3 papers
cs.CL2025
Revisiting Test-Time Scaling: A Survey and a Diversity-Aware Method for Efficient Reasoning
Ho-Lam Chung, Teng-Yun Hsiao, Hsiao-Ying Huang +4
Test-Time Scaling (TTS) improves the reasoning performance of Large Language Models (LLMs) by allocating additional compute during inference. We conduct a structured survey of TTS…
cs.CL2024
Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization
Yu-Min Tseng, Yu-Chao Huang, Teng-Yun Hsiao +4
The concept of persona, originally adopted in dialogue literature, has re-surged as a promising framework for tailoring large language models (LLMs) to specific context (e.g., pers…
cs.LG2024
Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models
Dennis Wu, Jerry Yao-Chieh Hu, Teng-Yun Hsiao +1
We propose a two-stage memory retrieval dynamics for modern Hopfield models, termed , with enhanced memory capacity. Our key contribution is a learnable feat…