92 citations · 123 across the 5 of their papers we have counts for
12 papers
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…
Efficiently Controlling Multiple Risks with Pareto Testing
Bracha Laufer-Goldshtein, Adam Fisch, Regina Barzilay +1
Machine learning applications frequently come with multiple diverse objectives and constraints that can change over time. Accordingly, trained models can be tuned with sets of hype…
Conformal Prediction Sets with Limited False Positives
Adam Fisch, Tal Schuster, Tommi Jaakkola +1
We develop a new approach to multi-label conformal prediction in which we aim to output a precise set of promising prediction candidates with a bounded number of incorrect answers.…
Consistent Accelerated Inference via Confident Adaptive Transformers
Tal Schuster, Adam Fisch, Tommi Jaakkola +1
We develop a novel approach for confidently accelerating inference in the large and expensive multilayer Transformers that are now ubiquitous in natural language processing (NLP).…
Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence
Tal Schuster, Adam Fisch, Regina Barzilay
Typical fact verification models use retrieved written evidence to verify claims. Evidence sources, however, often change over time as more information is gathered and revised. In…
Few-shot Conformal Prediction with Auxiliary Tasks
Adam Fisch, Tal Schuster, Tommi Jaakkola +1
We develop a novel approach to conformal prediction when the target task has limited data available for training. Conformal prediction identifies a small set of promising output ca…