193 citations · 250 across the 17 of their papers we have counts for
17 papers
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.…
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…
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…
When Hindsight is Not 20/20: Testing Limits on Reflective Thinking in Large Language Models
Yanhong Li, Chenghao Yang, Allyson Ettinger
Recent studies suggest that self-reflective prompting can significantly enhance the reasoning capabilities of Large Language Models (LLMs). However, the use of external feedback as…
Identifying Self-Disclosures of Use, Misuse and Addiction in Community-based Social Media Posts
Chenghao Yang, Tuhin Chakrabarty, Karli R Hochstatter +3
In the last decade, the United States has lost more than 500,000 people from an overdose involving prescription and illicit opioids making it a national public health emergency (US…