#InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models
Paper
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2308.07074
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Published
LLM-Instruct
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Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing
Paper • 2310.13855 • Published • 1 -
LIMIT: Less Is More for Instruction Tuning Across Evaluation Paradigms
Paper • 2311.13133 • Published -
Group Preference Optimization: Few-Shot Alignment of Large Language Models
Paper • 2310.11523 • Published -
The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning
Paper • 2312.01552 • Published • 30 -
Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision
Paper • 2312.09390 • Published • 32 -
The Impact of Reasoning Step Length on Large Language Models
Paper • 2401.04925 • Published • 16 -
DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
Paper • 2310.03714 • Published • 31 -
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Paper • 2402.17193 • Published • 23 -
Mixture-of-Instructions: Comprehensive Alignment of a Large Language Model through the Mixture of Diverse System Prompting Instructions
Paper • 2404.18410 • Published -
Self-Harmonized Chain of Thought
Paper • 2409.04057 • Published • 16 -
SurveySum: A Dataset for Summarizing Multiple Scientific Articles into a Survey Section
Paper • 2408.16444 • Published • 8 -
Instruction Following without Instruction Tuning
Paper • 2409.14254 • Published • 27