4 citations · 4 across the 3 of their papers we have counts for
4 papers · 1 filter
STEER-BENCH: A Benchmark for Evaluating the Steerability of Large Language Models
Kai Chen, Zihao He, Taiwei Shi +1
Steerability, or the ability of large language models (LLMs) to adapt outputs to align with diverse community-specific norms, perspectives, and communication styles, is critical fo…
Smoothing Out Hallucinations: Mitigating LLM Hallucination with Smoothed Knowledge Distillation
Hieu Nguyen, Zihao He, Shoumik Atul Gandre +3
Large language models (LLMs) often suffer from hallucination, generating factually incorrect or ungrounded content, which limits their reliability in high-stakes applications. A ke…
Improving and Assessing the Fidelity of Large Language Models Alignment to Online Communities
Minh Duc Chu, Zihao He, Rebecca Dorn +1
Large language models (LLMs) have shown promise in representing individuals and communities, offering new ways to study complex social dynamics. However, effectively aligning LLMs…
COMMUNITY-CROSS-INSTRUCT: Unsupervised Instruction Generation for Aligning Large Language Models to Online Communities
Zihao He, Minh Duc Chu, Rebecca Dorn +2
Social scientists use surveys to probe the opinions and beliefs of populations, but these methods are slow, costly, and prone to biases. Recent advances in large language models (L…