885 citations · 3.8k across the 104 of their papers we have counts for
25 papers · 1 filter
VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data
Thomas Zeng, Shuibai Zhang, Shutong Wu +13
Process Reward Models (PRMs) have proven effective at enhancing mathematical reasoning for Large Language Models (LLMs) by leveraging increased inference-time computation. However,…
Looped Transformers for Length Generalization
Ying Fan, Yilun Du, Kannan Ramchandran +1
Recent work has shown that Transformers trained from scratch can successfully solve various arithmetic and algorithmic tasks, such as adding numbers and computing parity. While the…
Learning to Understand: Identifying Interactions via the Möbius Transform
Justin S. Kang, Yigit E. Erginbas, Landon Butler +2
One of the key challenges in machine learning is to find interpretable representations of learned functions. The Möbius transform is essential for this purpose, as its coefficients…
The Fair Value of Data Under Heterogeneous Privacy Constraints in Federated Learning
Justin Kang, Ramtin Pedarsani, Kannan Ramchandran
Modern data aggregation often involves a platform collecting data from a network of users with various privacy options. Platforms must solve the problem of how to allocate incentiv…
Interactive Learning with Pricing for Optimal and Stable Allocations in Markets
Yigit Efe Erginbas, Soham Phade, Kannan Ramchandran
Large-scale online recommendation systems must facilitate the allocation of a limited number of items among competing users while learning their preferences from user feedback. As…
Interactive Recommendations for Optimal Allocations in Markets with Constraints
Yigit Efe Erginbas, Soham Phade, Kannan Ramchandran
Recommendation systems when employed in markets play a dual role: they assist users in selecting their most desired items from a large pool and they help in allocating a limited nu…