3 papers
cs.LG2025
Prompt Fairness: Sub-group Disparities in LLMs
Meiyu Zhong, Noel Teku, Ravi Tandon
Large Language Models (LLMs), though shown to be effective in many applications, can vary significantly in their response quality. In this paper, we investigate this problem of pro…
cs.LG2025
Speeding up Speculative Decoding via Sequential Approximate Verification
Meiyu Zhong, Noel Teku, Ravi Tandon
Speculative Decoding (SD) is a recently proposed technique for faster inference using Large Language Models (LLMs). SD operates by using a smaller draft LLM for autoregressively ge…
cs.LG2024
Learning Fair Robustness via Domain Mixup
Meiyu Zhong, Ravi Tandon
Adversarial training is one of the predominant techniques for training classifiers that are robust to adversarial attacks. Recent work, however has found that adversarial training,…