4 papers
AI Realtor: Towards Grounded Persuasive Language Generation for Automated Copywriting
Jibang Wu, Chenghao Yang, Yi Wu +5
This paper develops an agentic framework that employs large language models (LLMs) for grounded persuasive language generation in automated copywriting, with real estate marketing…
LLM Probability Concentration: How Alignment Shrinks the Generative Horizon
Chenghao Yang, Sida Li, Ari Holtzman
Despite their impressive capabilities, aligned large language models (LLMs) often generate outputs that lack diversity. What drives this consistency in the generation? We investiga…
Let it Calm: Exploratory Annealed Decoding for Verifiable Reinforcement Learning
Chenghao Yang, Lin Gui, Chenxiao Yang +3
Reinforcement learning with verifiable rewards (RLVR) is a powerful paradigm for enhancing the reasoning capabilities of large language models (LLMs), yet its success hinges on eff…
Tokenized Bandit for LLM Decoding and Alignment
Suho Shin, Chenghao Yang, Haifeng Xu +1
We introduce the tokenized linear bandit (TLB) and multi-armed bandit (TMAB), variants of linear and stochastic multi-armed bandit problems inspired by LLM decoding and alignment.…