5 papers
Diffusion Language Model Inference with Monte Carlo Tree Search
Zheng Huang, Kiran Ramnath, Yueyan Chen +8
Diffusion language models (DLMs) have recently emerged as a compelling alternative to autoregressive generation, offering parallel generation and improved global coherence. During…
SQL-Trail: Multi-Turn Reinforcement Learning with Interleaved Feedback for Text-to-SQL
Harper Hua, Zhen Han, Zhengyuan Shen +9
While large language models (LLMs) have substantially improved Text-to-SQL generation, a pronounced gap remains between AI systems and human experts on challenging benchmarks such…
BoundRL: Efficient Structured Text Segmentation through Reinforced Boundary Generation
Haoyuan Li, Zhengyuan Shen, Sullam Jeoung +6
Structured texts refer to texts containing structured elements beyond plain texts, such as code snippets and placeholders. Such structured texts increasingly require segmentation i…
PromptPrism: A Linguistically-Inspired Taxonomy for Prompts
Sullam Jeoung, Yueyan Chen, Yi Zhang +3
Prompts are the interface for eliciting the capabilities of large language models (LLMs). Understanding their structure and components is critical for analyzing LLM behavior and op…
A Systematic Survey of Automatic Prompt Optimization Techniques
Kiran Ramnath, Kang Zhou, Sheng Guan +18
Since the advent of large language models (LLMs), prompt engineering has been a crucial step for eliciting desired responses for various Natural Language Processing (NLP) tasks. Ho…