Distilling What Matters: Confidence-Aware Selective Distillation for Large Language Models
cs.CL
Submitted: 2026-09-29
Updated: 2026-09-29
Code: https://github.com/openlm-research/open_llama
Terminology
Sources
- Sequence-Level Knowledge Distillation
- Why Language Models Hallucinate
- Large Language Models are overconfident and amplify human bias
- DistiLLM: Towards Streamlined Distillation for Large Language Models
- Language Models (Mostly) Know What They Know
- Bayesian Active Learning for Classification and Preference Learning
- Distilling the Knowledge in a Neural Network
- OPT: Open Pre-trained Transformer Language Models
- Gemma 2: Improving Open Language Models at a Practical Size
- Qwen2 Technical Report
- DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence
- Evaluating Large Language Models Trained on Code
- Program Synthesis with Large Language Models
- Qwen2.5 Technical Report
- Training Verifiers to Solve Math Word Problems
- MathScale: Scaling Instruction Tuning for Mathematical Reasoning
- Patient Knowledge Distillation for BERT Model Compression
- Revisiting Knowledge Distillation for Autoregressive Language Models
- Knowledge Distillation Based on Transformed Teacher Matching
- MiniLLM: On-Policy Distillation of Large Language Models
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