Search Results for author:
Found 5 papers, 2 papers with code
Drowning in Documents: Consequences of Scaling Reranker Inference
Rerankers, typically cross-encoders, are often used to re-score the documents retrieved by cheaper initial IR systems.
Efficient Training of Retrieval Models using Negative Cache
These models are typically trained by optimizing the model parameters to score relevant positive" pairs higher than the irrelevantnegative" ones.
On $\infty$-Ground States in the Plane
We study $\infty$-Ground states in convex domains in the plane.
Analysis of PDEs 35K65, 35P30, 35J70
Approximate Probabilistic Inference with Composed Flows
We study the problem of probabilistic inference on the joint distribution defined by a normalizing flow model.
Accelerating Large-Scale Inference with Anisotropic Vector Quantization
Based on the observation that for a given query, the database points that have the largest inner products are more relevant, we develop a family of anisotropic quantization loss functions.
