A Fast and Effective Solution to the Problem of Look-ahead Bias in LLMs

arXiv:2512.06607 · cs.LG, cs.CL · Submitted 2025-12-07 · Read on arXiv

cs.LG, cs.CL

Submitted: 2025-12-07

Updated: 2026-09-23

Terminology

• Benchmark — 11× in this paper · explained in 2 episodes
• Divergence Decoding — 8× in this paper
• Core — 6× in this paper · explained in 2 episodes
• Product of Experts — 4× in this paper
• alpha — 4× in this paper · explained in 1 episode
• Machine Unlearning — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Institutional Review Board — 2× in this paper
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Monte Carlo Analysis — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Scaling Laws — 1× in this paper · explained in 4 episodes

Sources

• Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning

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