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Meta 的 AI 数学论文开始标注模型参与
Meta 公布 6 篇与 Muse Spark 协作的数学论文。更值得关注的是贡献来源、第二组复核、并行结果和形式化验证怎样进入公开论文。
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Google 让 Gboard 的联邦学习隐私可以被外部审计
Google 把 TEE、访问策略、远程证明、透明日志和可复现构建接成联邦学习的外部验证链,并已用于 Gboard 下一词预测。
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Agent markets: 85% of the loss comes before negotiation
Anthropic's book market experiment locates most efficiency loss in preference representation. A look at model choice, preference evals, and market rules.
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Anthropic Agent 市场:85% 的效率损失发生在谈判前
Anthropic 的 Agent 市场实验显示,主要效率损失发生在偏好表示和匹配阶段。本文拆解模型选择、偏好 Eval 与市场规则。
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Claude takes a candidate to the lab, not a new CRISPR
About 950 Claude agents helped identify ART. Human wet-lab experiments confirmed short RNA expression, but its main biological function remains unknown.
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Claude 把候选推进湿实验,但这不是新 CRISPR
Anthropic 用约 950 个 Claude Agent 从大规模逆转录酶候选中筛出 ART,并由人类湿实验验证短 RNA 表达,但 ART 的主要功能仍未知。
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When to split a task across agents: check dependencies
How task dependencies shape multi-agent results, with SAIGE experiments, ablations, and OpenAI guidance for deciding when to delegate.
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一个任务什么时候该拆成多个 Agent?先看依赖关系
Rethinking Multi-Agent Collaboration 说明多 Agent 的收益取决于任务依赖结构。本文结合 SAIGE 主实验、消融实验和 OpenAI 多 Agent 工程建议,整理可执行的委派判断。
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Qwen-Image 2.1: native RGBA and commercial licensing
Qwen-Image 2.1 offers native RGBA, unified generation and editing, up to 10 reference images, and 2K output. Commercial use needs a separate license.
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Qwen-Image 2.1 原生透明图很适合做资产,但商用要另取许可
Qwen-Image 2.1 支持原生 RGBA、统一生成编辑、最多 10 张参考图和 2K 输出,但仓库许可证默认只授权非商业研究与评测。
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How to score a coding agent that finishes 80% but fails
Android Bench 2.0 keeps pass rate as a hard gate and adds completion rate to diagnose progress and unfinished acceptance requirements.
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Coding Agent 做完 80% 还失败,Eval 怎么记
Android Bench 2.0 保留 Pass rate 作为硬门禁,再用 Completion rate 解释长任务已经完成多少,以及问题卡在哪一类验收。
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Anthropic opens internal processes to embedded evaluators
Anthropic and Accenture extend evaluation beyond model outputs to training, deployment, monitoring, and incident processes, with independence unresolved.
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Anthropic 让第三方 Eval 进入内部,模型评测开始看过程
Anthropic 与 Accenture 的 embedded evaluator 计划把评测范围从模型输出扩展到训练、部署、监控和事故流程,也暴露出独立性边界。
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Should an agent keep going or start a fresh attempt?
Use When Agents Slow Down, Reflexion, Hyperband, and agent evaluation to compare continued revision with independent attempts under reproducible budgets.
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Agent 该继续跑,还是重新开一轮?读懂预算分配、记忆与评测
结合 When Agents Slow Down、Reflexion、Hyperband 和 Agent 评测,说明怎样比较连续修改与独立尝试,并设计可复现的预算分配实验。
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Agentic search missed an incident. Test the eval too
The Anthropic incident review shows why automated monitors and LLM graders need coverage, independence, and tests for their own failure modes.
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Agentic Search 漏掉第四起事故,Eval 也要被测试
从 Anthropic Agentic Search 事故复盘看自动监控和 LLM grader 的漏检问题,说明 Agent Eval 也需要覆盖率、独立性和失效模式测试。
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