MingLiiii

Efficient-LLMs-Survey

[TMLR 2024] Efficient Large Language Models: A Survey

Layer_Gradient

What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective

MingLiiii.github.io

alpaca_eval

An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.

Cherry_LLM

[NAACL'24] Self-data filtering of LLM instruction-tuning data using a novel perplexity-based difficulty score, without using any other models

DEBATunE

[ACL'24] Can LLMs Speak For Diverse People? Tuning LLMs via Debate to Generate Controllable Controversial Statements

Mosaic-IT

Mosaic IT: Enhancing Instruction Tuning with Data Mosaics

Reflection_Tuning

[ACL'24] Selective Reflection-Tuning: Student-Selected Data Recycling for LLM Instruction-Tuning

RuleR

RuleR: Improving LLM Controllability by Rule-based Data Recycling

Superfiltering

[ACL'24] Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning

MingLiiii/Layer_Gradient

What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective

MingLiiii/MingLiiii.github.io