Anthropic CEO 长文《We Must Pace the Frontier》：首次呼吁为前沿 AI 能力进步"限速"，三步走方案详解
Dario Amodei 发文主张放慢 AI 能力提升速度，提出"嵌入式评估员—民主国家协调—全球协调"三步走方案，第一步 Anthropic 已单方面承诺执行；Altman 与马斯克罕见附和，业内同时出现"监管俘获"质疑。
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共 218 条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…
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…
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…
AdaptVPR: Route-Aware Hard Positive Generation for Robust Visual Place Recognition
Visual Place Recognition (VPR) localizes a query image by retrieving database images of the same or nearby place, yet it…
Let Confidence Change, Not the Prediction: Prediction-Preserving Repair for Post-hoc Calibration
Post-hoc calibration corrects reported confidence, yet a multiclass calibrator can also change the associated top-1 pred…
A Common Measure of Communication for Speech Brain-Computer Interfaces
Speech brain-computer interfaces (speech BCIs) translate neural activity into language, offering a path towards restorin…
ShallowStream: Index Shallow then Answer Deep for Streaming Video Understanding
Streaming video understanding is a critical capability for real-world applications, including embodied intelligence, aut…
Unifying Conformal Language Tasks with In-Context Ensembles
Many NLP tasks, such as summarization and extractive question answering, reduce to retrieving relevant content from docu…
Causal Foundation Models
Causal inference is the practice of estimating the effect of a treatment or intervention from data. It traditionally req…
Verify Before You Distill: Prompt-Level Teacher Gating for On-Policy Distillation
On-policy distillation (OPD) accelerates post-training by providing dense token-level supervision from a frozen teacher …
Graph Machine: Towards Better Pretraining via Edges
We introduce the Graph Machine (GM), an architecture that maintains an O(n)-sized state and accesses it through sparse, …