14 citations · 51 across the 10 of their papers we have counts for
12 papers
Data Debiasing with Datamodels (D3M): Improving Subgroup Robustness via Data Selection
Saachi Jain, Kimia Hamidieh, Kristian Georgiev +3
Machine learning models can fail on subgroups that are underrepresented during training. While techniques such as dataset balancing can improve performance on underperforming group…
Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation
Joshua Vendrow, Saachi Jain, Logan Engstrom +1
Distribution shift is a major source of failure for machine learning models. However, evaluating model reliability under distribution shift can be challenging, especially since it…
A Data-Based Perspective on Transfer Learning
Saachi Jain, Hadi Salman, Alaa Khaddaj +3
It is commonly believed that in transfer learning including more pre-training data translates into better performance. However, recent evidence suggests that removing data from the…
When does Bias Transfer in Transfer Learning?
Hadi Salman, Saachi Jain, Andrew Ilyas +3
Using transfer learning to adapt a pre-trained "source model" to a downstream "target task" can dramatically increase performance with seemingly no downside. In this work, we demon…
Distilling Model Failures as Directions in Latent Space
Saachi Jain, Hannah Lawrence, Ankur Moitra +1
Existing methods for isolating hard subpopulations and spurious correlations in datasets often require human intervention. This can make these methods labor-intensive and dataset-s…
Missingness Bias in Model Debugging
Saachi Jain, Hadi Salman, Eric Wong +4
Missingness, or the absence of features from an input, is a concept fundamental to many model debugging tools. However, in computer vision, pixels cannot simply be removed from an…
Certified Patch Robustness via Smoothed Vision Transformers
Hadi Salman, Saachi Jain, Eric Wong +1
Certified patch defenses can guarantee robustness of an image classifier to arbitrary changes within a bounded contiguous region. But, currently, this robustness comes at a cost of…
Combining Diverse Feature Priors
Saachi Jain, Dimitris Tsipras, Aleksander Madry
To improve model generalization, model designers often restrict the features that their models use, either implicitly or explicitly. In this work, we explore the design space of le…
A Mechanism for Producing Aligned Latent Spaces with Autoencoders
Saachi Jain, Adityanarayanan Radhakrishnan, Caroline Uhler
Aligned latent spaces, where meaningful semantic shifts in the input space correspond to a translation in the embedding space, play an important role in the success of downstream t…
Spectral Lower Bounds on the I/O Complexity of Computation Graphs
Saachi Jain, Matei Zaharia
We consider the problem of finding lower bounds on the I/O complexity of arbitrary computations in a two level memory hierarchy. Executions of complex computations can be formalize…
Learning to Speak and Act in a Fantasy Text Adventure Game
Jack Urbanek, Angela Fan, Siddharth Karamcheti +7
We introduce a large scale crowdsourced text adventure game as a research platform for studying grounded dialogue. In it, agents can perceive, emote, and act whilst conducting dial…
MASA: Motif-Aware State Assignment in Noisy Time Series Data
Saachi Jain, David Hallac, Rok Sosic +1
Complex systems, such as airplanes, cars, or financial markets, produce multivariate time series data consisting of a large number of system measurements over a period of time. Suc…