2 papers
cs.AI2025
VIGOR+: Iterative Confounder Generation and Validation via LLM-CEVAE Feedback Loop
JiaWei Zhu, ZiHeng Liu
Hidden confounding remains a fundamental challenge in causal inference from observational data. Recent advances leverage Large Language Models (LLMs) to generate plausible hidden c…
cs.CL2025
Pipeline Parallelism is All You Need for Optimized Early-Exit Based Self-Speculative Decoding
Ruanjun Li, Ziheng Liu, Yuanming Shi +3
Large language models (LLMs) deliver impressive generation quality, but incur very high inference cost because each output token is generated auto-regressively through all model la…