Adaptive Mutual Distillation for Balanced Multi-Task Post-Training of Large Language Models
cs.CL
Submitted: 2026-10-02
Updated: 2026-10-02
Code: https://github.com/open-compass/opencompass
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges
- Scaling Instruction-Finetuned Language Models
- The Llama 3 Herd of Models
- Distilling the Knowledge in a Neural Network
- Infinity Instruct: Scaling Instruction Selection and Synthesis to Enhance Language Models
- DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining
- DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services
- Adaptive Multi-Teacher Knowledge Distillation with Meta-Learning
Related papers
- Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
- Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
- Subliminal Steering: Stronger Encoding of Hidden Signals
- MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
- The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
- Untangling the Mechanisms of Misleading Context in Medical Question Answering