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data-scaling

topic2 events
papersTODAY 04:00 UTC

Study Ties Data and Memory Scaling to a Single Predictive Spectrum

A new arXiv paper argues that the benefit a model gains from more data and the amount of learned memory it needs are both determined by one predictive-energy spectrum in a positive-entropy autoregressive retrieval source. In this framework, each coordinate's contribution is the product of its query probability and a per-coordinate term, linking the two resources analytically. The work offers a theoretical account of how data volume and memory capacity trade off in autoregressive prediction.

research/scaling/memory/autoregressive
papersTODAY 04:00 UTC

Knowledge-enhanced approach proposed for single-cell foundation models

A new arXiv paper examines how single-cell foundation models depend on large transcriptomic pretraining datasets, noting that adding more data brings diminishing returns at rising computational cost. The authors' data scaling analysis suggests incorporating structured biological knowledge could improve efficiency instead of relying on scale alone. The work points toward knowledge-enhanced pretraining as an alternative direction for the field.

foundation-models/single-cell/pretraining/research