Xiaoxia (Shirley) Wu — accepted AI-conference papers

2026

V1: Unifying Generation and Self-Verification for Parallel Reasoners

Harman Singh, Xiuyu Li, Kusha Sareen, Monishwaran Maheswaran, Sijun Tan, Xiaoxia (Shirley) Wu +11

ICML 2026poster

Test-time scaling for complex reasoning tasks shows that leveraging inference-time compute, for example by independently sampling and aggregating multiple solutions, results in significantly better task outcomes. However, a critical bottleneck is _verification_: sampling is only effective if correct…

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2026

When RL Meets Adaptive Speculative Training: A Unified Training-Serving System

Fengxiang Bie, Junxiong Wang, Jisen Li, Zhongzhu Zhou, Chenfeng Xu, Zelei Shao +8

ICML 2026poster

Speculative decoding can significantly accelerate LLM serving, but its real-world benefits often erode due to training–serving mismatch and non-stationary traffic. Unlike previous systems that decouple speculator training from inference, we present a unified training–serving system, Aurora, that clo…

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