5 papers
Conformal Risk Control
Anastasios N. Angelopoulos, Stephen Bates, Adam Fisch +2
We extend conformal prediction to control the expected value of any monotone loss function. The algorithm generalizes split conformal prediction together with its coverage guarante…
Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA
Sangmin Bae, Adam Fisch, Hrayr Harutyunyan +3
Large language models (LLMs) are expensive to deploy. Parameter sharing offers a possible path towards reducing their size and cost, but its effectiveness in modern LLMs remains fa…
Block Transformer: Global-to-Local Language Modeling for Fast Inference
Namgyu Ho, Sangmin Bae, Taehyeon Kim +6
We introduce the Block Transformer which adopts hierarchical global-to-local modeling to autoregressive transformers to mitigate the inference bottlenecks associated with self-atte…
Calibrated Selective Classification
Adam Fisch, Tommi Jaakkola, Regina Barzilay
Selective classification allows models to abstain from making predictions (e.g., say "I don't know") when in doubt in order to obtain better effective accuracy. While typical selec…
Conformal Language Modeling
Victor Quach, Adam Fisch, Tal Schuster +4
We propose a novel approach to conformal prediction for generative language models (LMs). Standard conformal prediction produces prediction sets -- in place of single predictions -…