GPT-6-astra
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Headlines · 8
- Einsia launches Frontier3DBench for coding agents in 3D worlds
Einsia released Frontier3DBench, a benchmark with 145 tasks across nine categories that tests 11 model-harness configurations producing editable Blender projects and runnable Unreal Engine worlds. Evaluation covers appearance, structure and behavior through rendered views, scene inspection and runtime tests. Einsia reports that GPT-6.1-sol led overall, while GPT-6-astra led interactive-world tasks and MiniMax-M3.1-Flash ranked second in scene editing.
r/MachineLearning · 🔥 1 - Realtime-Bench Tests 12 Frontier Models on Dynamic Tasks
AIbase AI新闻 reports that NVIDIA and UT Austin introduced Realtime-Bench, a benchmark with 50 tasks across eight scenario types for assessing real-time perception, time-adaptive reasoning, and action timing. Researchers tested 12 frontier models under three environment-advancement clock protocols, and reportedly found that raising reasoning intensity did not reliably improve success. The report says GPT-6-Astra achieved a 44% task success rate when environments advanced according to actual reasoning time.
AIbase AI新闻 · 🔥 0 - PyRUA-REAL Turns Robot Exploration into Reusable Skills
A paper introduces PyRUA-REAL, a framework for embodied recursive self-improvement in which coding agents retain physical interaction experiences as persistent memory and reusable executable skills. The authors report an average success rate of 91.1% across eight real-world tasks and 84.4% across 42 tasks from the RoboDojo benchmark, including deployment without an online agent for decision-making. The paper also examines agent collaboration, execution feedback for code refinement, task specifications, robustness, and skill transfer.
Hugging Face · Papers · 🔥 0 - A Juejin author compares ten-year advice from several AI agents
A Juejin author prompted locally run Claude Code, Codex, Kimi, DeepSeek, Grok, and Antigravity agents for ten suggestions about the next ten years. The post reproduces outputs labeled Opus 5.5, GPT-6-Astra, and Kimi 3.1 Pro, with recurring themes including health, personal judgment, long-term focus, and systems for knowledge and automation. The author says the displayed agents broadly converged, while noting that several full outputs were omitted for space.
掘金 · 人工智能 · 🔥 0 - Realtime-Bench tests AI systems under real-time interaction
Researchers introduced Realtime-Bench, a 50-task benchmark for evaluating general-purpose AI systems whose decisions and actions must respond to changing conditions in real time. It includes 30 web tasks and 20 game tasks, measuring temporal state awareness, adaptive deliberation, and time-aware action selection under wall-clock, paused-clock, and token-clock conditions. Import AI reported that GPT-6-Astra achieved the highest wall-clock pass rate at 36%, while high-reasoning models approached 70% to 80% with the clock paused.
Import AI · 🔥 0 - LongChang tests whether LLMs can discover altered physical laws
A paper by Zhen Yang, Wen Wang, Xander Xu, and Ying-Cong Chen introduces LongChang, an automated framework for simulated worlds where one or more physical laws differ from ordinary physics. LLM agents explore these environments and design experiments without research-task hints, while separate agents generate scenes, review tools, and assess reports. Among 12 evaluated models, GPT-6-Astra achieved a 16.7% discovery rate, while the other 11 scored 0%.
Hugging Face · Papers · 🔥 0 - LLMs Show “Thinking Inertia” When Told to Answer Only
Researchers from Tsinghua University, the University of Oxford and Stanford University tested six models from the Qwen3, DeepSeek, GPT and Gemini families across six benchmarks. They found that disabling thinking mode and asking for answers without reasoning reduced, but did not eliminate, visible calculations or derivations. Explicit reasoning was most common on open-ended questions, while yes-or-no questions prompted more direct answers. The study introduced three metrics to assess answer-only compliance, relevance of preceding text and explicit reasoning separately. The paper, code and trajectory data are public. The source reported that the paper was accepted at NeurIPS 2026, and a separate community member ran a small-scale independent test that also observed reasoning after thinking was disabled.
新智元 · 🔥 0 - decomp.dev disables public index and leaderboard after AI-driven community disruption
The decomp.dev administrator said AI-assisted decompilation can substantially accelerate work when combined with guidance, human input, and code review, but has also encouraged rapid forks, rushed PC ports, and less sustained collaboration. The site therefore disabled its public index, leaderboard, and new-project intake while retaining existing project pages and historical data. Decompilation itself continues elsewhere, and no successor or shutdown date has been announced.
404 Media · 🔥 0
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