Picture for Fereshte Khani

Fereshte Khani

Prompt Engineering a Prompt Engineer

Add code
Nov 09, 2023
Viaarxiv icon

Targeted Data Generation: Finding and Fixing Model Weaknesses

Add code
May 28, 2023
Viaarxiv icon

Collaborative Development of NLP models

Add code
May 24, 2023
Viaarxiv icon

MaskTune: Mitigating Spurious Correlations by Forcing to Explore

Add code
Oct 08, 2022
Figure 1 for MaskTune: Mitigating Spurious Correlations by Forcing to Explore
Figure 2 for MaskTune: Mitigating Spurious Correlations by Forcing to Explore
Figure 3 for MaskTune: Mitigating Spurious Correlations by Forcing to Explore
Figure 4 for MaskTune: Mitigating Spurious Correlations by Forcing to Explore
Viaarxiv icon

Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness

Add code
Jul 04, 2022
Figure 1 for Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness
Figure 2 for Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness
Figure 3 for Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness
Figure 4 for Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness
Viaarxiv icon

On the Opportunities and Risks of Foundation Models

Add code
Aug 18, 2021
Figure 1 for On the Opportunities and Risks of Foundation Models
Figure 2 for On the Opportunities and Risks of Foundation Models
Figure 3 for On the Opportunities and Risks of Foundation Models
Figure 4 for On the Opportunities and Risks of Foundation Models
Viaarxiv icon

In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness

Add code
Dec 16, 2020
Figure 1 for In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
Figure 2 for In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
Figure 3 for In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
Figure 4 for In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
Viaarxiv icon

Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately

Add code
Dec 07, 2020
Figure 1 for Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately
Figure 2 for Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately
Figure 3 for Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately
Figure 4 for Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately
Viaarxiv icon

Noise Induces Loss Discrepancy Across Groups for Linear Regression

Add code
Nov 22, 2019
Figure 1 for Noise Induces Loss Discrepancy Across Groups for Linear Regression
Figure 2 for Noise Induces Loss Discrepancy Across Groups for Linear Regression
Figure 3 for Noise Induces Loss Discrepancy Across Groups for Linear Regression
Figure 4 for Noise Induces Loss Discrepancy Across Groups for Linear Regression
Viaarxiv icon

Maximum Weighted Loss Discrepancy

Add code
Jun 08, 2019
Figure 1 for Maximum Weighted Loss Discrepancy
Figure 2 for Maximum Weighted Loss Discrepancy
Figure 3 for Maximum Weighted Loss Discrepancy
Figure 4 for Maximum Weighted Loss Discrepancy
Viaarxiv icon