OUTLETS: Output-Length Prediction from Speculative Decoding Backbones

arXiv:2609.01068 · cs.CL · Submitted 2026-09-01 · Read on arXiv

cs.CL

Submitted: 2026-09-01

Updated: 2026-09-10

Terminology

• Speculative Decoding — 30× in this paper · explained in 2 episodes
• Decode — 16× in this paper · explained in 2 episodes
• Large Language Model — 10× in this paper
• Accuracy — 9× in this paper · explained in 1 episode
• Transformer — 7× in this paper · explained in 2 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Fidelity — 4× in this paper · explained in 2 episodes
• Ablation Studies — 3× in this paper · explained in 1 episode
• Large Language Model (LLM) — 3× in this paper · explained in 3 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Adaptive Weighting — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 4 episodes
• Communication Overhead — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• For Load Balancing — 1× in this paper
• Generalization — 1× in this paper · explained in 13 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Mixture-of-Experts (MoE) — 1× in this paper · explained in 7 episodes
• Perception in Advance — 1× in this paper
• Regret — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Training-Time Test — 1× in this paper
• Unified Framework — 1× in this paper · explained in 5 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• Evaluating Large Language Models Trained on Code
• GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks
• Training Verifiers to Solve Math Word Problems
• Overclocking LLM Reasoning: Monitoring and Controlling Thinking Path Lengths in LLMs
• STAR: Decode-Phase Rescheduling for LLM Inference
• OPT: Open Pre-trained Transformer Language Models
• LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

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