3 papers
cs.CL2026
Semantic Chunking and the Entropy of Natural Language
Weishun Zhong, Doron Sivan, Tankut Can +2
The entropy rate of printed English is famously estimated to be about one bit per character, a benchmark that modern large language models (LLMs) have only recently approached. Thi…
q-bio.NC2025
Synaptic Theory of Chunking in Working Memory
Weishun Zhong, Mikhail Katkov, Misha Tsodyks
Working memory often appears to exceed its basic span by organizing items into compact representations called chunks. Chunking can be learned over time for familiar inputs; however…
cond-mat.stat-mech2025
Random Tree Model of Meaningful Memory
Weishun Zhong, Tankut Can, Antonis Georgiou +3
Traditional studies of memory for meaningful narratives focus on specific stories and their semantic structures but do not address common quantitative features of recall across dif…