Publications (8)
Ontology of Belief Diversity: A Community-Based Epistemological Approach
Tyler Fischella, Erin van Liemt, Qiuyi +1
AI applications across classification, fairness, and human interaction often implicitly require ontologies of social concepts. Constructing these well, especially when there are ma…
Leveraging Initial Hints for Free in Stochastic Linear Bandits
Ashok Cutkosky, Chris Dann, Abhimanyu Das +2
We study the setting of optimizing with bandit feedback with additional prior knowledge provided to the learner in the form of an initial hint of the optimal action. We present a n…
Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products
Tamas Sarlos, Xingyou Song, David Woodruff +2
Inspired by fast algorithms in natural language processing, we study low rank approximation in the entrywise transformed setting where we want to find a good rank approximation…
Randomization Boosts KV Caching, Learning Balances Query Load: A Joint Perspective
Fangzhou Wu, Sandeep Silwal, Qiuyi +1
KV caching is a fundamental technique for accelerating Large Language Model (LLM) inference by reusing key-value (KV) pairs from previous queries, but its effectiveness under limit…
Optimized Tradeoffs for Private Prediction with Majority Ensembling
Shuli Jiang, Qiuyi, Zhang +1
We study a classical problem in private prediction, the problem of computing an -differentially private majority of -differentially private algorithms for…
Prompts Generalize with Low Data: Non-vacuous Generalization Bounds for Optimizing Prompts with More Informative Priors
David Madras, Joshua Safyan, Qiuyi +1
Many prompt engineering techniques have been successful in practice, even when optimizing over a large prompt space with with a small amount of task-specific data. Recent work has…