885 citations · 3.8k across the 104 of their papers we have counts for
115 papers
SAGE: A Realistic Benchmark for Semantic Understanding
Samarth Goel, Reagan J. Lee, Kannan Ramchandran
As large language models (LLMs) achieve strong performance on traditional benchmarks, there is an urgent need for more challenging evaluation frameworks that probe deeper aspects o…
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,…
Quantifying Positional Biases in Text Embedding Models
Reagan J. Lee, Samarth Goel, Kannan Ramchandran
Embedding models are crucial for tasks in Information Retrieval (IR) and semantic similarity measurement, yet their handling of longer texts and associated positional biases remain…
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…
MRI Reconstruction with Side Information using Diffusion Models
Brett Levac, Ajil Jalal, Kannan Ramchandran +1
Magnetic resonance imaging (MRI) exam protocols consist of multiple contrast-weighted images of the same anatomy to emphasize different tissue properties. Due to the long acquisiti…