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Linux 内核新补丁可提升大型 RAID5 阵列性能，最高增益 17%
IT之家 6 月 27 日消息，Phoronix 今日发现，Linux 内核开发者 Hiroshi Nishida 本周提交了一组 8 个补丁，旨在提升 MD RAID5 软件 RAID 在大型、多核心、多磁盘阵列上的可扩展性与重建路径性能。根据其公布的测试数据，在特定配置下，系统整体性能可提升约 …
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When Is Emergent Consensus Real? A Measured Coupling Gain and a Validity Diagnostic for LLM Agent Societies
创新提出耦合增益γ测量LLM智能体社会涌现共识，破解模型伪动态与真正社会行为的辨别难题。
arXiv:2606.22203v1 Announce Type: cross Abstract: LLM "agent societies" are studied via demonstrations of emergent consensus or polarization -- with n…
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How Much Coordination Gain Is Real? A Paired Noise-Floor Protocol for Multi-Agent LLM Benchmarks
新协议揭穿多智能体LLM协调增益的虚假繁荣，用配对噪声底线方法精准衡量真实协同效应。
arXiv:2606.20695v1 Announce Type: cross Abstract: Multi-agent LLM coordination papers report small benchmark deltas as evidence that one architecture …
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10 核 Wi-Fi7 路由器 269 元：中兴问天 BE6800 Pro＋新低，自研四振子全向增益天线
中兴问天 BE6800 Pro+ 路由器去年 4 月上市，配备自研四振子全向增益天线、支持 Xtra Range 3.0 技术， 售价 399 元 。 今日天猫旗舰店开启 618 补贴，88VIP 凑单叠加淘金币后，仅需 269 元破冰新低。 共需 3 步 点击下方卡片 → 加购物车 1 件 → 点…
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Heteroskedastic Signals in Budgeted LLM Verification: Structural Heterogeneity Limits Optimization Gains
揭示LLM验证中不确定性信号的结构异质性，指出资源分配优化增益存在上限。
arXiv:2606.15841v1 Announce Type: new Abstract: Large language model (LLM) systems increasingly use uncertainty signals to allocate limited computatio…
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From Correctness to Utility: Gain-Based Prefix Evaluation for LLM Reasoning
从追求正确性转向衡量实用性，这一新方法革新了LLM推理过程中的前缀评估策略。
arXiv:2606.07190v1 Announce Type: new Abstract: Reasoning prefixes shape the future trajectory of LLM problem solving, yet existing process reward mod…
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GraphWalker: Patient Analogy Meets Information Gain for Clinical Reasoning with Large Language Models
结合患者类比与信息增益，让LLM临床推理更精准、更可解释，方法新颖。
arXiv:2604.06684v2 Announce Type: replace Abstract: Clinical reasoning over electronic health records (EHRs) is a fundamental yet challenging task in …
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InfoMem: Training Long-Context Memory Agents with Answer-Conditioned Information Gain
新方法InfoMem用答案条件信息增益训练长上下文记忆代理，大幅提升模型知识检索与记忆能力。
arXiv:2606.03329v1 Announce Type: new Abstract: Long-context tasks require LLMs to identify and preserve answer-relevant information from large contex…
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Uncertainty-Aware Clarification in LLM Agents with Information Gain
让LLM Agent学会主动追问澄清：用信息增益量化不确定性，提升任务成功率与交互效率
arXiv:2606.03135v1 Announce Type: new Abstract: Large Language Model (LLM) agents often operate under underspecified user instructions, where latent u…
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A locus-coeruleus model for LLM agents (phasic and tonic attention gain)
蓝斑神经模型启发的LLM注意力增益机制，融合phasic/tonic调节与神经科学理论，代码已开源。
Article URL: https://github.com/mrshanebarron/lc-attention Comments URL: https://news.ycombinator.com/item?id=48289935 Points: 1 # Comments: 0
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Mind the Tool Failures: Achieving Synergistic Tool Gains for Medical Agents
医疗AI代理如何应对工具故障？这篇论文提出协同工具增益策略，让多个工具互补提升可靠性。
arXiv:2605.26691v1 Announce Type: new Abstract: Medical AI agents increasingly use external tools for diagnosis, treatment recommendation, and evidenc…
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CIG: Exploration via Conditional Information Gain
用条件信息增益(CIG)驱动智能体探索，为强化学习探索策略提供新思路。
arXiv:2605.20878v1 Announce Type: new Abstract: Intrinsic rewards for exploration in reinforcement learning condition on different contexts: lifelong …
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Self-Play Only Evolves When Self-Synthetic Pipeline Ensures Learnable Information Gain
揭示自我对弈仅在自合成数据提供可学习信息增益时才有效演化，为AI训练策略提供关键理论指导。
arXiv:2603.02218v2 Announce Type: replace Abstract: Large language models (LLMs) make it plausible to build systems that improve through self-evolving…