4 papers
ItinBench: Benchmarking Planning Across Multiple Cognitive Dimensions with Large Language Models
Tianlong Wang, Pinqiao Wang, Weili Shi +1
Large language models (LLMs) with advanced cognitive capabilities are emerging as agents for various reasoning and planning tasks. Traditional evaluations often focus on specific r…
Finding the Cracks: Improving LLMs Reasoning with Paraphrastic Probing and Consistency Verification
Weili Shi, Dongliang Guo, Lehan Yang +3
Large language models have demonstrated impressive performance across a variety of reasoning tasks. However, their problem-solving ability often declines on more complex tasks due…
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation
Kexin Zhang, Shuhan Liu, Song Wang +6
Distribution shifts on graphs -- the discrepancies in data distribution between training and employing a graph machine learning model -- are ubiquitous and often unavoidable in rea…
VRMDiff: Text-Guided Video Referring Matting Generation of Diffusion
Lehan Yang, Jincen Song, Tianlong Wang +4
We propose a new task, video referring matting, which obtains the alpha matte of a specified instance by inputting a referring caption. We treat the dense prediction task of mattin…