3 papers
cs.LG2025
PROPS: Progressively Private Self-alignment of Large Language Models
Noel Teku, Fengwei Tian, Payel Bhattacharjee +3
Alignment is a key step in developing Large Language Models (LLMs) using human feedback to ensure adherence to human values and societal norms. Dependence on human feedback raises…
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…