5 papers
VKnowU: Evaluating Visual Knowledge Understanding in Multimodal LLMs
Tianxiang Jiang, Sheng Xia, Yicheng Xu +5
While Multimodal Large Language Models (MLLMs) have become adept at recognizing objects, they often lack the intuitive, human-like understanding of the world's underlying physical…
Creativity or Brute Force? Using Brainteasers as a Window into the Problem-Solving Abilities of Large Language Models
Simeng Han, Howard Dai, Stephen Xia +7
Accuracy remains a standard metric for evaluating AI systems, but it offers limited insight into how models arrive at their solutions. In this work, we introduce a benchmark based…
EasyFS: an Efficient Model-free Feature Selection Framework via Elastic Transformation of Features
Jianming Lv, Sijun Xia, Depin Liang +1
Traditional model-free feature selection methods treat each feature independently while disregarding the interrelationships among features, which leads to relatively poor performan…
Optimal Pricing for Data-Augmented AutoML Marketplaces
Minbiao Han, Jonathan Light, Steven Xia +3
Organizations often lack sufficient data to effectively train machine learning (ML) models, while others possess valuable data that remains underutilized. Data markets promise to u…
TW-CRL: Time-Weighted Contrastive Reward Learning for Efficient Inverse Reinforcement Learning
Yuxuan Li, Yicheng Gao, Ning Yang +1
Episodic tasks in Reinforcement Learning (RL) often pose challenges due to sparse reward signals and high-dimensional state spaces, which hinder efficient learning. Additionally, t…