3 papers
cs.LG2026
QEDBENCH: Quantifying the Alignment Gap in Automated Evaluation of University-Level Mathematical Proofs
Santiago Gonzalez, Alireza Amiri Bavandpour, Peter Ye +48
As Large Language Models (LLMs) saturate elementary benchmarks, the research frontier has shifted from generation to the reliability of automated evaluation. We demonstrate that st…
cs.AI2026
QV May Be Enough: Toward the Essence of Attention in LLMs
Zhang Edward
Starting from first principles and a linguistic perspective centered on part-of-speech (POS) and syntactic analysis, this paper explores and derives the underlying essence of the Q…
cs.CL2026
Attention's Gravitational Field:A Power-Law Interpretation of Positional Correlation
Edward Zhang
This paper explores the underlying principles of positional relationships and encodings within Large Language Models (LLMs) and introduces the concept of the Attention Gravitationa…