8 citations · 17 across the 8 of their papers we have counts for
8 papers
Set a Thief to Catch a Thief: Combating Label Noise through Noisy Meta Learning
Hanxuan Wang, Na Lu, Xueying Zhao +4
Learning from noisy labels (LNL) aims to train high-performance deep models using noisy datasets. Meta learning based label correction methods have demonstrated remarkable performa…
DOCBENCH: A Benchmark for Evaluating LLM-based Document Reading Systems
Anni Zou, Wenhao Yu, Hongming Zhang +5
Recently, there has been a growing interest among large language model (LLM) developers in LLM-based document reading systems, which enable users to upload their own documents and…
MARVEL: Multidimensional Abstraction and Reasoning through Visual Evaluation and Learning
Yifan Jiang, Jiarui Zhang, Kexuan Sun +5
While multi-modal large language models (MLLMs) have shown significant progress on many popular visual reasoning benchmarks, whether they possess abstract visual reasoning abilitie…
SemEval-2024 Task 9: BRAINTEASER: A Novel Task Defying Common Sense
Yifan Jiang, Filip Ilievski, Kaixin Ma
While vertical thinking relies on logical and commonsense reasoning, lateral thinking requires systems to defy commonsense associations and overwrite them through unconventional th…
BRAINTEASER: Lateral Thinking Puzzles for Large Language Models
Yifan Jiang, Filip Ilievski, Kaixin Ma +1
The success of language models has inspired the NLP community to attend to tasks that require implicit and complex reasoning, relying on human-like commonsense mechanisms. While su…
A Study of Situational Reasoning for Traffic Understanding
Jiarui Zhang, Filip Ilievski, Kaixin Ma +3
Intelligent Traffic Monitoring (ITMo) technologies hold the potential for improving road safety/security and for enabling smart city infrastructure. Understanding traffic situation…