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研究Teaching Everyone to Fish for Tokens(interconnects.ai)
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jack-clark.net
研究Import AI 469: Science AI; RSI simulator; and Zuck’s technological pessimism(jack-clark.net)
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研究How much hydrogen awaits us underground?(technologyreview.com)
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研究SAGE: Surrogate-gradient Adaptation via Attention-Guided Entropy for Spiking Transformers(arxiv.org)
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研究Inducing Reward-Free Judging Rubrics that Reduce Over-Crediting in Agent Evaluation(arxiv.org)
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研究Depth-Aware Sensitivity Analysis of Mixture-of-Experts Models via Magnitude-Based Expert Masking(arxiv.org)
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研究CutClean: Neural Network Pruning for Privacy-Preserving Inference(arxiv.org)
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研究Evaluating Agentic Learning Harness Capabilities Without Labels via the Scaling Hypothesis(arxiv.org)
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研究Don't Claim Benchmark-Oriented Optimization Improves General Coding Capability -- Diverse Evaluation Is Required(arxiv.org)
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研究The Integer Alibi: Localizing Cross-Kernel Divergence in INT8-Quantized LLM Inference(arxiv.org)
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研究L-FNO: Lorentzian Fourier Neural Operator for Stochastic Event Dynamics(arxiv.org)
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研究How Compliant is Sepsis Treatment? An Expert-Guided Neuro-symbolic Pipeline for Generating Clinical Compliance Insights(arxiv.org)
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103
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研究A Year in LLM Serving: Workload Evolution, Caching and Load-Balancing(arxiv.org)
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研究From BERT to Frontier Agents: Eight Years of Language-Model Progress, the Collapse of the Capability-Cost Curve, and the Rise of Task-Targeted Models(arxiv.org)
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研究Agentao: A Governed Local-First Runtime for Tool-Using LLM Agents(arxiv.org)
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研究Measuring Cross-Task Behavioral Consistency in Language Model Agents(arxiv.org)
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107
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研究MobileMem: Learning from a Year of Mobile Experiences(arxiv.org)
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108
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研究Robust XGBoosting for Regression(arxiv.org)
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109
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研究AI Evaluation Should Work With Humans(arxiv.org)
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研究Hard Cases, Bad Labels: Testing Error Exposure and Error Location in Uncertainty Sampling Under Bounded Label Noise(arxiv.org)
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研究Paper claims RL for reasoning only changes 1-3% of tokens, and they replicate the gains without RL at ~1000x less compute(reddit.com)
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研究Does DiffusionGemma do latent reasoning?(alignmentforum.org)
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研究GLM-5.3: How Chinese labs keep stride with the frontier(interconnects.ai)
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研究The Download: Flock’s new rules, cloning’s future, and children’s cells(technologyreview.com)
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研究Job titles of the future: Space travel agent(technologyreview.com)
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研究This scientist is helping build a missing map of childhood(technologyreview.com)
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研究CAS: A Causal Attribution Score for Local and Global Explainable Artificial Intelligence(arxiv.org)
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研究Agreement Is Not Alignment: Divergent Moral Grounds in Human and LLM Ethical Judgments(arxiv.org)
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研究Unifying Generative Models with Path Integrals(arxiv.org)
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研究Research Assistant: AstraZeneca's Agentic System for R&D(arxiv.org)
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