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EIR: Enhanced Image Representations for Medical Report Generation
Qiang Sun, Zongcheng Ji, Yinlong Xiao +2
Generating medical reports from chest X-ray images is a critical and time-consuming task for radiologists, especially in emergencies. To alleviate the stress on radiologists and re…
Reward Auditor: Inference on Reward Modeling Suitability in Real-World Perturbed Scenarios
Jianxiang Zang, Yongda Wei, Ruxue Bai +5
Reliable reward models (RMs) are critical for ensuring the safe alignment of large language models (LLMs). However, current RM evaluation methods focus solely on preference percept…
PCA++: How Uniformity Induces Robustness to Background Noise in Contrastive Learning
Mingqi Wu, Qiang Sun, Yi Yang
High-dimensional data often contain low-dimensional signals obscured by structured background noise, which limits the effectiveness of standard PCA. Motivated by contrastive learni…
C3-OWD: A Curriculum Cross-modal Contrastive Learning Framework for Open-World Detection
Siheng Wang, Zhengdao Li, Yanshu Li +12
Object detection has advanced significantly in the closed-set setting, but real-world deployment remains limited by two challenges: poor generalization to unseen categories and ins…
Optimization-Induced Dynamics of Lipschitz Continuity in Neural Networks
Róisín Luo, James McDermott, Christian Gagné +2
Lipschitz continuity characterizes the worst-case sensitivity of neural networks to small input perturbations; yet its dynamics (i.e. temporal evolution) during training remains un…
Generative Market Equilibrium Models with Stable Adversarial Learning via Reinforcement
Anastasis Kratsios, Xiaofei Shi, Qiang Sun +1
We present a general computational framework for solving continuous-time financial market equilibria under minimal modeling assumptions while incorporating realistic financial fric…