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1539 technical news articles
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GAUGE puts physics engines and generative world models through the same real-world benchmark, diagnosing errors separately in trajectories, equation forms, and physical parameters. The results show that visually plausible output—or even conformity to the correct equation form—does not guarantee accurate acceleration, momentum transfer, or oscillation periods.
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MIST tests not only whether models can resist incorrect prompts, but also whether they still incorporate accurate external information. Its companion method, SCOPE, reduced Qwen3-4B’s correct-to-wrong rate from 35.0% to 16.3%, though training has so far been validated on only two families of small open models.
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A new study compiles API schemas into typed Python stubs, allowing models to chain or invoke tools in parallel within a single inference. The method matches or outperforms native JSON for most models on a BFCL v4 subset, but it has so far been tested only with simulated tools that return their arguments, so the results do not establish that real-world API workflows would see the same benefits.
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GeniWorld first uses URDF to convert joint actions into pixel-aligned robot motion, then employs a causal DiT to predict how the environment will respond. Across four real-world tasks, the authors report that the overall success rate increased from 40.8% to 69.0%, although neither the code nor model weights have been released.
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A new study audits video models using executable temporal trajectories rather than checking only final counts. In the high-event-count, high-frequency regime, Gemini 3.6 Flash answered just 0.2% correctly and recovered only 18.1% of ground-truth events.
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HarnessOpt-Bench asks models to modify prompts, tools, memory, and control flow within a fixed evaluation budget, then measures actual gains on an unseen test set. Across 111 experiments, the model itself accounted for more variation than the outer coding harness, while native tools did not consistently outperform shared ones.
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TrajDebug does not treat the first error in an agent trajectory as the root cause. Instead, it tracks whether errors are repaired, whether they leave an impact on the final outcome, and how much recovery budget they consume. In tests on 486 human-annotated trajectories, converting diagnoses into prompts improved the success rate of rerunning the same tasks by 10.8% on average.
最新模型
The study traces the difference between Adam and low-rank recovery to the coordinate-wise preconditioner’s lack of gauge equivariance. In published experiments, two functionally equivalent initializations trained with Adam produced attention invariants that differed by 56%, though the findings have not yet been validated in large-model pretraining.
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Rather than treating teacher–student discrepancies at every token equally, DASH adjusts how far supervision can propagate based on the entire generation trajectory. The authors report consistent gains on three mathematics benchmarks and have released the training code, evaluation pipeline, and LoRA weights.
Reasoning Core 用可執行評分器、難度控制與短答案格式產生數學、規劃、形式證明及程式題。匹配訓練實驗顯示它優於三套程序資料集，但作者也在外部資料庫發現生成器與評分器不一致。
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A new study distinguishes persistent AGENTS.md files from task-specific Agent Plans and examines how plans enter public version histories. The sample is heavily concentrated in a handful of projects, suggesting that treating plans as collaborative artifacts remains an early and unstable practice.
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Muse Code packages Muse Spark 1.2 as a terminal agent capable of working on large codebases in parallel within isolated worktrees. Its append-only event log can reconstruct state after a process interruption, though the performance figures still come primarily from Meta itself.