6 papers
Online Verification of Language Model Responses Under Cost Constraints
Erfan Hajihashemi, Yanning Shen
As large language models are increasingly deployed for multi-step reasoning, verifying the correctness of their outputs has become essential for maintaining reliability at scale. V…
Enhanced Multi-model Online Conformal Prediction
Erfan Hajihashemi, Yanning Shen
Conformal prediction is a framework for uncertainty quantification that constructs prediction sets for previously unseen data, guaranteeing coverage of the true label with a specif…
Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models
Jipeng Li, Yanning Shen
Explicit noise-level conditioning is widely regarded as essential for the effective operation of Graph Diffusion Models (GDMs). In this work, we challenge this assumption by invest…
Multi-model Online Conformal Prediction with Graph-Structured Feedback
Erfan Hajihashemi, Yanning Shen
Online conformal prediction has demonstrated its capability to construct a prediction set for each incoming data point that covers the true label with a predetermined probability.…
FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning
Lisha Chen, AFM Saif, Yanning Shen +1
Finding specific preference-guided Pareto solutions that represent different trade-offs among multiple objectives is critical yet challenging in multi-objective problems. Existing…
Multi-model Ensemble Conformal Prediction in Dynamic Environments
Erfan Hajihashemi, Yanning Shen
Conformal prediction is an uncertainty quantification method that constructs a prediction set for a previously unseen datum, ensuring the true label is included with a predetermine…