Escaping Mode Collapse in LLM Generation via Geometric Regulation
Mode collapse is a persistent challenge in generative modeling and appears in autoregressive text generation as behaviors ranging from explicit looping to gradual loss of diversity and premature trajectory convergence. We take a dynamical-systems view and reinterpret mode collapse as reduced state-space accessibility caused by *geometric collapse*: during generation, the model's internal trajectory becomes confined to a low-dimensional region of its representation space. This implies mode collapse is not purely a token-level phenomenon and cannot be reliably solved by symbolic constraints or probability-only decoding heuristics. Guided by this perspective, we propose *Reinforced Mode Regu...
| Authors | Xin Du, Kumiko Tanaka-Ishii |
|---|---|
| Primary category | cs.CL |
| Published | 1 May 2026 |
| Last updated at source | 31 July 2026 |
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