Sadhana Kumaravel

Beyond Backprop: Alternating Minimization with co-Activation Memory.

2018 · arXiv (Cornell University)

Despite significant recent advances in deep neural networks, training them remains a challenge due to the highly non-convex nature of the objective function. State-of-the-art methods rely on error backpropagation, which suffers from several well-known issues, …

Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Embeddings and the Implications to Representation Learning

2020 · arXiv (Cornell University)

Human judgments of word similarity have been a popular method of evaluating the quality of word embedding. But it fails to measure the geometry properties such as asymmetry. For example, it is more natural to …

NESTFUL: A Benchmark for Evaluating LLMs on Nested Sequences of API Calls

2024 · arXiv (Cornell University)

The resurgence of autonomous agents built using large language models (LLMs) to solve complex real-world tasks has brought increased focus on LLMs' fundamental ability of tool or function calling. At the core of these agents, …