When Built-in Thinking Helps and Hurts: Constraint-Level Error Shifts in Instruction Following
Large reasoning models (LRMs) often improve math and coding performance, but their effect on instruction following is unclear. We study IFEval with Qwen3 models (1.7B-32B), using same-weights Thinking ON/OFF controls; four Hunyuan models provide directional cross-family support. Aggregate pass-rate changes are small (-0.55 to -3.52 pp), yet 10-20% of prompts switch between pass and fail across modes, suggesting that thinking changes the pattern of errors--some prompts improve while others worsen--rather than uniformly degrading performance. Under a post-hoc Qwen3-derived grouping, constraint types separate into Planning (global counting, structure, coordination), which improves at the cla...
| Authors | Sai Adith Senthil Kumar |
|---|---|
| Primary category | cs.CL |
| Published | 8 June 2026 |
| Last updated at source | 8 June 2026 |
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