10 papers
Skip-It? Theoretical Conditions for Layer Skipping in Vision-Language Models
Max Hartman, Vidhata Jayaraman, Moulik Choraria +2
Vision-language models achieve incredible performance across a wide range of tasks, but their large size makes inference costly. Recent work has shown that multimodal processing co…
Energy-Aware Routing to Large Reasoning Models
Austin R. Ellis-Mohr, Max Hartman, Lav R. Varshney
Large reasoning models (LRMs) have heterogeneous inference energy costs based on which model is used and how much it reasons. To reduce energy, it is important to choose the right…
Federated Nonlinear System Identification
Omkar Tupe, Max Hartman, Lav R. Varshney +1
We consider federated learning of linearly-parameterized nonlinear systems. We establish theoretical guarantees on the effectiveness of federated nonlinear system identification co…
Computing with Living Neurons: Chaos-Controlled Reservoir Computing with Knowledge Transplant
Seung Hyun Kim, Zhi Dou, Gaurav Upadhyay +6
We introduce chaos-controlled Reservoir Computing (cc-RC) for living neural cultures: dynamically rich substrates of unique potential for adaptive computation. To account for intri…
Verifier Threshold: An Efficient Test-Time Scaling Approach for Image Generation
Vignesh Sundaresha, Akash Haridas, Vikram Appia +1
Image generation has emerged as a mainstream application of large generative models. Just as test-time compute and reasoning have improved language model capabilities, similar bene…
Watermarking Discrete Diffusion Language Models
Avi Bagchi, Akhil Bhimaraju, Moulik Choraria +2
Watermarking has emerged as a promising technique to track AI-generated content and differentiate it from authentic human creations. While prior work extensively studies watermarki…