4 papers
SIGMA: Scalable Spectral Insights for LLM Model Collapse
Yi Gu, Lingyou Pang, Xiangkun Ye +4
The rapid adoption of synthetic data for training Large Language Models (LLMs) has introduced the technical challenge of "model collapse"-a degenerative process where recursive tra…
Taming Variability: Randomized and Bootstrapped Conformal Risk Control for LLMs
Lingyou Pang, Lei Huang, Jianyu Lin +3
We transform the randomness of LLMs into precise assurances using an actuator at the API interface that applies a user-defined risk constraint in finite samples via Conformal Risk…
Unsupervised Conformal Inference: Bootstrapping and Alignment to Control LLM Uncertainty
Lingyou Pang, Lei Huang, Jianyu Lin +4
Deploying black-box LLMs requires managing uncertainty in the absence of token-level probability or true labels. We propose introducing an unsupervised conformal inference framewor…
On seeded subgraph-to-subgraph matching: The ssSGM Algorithm and matchability information theory
Lingyao Meng, Mengqi Lou, Jianyu Lin +2
The subgraph-subgraph matching problem is, given a pair of graphs and a positive integer , to find vertices in the first graph, vertices in the second graph, and a bijec…