63 citations · 116 across the 10 of their papers we have counts for
4 papers · 1 filter
SALMON: Self-Alignment with Instructable Reward Models
Zhiqing Sun, Yikang Shen, Hongxin Zhang +5
Supervised Fine-Tuning (SFT) on response demonstrations combined with Reinforcement Learning from Human Feedback (RLHF) constitutes a powerful paradigm for aligning LLM-based AI ag…
Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints
Albert Lu, Hongxin Zhang, Yanzhe Zhang +2
The limits of open-ended generative models are unclear, yet increasingly important. What causes them to succeed and what causes them to fail? In this paper, we take a prompt-centri…
On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning
Omar Shaikh, Hongxin Zhang, William Held +2
Generating a Chain of Thought (CoT) has been shown to consistently improve large language model (LLM) performance on a wide range of NLP tasks. However, prior work has mainly focus…
Robustness of Demonstration-based Learning Under Limited Data Scenario
Hongxin Zhang, Yanzhe Zhang, Ruiyi Zhang +1
Demonstration-based learning has shown great potential in stimulating pretrained language models' ability under limited data scenario. Simply augmenting the input with some demonst…