1 citations · 1 across the 4 of their papers we have counts for
4 papers
LLMs Are Not Good Strategists, Yet Memory-Enhanced Agency Boosts Reasoning
Yi Wu, Zhimin Hu
Strategic reasoning in Large Language Models (LLMs) within long-horizon environments is often limited by inconsistent subgoals. In these settings, finite attention resources preven…
ExVerus: Verus Proof Repair via Counterexample Reasoning
Jun Yang, Yuechun Sun, Yi Wu +5
Large Language Models (LLMs) have shown promising results in automating formal verification. However, existing approaches treat proof generation as a static, end-to-end prediction…
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…
Evolving Domain Adaptation of Pretrained Language Models for Text Classification
Yun-Shiuan Chuang, Yi Wu, Dhruv Gupta +7
Adapting pre-trained language models (PLMs) for time-series text classification amidst evolving domain shifts (EDS) is critical for maintaining accuracy in applications like stance…