survey of Autonomous Research Agents: Bridging the AI Scientist Verification Gap

This survey examines how large‑language‑model‑driven AI scientists now span the full research lifecycle, yet most systems provide scant evidence for reproducibility and claim verification, analyzing 35 works to reveal audit gaps and propose a concrete reporting checklist for trustworthy autonomous research.

AI scientistsLLMaudit framework
0 likes · 15 min read
Survey of Autonomous Research Agents: Bridging the AI Scientist Verification Gap
Data Party THU
Data Party THU
Aug 19, 2026 · Artificial Intelligence

Weights vs. Skills: How Robot Learning Shifts from Action Prediction to Self-Written Skills

This survey maps a decade of robot‑learning research onto a weight‑vs‑skill axis, classifies 77 representative systems into six technical branches, analyzes their trade‑offs, highlights emerging skill‑economy challenges, and proposes measurable metrics for future self‑improving robotic systems.

AI roboticscode-as-policyrobot learning
0 likes · 17 min read
Weights vs. Skills: How Robot Learning Shifts from Action Prediction to Self-Written Skills
Data Party THU
Data Party THU
Aug 18, 2026 · Artificial Intelligence

How to Master Online and Offline Policy Learning in Massive Action Spaces

This article reviews a PhD thesis that systematically studies online and offline learning for contextual bandits with huge action spaces, highlighting statistical, computational, and optimization challenges and presenting mixed‑effect Thompson sampling, diffusion priors, structured direct methods, and PAC‑Bayes pessimism as effective solutions.

PAC-BayesThompson samplingcontextual bandits
0 likes · 18 min read
How to Master Online and Offline Policy Learning in Massive Action Spaces
Data Party THU
Data Party THU
Aug 17, 2026 · Artificial Intelligence

Causal Inference for Text and Image Outcomes: Discovering the Most Affected Feature

This article reviews the paper “Causal Inference with Unstructured Outcomes”, explaining how the authors extend causal analysis from scalar results to text and image data by defining a max‑contrast feature, presenting identification conditions, estimation algorithms, and extensive experiments on formalness, toxicity, image blur, and paired treatment‑result scenarios.

causal inferencegenerative AIimage analysis
0 likes · 14 min read
Causal Inference for Text and Image Outcomes: Discovering the Most Affected Feature
Data Party THU
Data Party THU
Aug 17, 2026 · Artificial Intelligence

How Real Feedback Drives Continuous Skill Evolution for AI Agents

The article explains a three‑layer Skill architecture for AI agents, shows how real user feedback is turned into concrete rule updates across routing, instruction, and resource layers, and describes iterative refinement, compaction, and validation before releasing new Skill versions.

AI AgentsFeedback iterationSkill Design
0 likes · 12 min read
How Real Feedback Drives Continuous Skill Evolution for AI Agents