Anthropic 发布了 Claude Opus 4.8，该版本具有增强的努力度控制、动态工作流和在编码任务中提高的诚实度。这个新模型在 SWE-bench Pro 和 GraphWalks 等基准测试中取得了显著进步，同时还提供了一个更快、更便宜的模式。该版本旨在通过提供更强大的配置和对齐来解决 AI 编码代理中常见的失败模式，例如约束违反和过度自信。 AI
影响 在编码基准测试上设定了新的 SOTA（State-of-the-Art），并提高了代理的可靠性，可能加速先进 AI 编码助手的采用。
排序理由 来自前沿实验室（Anthropic）的新旗舰模型发布。
AI 生成摘要 · Google Gemini · 来自 9 个来源。 我们如何撰写摘要 →
arXiv:2606.00579v1 Announce Type: new Abstract: As multimodal LLMs increasingly target video and audio, it is often assumed that such tasks require native omnimodal models. We show that this is not always the case: coding agents with only text+image access and a sandboxed tool-us…
arXiv:2603.03202v3 Announce Type: replace Abstract: As large language models (LLMs) advance their mathematical capabilities toward the IMO and research level, the scarcity of challenging, high-quality problems has become a significant bottleneck for training, evaluation and self-…
arXiv:2604.11088v2 Announce Type: replace Abstract: Random rules improve a coding agent's task performance as much as expert-curated ones (both $+13.8$pp on a discriminative subset of SWE-bench Verified), and in our data every individually beneficial rule is a negative constraint…
arXiv:2605.29442v1 Announce Type: cross Abstract: AI coding agents increasingly act directly within software environments, yet existing analyses of their failures rely on benchmark trajectories that miss how developers actually experience misalignment. We present an observational…
AI coding agents increasingly act directly within software environments, yet existing analyses of their failures rely on benchmark trajectories that miss how developers actually experience misalignment. We present an observational study of 20,574 coding-agent sessions from 1,639 …
arXiv:2603.24631v2 Announce Type: replace-cross Abstract: Code agents resolve 65-70% of SWE-bench Verified issues, but Pass@1 cannot tell us why the rest fail, and, as we show, capable-model failures are systematically misdiagnosed without trajectory data. We introduce TRAJEVAL, …
<p>The frontier model race has been moving in fits and starts. OpenAI shipped GPT-5.5 and a new Codex line. Google pushed Gemini 3.1 Pro and a faster Gemini Flash. xAI keeps iterating on Grok. And now Anthropic has shipped <strong>Claude Opus 4.8</strong>, only 41 days after Opus…
<!-- SC_OFF --><div class="md"><p>We ended up building two products: the software we ship, and the system/harness around our agents that makes them useful in building the thing we ship.</p> <p>A harness is the durable layer around a model: instructions, tools, permissions, contex…