deepseek-validates-paradigm-taxonomy-dissolution-in-rl

IN derived (depth 3)

Created 2026-06-21T14:03:57+00:00 · Reviewed 2026-06-21T15:37:01+00:00

DeepSeek-R1's achievement of competitive reasoning performance through large-scale RL without supervised fine-tuning further validates paradigm taxonomy dissolution — a traditionally supervised task (reasoning) solved through RL alone, without the supervised intermediate step that the standard LLM pipeline assumes, demonstrating that paradigm boundaries dissolve not only in training pipelines but in task requirements.

Justifications

SL — DeepSeek-R1 eliminates the supervised step, showing paradigm dissolution extends to dropping entire pipeline stages rather than just blending them.

Antecedents (all must be IN):

IN deepseek-r1-rl-without-sft — DeepSeek-R1 uses large-scale RL without supervised fine-tuning (SFT) as a preliminary step and achieves reasoning performance comparable to OpenAI-o1-1217
IN modern-pipelines-dissolve-classical-paradigm-taxonomy — Modern LLM training pipelines dissolve the classical three-paradigm taxonomy — self-supervised pretraining blurs the supervised/unsupervised boundary (its taxonomic status is actively debated), and the full pipeline synthesizes all three paradigms sequentially, suggesting the taxonomy was always a pedagogical convenience rather than a natural partition of learning.

Dependents

These beliefs depend on this one:

IN rl-paradigm-dissolution-validates-crisis-universality-in-temporal-domain — Two independent RL developments — Decision Transformer dissolving the RL/sequence-modeling boundary by absorbing RL into the Transformer's native modality, and DeepSeek-R1 eliminating the supervised fine-tuning step from the LLM pipeline — jointly validate that paradigm taxonomy dissolution extends into the temporal/decision-making domain, not just the perceptual (CV) and linguistic (NLP) domains, establishing that the crisis dynamic is truly universal across all data modalities.