16.2k citations · 26.2k across the 16 of their papers we have counts for
16 papers
Studying Large Language Model Generalization with Influence Functions
Roger Grosse, Juhan Bae, Cem Anil +14
When trying to gain better visibility into a machine learning model in order to understand and mitigate the associated risks, a potentially valuable source of evidence is: which tr…
Measuring Faithfulness in Chain-of-Thought Reasoning
Tamera Lanham, Anna Chen, Ansh Radhakrishnan +27
Large language models (LLMs) perform better when they produce step-by-step, "Chain-of-Thought" (CoT) reasoning before answering a question, but it is unclear if the stated reasonin…
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning
Taoan Huang, Aaron Ferber, Yuandong Tian +2
Integer Linear Programs (ILPs) are powerful tools for modeling and solving a large number of combinatorial optimization problems. Recently, it has been shown that Large Neighborhoo…
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction
Youwei Liang, Kevin Stone, Ali Shameli +8
Finding the optimal pass sequence of compilation can lead to a significant reduction in program size and/or improvement in program efficiency. Prior works on compilation pass order…
Local Branching Relaxation Heuristics for Integer Linear Programs
Taoan Huang, Aaron Ferber, Yuandong Tian +2
Large Neighborhood Search (LNS) is a popular heuristic algorithm for solving combinatorial optimization problems (COP). It starts with an initial solution to the problem and iterat…
OLLA: Optimizing the Lifetime and Location of Arrays to Reduce the Memory Usage of Neural Networks
Benoit Steiner, Mostafa Elhoushi, Jacob Kahn +1
The size of deep neural networks has grown exponentially in recent years. Unfortunately, hardware devices have not kept pace with the rapidly increasing memory requirements. To cop…