Unverified50% confidenceFactExact time
The entire process is based on a frozen encoder, leaving the original weights of SPEAR and WavLM unchanged, and only reorganizing representations at the output level.
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50%
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Long-term
Relevance
10/9/2026
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UnverifiedApproaches that fall between frozen embeddings and full fine-tuning include fine-tuning only the last few layers, using parameter-efficient fine-tuning methods such as LoRA, or employing an adapter architecture.66% similarUnverifiedStructured Outputs通过约束解码（Constrained Decoding）技术实现，在模型生成token时动态限制可选token的范围63% similarUnverified该模型的架构设计目标是让每个token的解码速度只取决于激活参数而非总参数62% similarUnverifiedSpeculative decoding improves generation throughput while guaranteeing that the output is completely identical to that of the original model.62% similarUnverifiedThe decode phase of large language model inference generates only one token at a time and is a memory-bandwidth-bound operation, because generating each token requires loading the entire model weights from memory once.61% similar
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