๐ŸŽ“How I Study AIHISA
๐Ÿ“–Read
๐Ÿ“„Papers๐Ÿ“ฐBlogs๐ŸŽฌCourses
๐Ÿ’กLearn
๐Ÿ›ค๏ธPaths๐Ÿ“šTopics๐Ÿ’กConcepts๐ŸŽดShorts
๐ŸŽฏPractice
๐ŸงฉProblems๐ŸŽฏPrompts๐Ÿง Review
Search
How I Study AI - Learn AI Papers & Lectures the Easy Way

Papers2

AllBeginnerIntermediateAdvanced
All SourcesarXiv
#Attention Entropy

Rethinking LLM-as-a-Judge: Representation-as-a-Judge with Small Language Models via Semantic Capacity Asymmetry

Intermediate
Zhuochun Li, Yong Zhang et al.Jan 30arXiv

Big models are often used to grade AI answers, but they are expensive, slow, and depend too much on tricky prompts.

#Representation-as-a-Judge#Semantic Capacity Asymmetry#LLM-as-a-Judge

MHLA: Restoring Expressivity of Linear Attention via Token-Level Multi-Head

Intermediate
Kewei Zhang, Ye Huang et al.Jan 12arXiv

Transformers are powerful but slow because regular self-attention compares every token with every other token, which grows too fast for long sequences.

#Multi-Head Linear Attention#Linear Attention#Self-Attention