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Firefox in WebAssembly
Developers have successfully compiled the Firefox browser into WebAssembly, allowing it to run entirely within another web browser.
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独家｜把芯片设计交给AI，上海AI Lab李林阳创业获数千万元首轮融资
Chinese startup Novasilicon has secured multi-million yuan in seed funding to develop AI-driven chip design solutions.
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Alphabet spin-out Verrus plans three-building data center campus outside Portland, Oregon
Verrus, an Alphabet spin-out, is planning the construction of a new grid-reactive data center campus in Oregon to support infrastructure needs.
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德明利：预计上半年净利润为57亿元–65亿元
Chinese storage company Demingli projects a first-half net profit of up to 6.5 billion yuan, reversing a previous loss due to surging AI-driven storage demand.
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In China’s electronics hub, a memory chip crisis is hitting consumers hard
The global artificial intelligence boom has driven up memory and solid-state drive prices in Shenzhen's Huaqiangbei electronics market, significantly increasing costs for PC builders.
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Discrete Diffusion Models: A Unified Framework from Tokenization to Generation
A new framework for discrete diffusion models explores how tokenization and vocabulary structure influence generative performance.
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Reassessing Muon for Matrix Factorization
This paper provides a theoretical analysis of the Muon optimizer to clarify the mechanisms behind its performance advantages in large-scale deep learning.
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SteinGate: Tail-Sensitive Safe Reinforcement Learning via Stein Discrepancy
The SteinGate framework introduces a new safety certification method for reinforcement learning to better mitigate rare but catastrophic risks.
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STKAN: Kolmogorov-Arnold Networks for Spatio-Temporal Forecasting
The authors introduce STKAN, a spatio-temporal forecasting architecture that leverages Kolmogorov-Arnold Networks to better model complex traffic data.
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Learning Engagement Assistant (LEA): Cross-Course Scalability and Classroom Evaluation of an Agentic AI Tutoring System
A study evaluates the scalability and classroom performance of an AI tutoring agent that integrates retrieval-augmented generation with structured knowledge models.
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ScanFocus: A Coarse-to-Fine Framework for Spatio-Temporal Video Grounding
The proposed ScanFocus framework addresses computational efficiency and precision in spatio-temporal video grounding through a coarse-to-fine processing approach.
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The Hitchhiker's Guide to Monoculture
An analysis of Kaggle contest submissions examines whether the use of AI coding assistants is leading to increased homogenization of software development outputs.
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When Bots Join the Team: Bot Adoption and the Institutional Fabric of Open-Source Software Projects
Researchers analyzed nearly 3,000 GitHub projects to understand how the integration of automated bots as active participants influences the organizational structure of open-source software teams.
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From Language to Navigation Goals: A Vision-Language Approach for Semantic Navigation of Mobile Robots Using RGB-D Perception
A new framework enables mobile robots to interpret natural language commands for autonomous navigation using RGB-D perception.
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Anatomically Faithful but Temporally Blind: Auditing Attribution for Left-Ventricular Ejection-Fraction Estimation from Echocardiography
A study evaluating deep learning models for echocardiography analysis reveals that current attribution methods often fail to verify temporal faithfulness in medical imaging predictions.
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IMMNet: Hybrid Fusion of Model-based and Data-driven Approaches for Maneuvering Target Tracking
IMMNet integrates traditional model-based tracking algorithms with neural components to improve the accuracy and interpretability of maneuvering target tracking in 3D environments.
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How Far Can Root Cause Analysis Go on Real-World Telemetry Data?
A study evaluating root cause analysis in microservice failures reveals that current AI and classical methods struggle to effectively process large-scale, multimodal telemetry data.
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Set-shifting Behavioral Test for Harnessed Agents
A new benchmark based on cognitive psychology tests has been developed to evaluate how AI agents adapt when the reliability of their tools changes during operation.
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Traffic-Aware Randomized Smoothing for LLM-Based Network Intrusion Detection
A new defense mechanism called Traffic-Aware Randomized Smoothing has been proposed to improve the robustness of LLM-based network intrusion detection systems against traffic manipulation.
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Unleashing Multimodal Large Language Models for Training-free HOI Detection in the Wild
Researchers have proposed a training-free approach for detecting human-object interactions in the wild by leveraging the capabilities of multimodal large language models.
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Generative Compilation: On-the-Fly Compiler Feedback as AI Generates Code
The authors present a method for integrating compiler feedback directly into the autoregressive decoding process to improve the quality of AI-generated code.
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The SIGReg Objective as Variational Free Energy: A Theoretical Active-Inference Account of JEPA World Models
The paper provides a theoretical framework linking Joint-Embedding Predictive Architectures to active inference principles through variational free energy.
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A Causal Model of Theory of Mind in Conflict for Artificial Intelligence
This paper proposes a causal framework to determine when artificial intelligence systems should engage in theory of mind processes during conflict scenarios.
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MASPRM: Multi-Agent System Process Reward Model
The Multi-Agent System Process Reward Model provides a method to evaluate and optimize message sequences between agents during inference-time search.