11 citations · 52 across the 19 of their papers we have counts for
6 papers · 1 filter
SCE: Scalable Consistency Ensembles Make Blackbox Large Language Model Generation More Reliable
Jiaxin Zhang, Zhuohang Li, Wendi Cui +3
Large language models (LLMs) have demonstrated remarkable performance, yet their diverse strengths and weaknesses prevent any single LLM from achieving dominance across all tasks.…
A Survey of Automatic Prompt Optimization with Instruction-focused Heuristic-based Search Algorithm
Wendi Cui, Zhuohang Li, Hao Sun +5
Recent advances in Large Language Models have led to remarkable achievements across a variety of Natural Language Processing tasks, making prompt engineering increasingly central t…
SEE: Strategic Exploration and Exploitation for Cohesive In-Context Prompt Optimization
Wendi Cui, Zhuohang Li, Hao Sun +5
Designing optimal prompts for Large Language Models (LLMs) is a complicated and resource-intensive task, often requiring substantial human expertise and effort. Existing approaches…
DCR-Consistency: Divide-Conquer-Reasoning for Consistency Evaluation and Improvement of Large Language Models
Wendi Cui, Jiaxin Zhang, Zhuohang Li +4
Evaluating the quality and variability of text generated by Large Language Models (LLMs) poses a significant, yet unresolved research challenge. Traditional evaluation methods, suc…
SAC3: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency
Jiaxin Zhang, Zhuohang Li, Kamalika Das +2
Hallucination detection is a critical step toward understanding the trustworthiness of modern language models (LMs). To achieve this goal, we re-examine existing detection approach…
Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision
Jiaxin Zhang, Zhuohang Li, Kamalika Das +1
Large language models (LLMs) have demonstrated remarkable capabilities in various tasks. However, their suitability for domain-specific tasks, is limited due to their immense scale…