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Xiaoou Liu

3 accepted papers

2026

Diagnosing Multi-step Reasoning Failures in Black-box LLMs via Stepwise Confidence Attribution

ICML 2026poster

Large Language Models have achieved strong performance on reasoning tasks with objective answers by generating step-by-step solutions, but diagnosing where a multi-step reasoning trace might fail remains difficult. Confidence estimation offers a natural diagnostic signal, yet existing methods are re…

Cited by 0SourceScholar
2026

Position: Uncertainty Quantification in LLMs is Just Unsupervised Clustering

ICML 2026poster

Uncertainty Quantification (UQ) is widely regarded as the primary safeguard for deploying Large Language Models (LLMs) in high-stakes domains. However, \textbf{we argue that the field suffers from a category error: prevailing UQ methods are just unsupervised clustering algorithms.} We demonstrate th…

Cited by 0SourceScholar
2024

Hear You Say You: An Efficient Framework for Marine Mammal Sounds’ Classification

AAAI 2024technical

Marine mammals and their ecosystem face significant threats from, for example, military active sonar and marine transportation. To mitigate this harm, early detection and classification of marine mammals are essential. While recent efforts have utilized spectrogram analysis and machine learning tech…

Cited by 0SourcePDFScholar