The Flexibility Trap: Rethinking the Value of Arbitrary Order in Diffusion Language Models
Tests whether arbitrary token order helps reasoning in diffusion language models. JustGRPO uses left-to-right RL rollouts to investigate avoidance of uncertain decisions while retaining parallel inference decoding.
Overview
Tests whether arbitrary token order helps reasoning in diffusion language models. JustGRPO uses left-to-right RL rollouts to investigate avoidance of uncertain decisions while retaining parallel inference decoding.
Tests whether arbitrary token order helps reasoning in diffusion language models. JustGRPO uses left-to-right RL rollouts to investigate avoidance of uncertain decisions while retaining parallel inference decoding.
When reading the original paper, identify its problem, inputs, outputs, and methodological assumptions.
Tests whether arbitrary token order helps reasoning in diffusion language models. JustGRPO uses left-to-right RL rollouts to investigate avoidance of uncertain decisions while retaining parallel inference decoding.
Check the baselines, datasets, evaluation protocol, and ablations in the original paper. This directory overview does not provide an independent evaluation or experimental results table.
References
ID: icml-2026-flexibility-trap · Last verified:
