How do we make multiple robots work together seamlessly without getting bogged down by complexity? Researchers at the Chinese Academy of Sciences introduce the Sequential World Model (SeqWM), a novel approach where robots predict their own actions and share intentions based on
@jiqizhixin
-
RNNs with Growing Memory: Memory Caching Approaches
By
–
Memory Caching: RNNs with Growing Memory Paper:
-
RNNs Match Transformer Memory Without Quadratic Cost
By
–
Huge! Recurrent neural networks could match Transformer memory without the quadratic burden! Ali Behrouz from Google and colleagues have cracked it! They present Memory Caching (MC), a simple yet powerful method that lets RNNs store "memory checkpoints" of their internal
-
Efficient Cross-Domain Offline Reinforcement Learning with Data Filtering
By
–
Efficient Cross-Domain Offline Reinforcement Learning with Dynamics- and Value-Aligned Data Filtering Paper: https://
arxiv.org/pdf/2512.02435
Code: https://
github.com/zq2r/DVDF.git Our report: https://
mp.weixin.qq.com/s/ztE8GofcssuI
1PdkHx_kLg
… #PapersAccepted by Jiqizhixin -
AI Agents Learning Across Different Environments
By
–
How can AI agents learn effectively when their training data comes from environments vastly different from where they'll operate? Researchers from City University of Hong Kong, UIUC, Tencent, and Tsinghua University present DVDF, a new method for cross-domain offline
-
MeanCache: Accelerating Generative AI Without Quality Loss
By
–
Can we make generative AI models accelerate without sacrificing quality? Huanlin Gao and team from China Unicom & Nanjing University just unveiled MeanCache! This training-free caching framework tackles a key problem: traditional methods rely on instantaneous speed, leading to
-
DeepMind hires philosopher to investigate AI consciousness implications
By
–
DeepMind has hired a philosopher to study AI consciousness. I'm really curious about what exactly they've observed internally.
-
Deep Research Bench II Evaluates AI Research Agent Quality
By
–
How good are our AI research agents at producing genuinely insightful reports? University of Science and Technology of China and Metastone Technology just released "Deep Research Bench II". This new benchmark features 132 complex research tasks across 22 fields, evaluating AI
-
OpenSeeker: Open-Source AI Search Agent Achieves Frontier Performance
By
–
Cutting-edge AI search capabilities are open to everyone! Researchers at Shanghai Jiao Tong University unveil OpenSeeker, the first fully open-source search agent to achieve frontier performance. They did this by reverse-engineering the web to create complex, multi-hop search
-
ProMoE: Scaling Diffusion Transformers with MoE for Visual Data
By
–
Why has scaling Diffusion Transformers with Mixture-of-Experts been so tricky for visual data? Researchers from Fudan University, Alibaba Group's Tongyi Lab, Zhejiang University, The University of Hong Kong, and MMLab just cracked the code! They introduce ProMoE, an MoE