4 papers
Fine-tuning Small Language Models as Efficient Enterprise Search Relevance Labelers
Yue Kang, Zhuoyi Huang, Benji Schussheim +19
In enterprise search, building high-quality datasets at scale remains a central challenge due to the difficulty of acquiring labeled data. To resolve this challenge, we propose an…
High-Fidelity Synthetic ECG Generation via Mel-Spectrogram Informed Diffusion Training
Zhuoyi Huang, Nutan Sahoo, Anamika Kumari +13
The development of machine learning for cardiac care is severely hampered by privacy restrictions on sharing real patient electrocardiogram (ECG) data. Although generative AI offer…
One Head, Many Models: Cross-Attention Routing for Cost-Aware LLM Selection
Roshini Pulishetty, Mani Kishan Ghantasala, Keerthy Kaushik Dasoju +8
The proliferation of large language models (LLMs) with varying computational costs and performance profiles presents a critical challenge for scalable, cost-effective deployment in…
Auto-Eval Judge: Towards a General Agentic Framework for Task Completion Evaluation
Roshita Bhonsle, Rishav Dutta, Sneha Vavilapalli +8
The increasing adoption of foundation models as agents across diverse domains necessitates a robust evaluation framework. Current methods, such as LLM-as-a-Judge, focus only on fin…