4 papers
Uncertainty-Guided Inference-Time Depth Adaptation for Transformer-Based Visual Tracking
Patrick Poggi, Divake Kumar, Theja Tulabandhula +1
Transformer-based single-object trackers achieve state-of-the-art accuracy but rely on fixed-depth inference, executing the full encoder--decoder stack for every frame regardless o…
CURATRON: Complete and Robust Preference Data for Rigorous Alignment of Large Language Models
Son The Nguyen, Niranjan Uma Naresh, Theja Tulabandhula
This paper addresses the challenges of aligning large language models (LLMs) with human values via preference learning (PL), focusing on incomplete and corrupted data in preference…
MEMETRON: Metaheuristic Mechanisms for Test-time Response Optimization of Large Language Models
Son The Nguyen, Theja Tulabandhula
Large language models (LLMs) are increasingly used for both open-ended and structured tasks, yet their inference-time behavior is still largely dictated by heuristic decoding strat…
Prediction of Lung Metastasis from Hepatocellular Carcinoma using the SEER Database
Jeff J. H. Kim, George R. Nahass, Yang Dai +1
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, with lung metastases being the most common site of distant spread and significantly worsening prognos…