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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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On-Device Deep Research at 4B: Exposure Bounds Faithfulness, Retrieval Bounds Coverage
Researchers analyzed the citation faithfulness and coverage of a four-billion parameter research agent running locally on a consumer laptop.
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Optimization Is Not All You Need
This paper critiques the prevailing optimization culture in AI alignment, arguing that evaluating models solely on predefined, measurable axes fails to capture true value.
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The Model Knows Your Project, Not You: Measuring Recognition in LLMs with NameRank
The paper introduces NameRank, a metric designed to measure how well large language models recognize specific researchers and tools within their parametric memory.
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Internet of Agentic Things: Networked AI Agents for Closed-Loop IoT Orchestration
The paper introduces the Internet of Agentic Things, an architectural framework that connects autonomous AI agents across cloud, edge, and physical IoT layers.
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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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Experience Memory Graph: One-Shot Error Correction for Agents
A new error-correction method called Experience Memory Graph aims to help LLM agents recover from failures in long-horizon tasks more efficiently than traditional reflection techniques.
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Interventional Grounding Audits: Black-Box Premise-Dependency Tests for LLM Chain-of-Thought via Predicate Substitution
A new auditing method uses predicate substitution to test whether large language models genuinely rely on stated premises during chain-of-thought reasoning.
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STOCKTAKE: Measuring the Gap Between Perception and Action in LLM Agents with a Fair Oracle
A new evaluation framework called STOCKTAKE aims to distinguish between perception errors and execution failures in LLM agents during long-term decision-making tasks.
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Federated Explainable Artificial Intelligence: Roles, Architectures, Evaluation, and Open Challenges
This review examines the integration of explainable AI techniques within federated learning architectures to improve transparency in privacy-preserving distributed model training.
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Interaction Protocol Shapes Moral Judgment in Multi-Agent Debate
A study demonstrates that the interaction protocols used in multi-agent debates significantly influence the moral reasoning and judgment outcomes of large language models.
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DIVE: Embedding Compression via Self-Limiting Gradient Updates
DIVE is a new dimensionality reduction technique for language model embeddings that uses self-limiting gradient updates to improve compression efficiency.
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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.