3 papers
cs.CL2026
METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models
Pengfeng Li, Chen Huang, Chaoqun Hao +4
Contextual causal reasoning is a critical yet challenging capability for Large Language Models (LLMs). Existing benchmarks, however, often evaluate this skill in fragmented setting…
cs.CV2025
MARS2 2025 Challenge on Multimodal Reasoning: Datasets, Methods, Results, Discussion, and Outlook
Peng Xu, Shengwu Xiong, Jiajun Zhang +125
This paper reviews the MARS2 2025 Challenge on Multimodal Reasoning. We aim to bring together different approaches in multimodal machine learning and LLMs via a large benchmark. We…
cs.LG2025
Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated Learning
Hongyao Chen, Tianyang Xu, Xiaojun Wu +1
Batch Normalisation (BN) is widely used in conventional deep neural network training to harmonise the input-output distributions for each batch of data. However, federated learning…