78 citations · 165 across the 14 of their papers we have counts for
19 papers
Convex Dataset Valuation for Post-Training
Siqi Zeng, Christopher Jung, Rui Li +7
Improving LLM performance on downstream tasks sometimes requires leveraging auxiliary datasets during post-training. In practice, however, developers face constraints on compute, l…
Expectation Error Bounds for Transfer Learning in Linear Regression and Linear Neural Networks
Meitong Liu, Christopher Jung, Rui Li +2
In transfer learning, the learner leverages auxiliary data to improve generalization on a main task. However, the precise theoretical understanding of when and how auxiliary data h…
Cross-attention Secretly Performs Orthogonal Alignment in Recommendation Models
Hyunin Lee, Yong Zhang, Hoang Vu Nguyen +8
Cross-domain sequential recommendation (CDSR) aims to align heterogeneous user behavior sequences collected from different domains. While cross-attention is widely used to enhance…
Oracle Efficient Online Multicalibration and Omniprediction
Sumegha Garg, Christopher Jung, Omer Reingold +1
A recent line of work has shown a surprising connection between multicalibration, a multi-group fairness notion, and omniprediction, a learning paradigm that provides simultaneous…
Batch Multivalid Conformal Prediction
Christopher Jung, Georgy Noarov, Ramya Ramalingam +1
We develop fast distribution-free conformal prediction algorithms for obtaining multivalid coverage on exchangeable data in the batch setting. Multivalid coverage guarantees are st…
Multicalibrated Regression for Downstream Fairness
Ira Globus-Harris, Varun Gupta, Christopher Jung +3
We show how to take a regression function that is appropriately ``multicalibrated'' and efficiently post-process it into an approximately error minimizing classifier sati…