Why Do Sequential LLMs Hit a Bottleneck? Test-time compute scaling in LLMs has traditionally relied on extending single reasoning paths. While this approach improves reasoning for a limited range, performance plateaus quickly. Experiments on DeepSeek-R1-distill-Qwen-1.5B show that increasing token budgets beyond 32K (up to 128K) yields negligible accuracy gains. The bottleneck arises from early token […] The post ParaThinker: Scaling LLM Test-Time Compute with Native Parallel Thinking to Overcome Tunnel Vision in Sequential Reasoning appeared first on MarkTechPost.
ParaThinker: Scaling LLM Test-Time Compute with Native Parallel Thinking to Overcome Tunnel Vision in Sequential Reasoning
Why Do Sequential LLMs Hit a Bottleneck? Test-time compute scaling in LLMs has traditionally relied on extending single reasoning paths. While this approach improves reasoning for a limited range, performance plateaus quickly. Experiments on DeepSeek-R1-distill-Qwen-1.5B show that increasing token budgets beyond 32K (up to 128K) yields negligible accuracy gains. The bottleneck arises from early token […] The post ParaThinker: Scaling LLM Test-Time Compute with Native Parallel Thinking to Overcome Tunnel Vision in Sequential Reasoning appeared first on MarkTechPost.