The article identifies signals of slop, which refers to low-quality content regardless of its origin. Key indicators include repetition, lack of intentionality, and low information density. Repetitiveness causes fatigue and often stems from imitation or superficial copying. Slop lacks meaningful details, and its content is often expanded with filler rather than substantive information.
The chart will appear after repeat observations. The current metric comes from the source.
9 source pointsReal observations only. History before source connection is not reconstructed.
Useful for identifying low-quality content in both AI-generated and human-created materials, helping to distinguish between meaningful and superficially produced work.
IntBMoE introduces a block-conditioned Mixture-of-Experts (MoE) framework that decouples participation, execution, and materialization by combining dense expert composition with sparse block execution. It uses a learned codebook for blocks and a hypernetwork to merge experts, achieving full participation while keeping execution and memory costs low. Experiments show improvements in image classification, language modeling, and sequential recommendation, with real-world deployment in AMap's recommendation system.
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2 days agoDaily PapersCodeMidas is an agentic pipeline that converts implemented functionality in open-source codebases into executable reinforcement learning (RL) environments using only source code as input. It generates 5,545 training tasks from 3,185 codebases across 23 languages and 15 domains, improving performance on multiple coding benchmarks when training MiMo-V2.5 with GRPO.
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5 days ago