深度研究｜递归自我改进（RSI）全景 2026：AI 正在加速 AI，但「验证瓶颈」决定它能走多远
梳理 RSI 从 Good 1965 到 2026 的思想史、技术图谱与一手实证：Anthropic 承认其代码库 >80% 合并代码由 Claude 撰写、METR 测得 AI 可完成任务时长约每 4 个月翻倍、AlphaEvolve 优化了支撑自身的计算栈。核心判断——有界自我精炼已工程化，开放式 RSI 尚未发生；而进步与安全共享同一个「验证瓶颈」。
阅读全文 →
最新文章
LATEST 共 516 条When Models Edit Too Much: On the Fidelity of Minimal Code Edits
Large language models (LLMs) are increasingly used to edit existing code, but correctness alone is not enough: useful re…
The 2026 PNPL Competition: Word Classification and Efficient Cross-Subject Generalisation in LibriBrain100
The ambition of the 2025 PNPL competition (Landau et al., 2025) was to launch a multi-year curriculum for non-invasive s…
Select, Compress, Reinvest: A Controlled Study of Visual-Token Allocation in Long-Video MLLMs
Long-video language models cannot look at every frame: an hour sampled once per second is 3,600 images, and a system kee…
Unfold The World: Factorize 4D Properties in Reinforcing Spatial Reasoning
Despite the remarkable prowess of Vision-Language Models (VLMs) in general multimodal tasks, they remain fundamentally `…
Last Translation Benchmark
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that…
HarvestBench: Measuring Whether LLM Agents Will Pay to Avoid Killing Animals
Benchmarks for the side effects an agent causes on the way to a goal already exist, but HarvestBench is the first to put…
Compile by Training: Turning Natural-Language Specifications into Local Neural Functions
Many recurring text functions are easy to describe but difficult to implement with rules, while calling a large remote m…
Building and Evaluating Fixed-Voice Thai TTS from Synthetic Speech
In low-resource settings, deploying TTS typically requires choosing between a large voice-cloning model with costly infe…
How Far Can Synthetic Data Take Thai OCR?
We investigate what makes synthetic OCR supervision transfer to real Thai documents and use the resulting insights to bu…
MaxKernel: Agentic Kernel Generation for TPUs
Designing and authoring high-performance custom kernels for accelerators is a complex task that requires deep hardware-l…
One Editor, Many Edits: A Unified Training-Free Framework for Diverse Video Editing
Video editing spans diverse editing paradigms, yet achieving high-quality instruction-guided and subject-guided editing …
ENEAS: Embedding-guided Neural Ensemble for Adaptive Segmentation
We present ENEAS, a unified, text-promptable method for instance tracking and semantic discovery. Text-promptable segmen…