5 citations · 10 across the 7 of their papers we have counts for
7 papers
Mem-Gallery: Benchmarking Multimodal Long-Term Conversational Memory for MLLM Agents
Yuanchen Bei, Tianxin Wei, Xuying Ning +7
Long-term memory is a critical capability for multimodal large language model (MLLM) agents, particularly in conversational settings where information accumulates and evolves over…
Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting
Zhining Liu, Ze Yang, Xiao Lin +6
Time-series forecasting plays a critical role in many real-world applications. Although increasingly powerful models have been developed and achieved superior results on benchmark…
CLIMB: Class-imbalanced Learning Benchmark on Tabular Data
Zhining Liu, Zihao Li, Ze Yang +6
Class-imbalanced learning (CIL) on tabular data is important in many real-world applications where the minority class holds the critical but rare outcomes. In this paper, we presen…
ClimateBench-M: A Multi-Modal Climate Data Benchmark with a Simple Generative Method
Dongqi Fu, Yada Zhu, Zhining Liu +10
Climate science studies the structure and dynamics of Earth's climate system and seeks to understand how climate changes over time, where the data is usually stored in the format o…
Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal Narrative
Zihao Li, Xiao Lin, Zhining Liu +8
While many advances in time series models focus exclusively on numerical data, research on multimodal time series, particularly those involving contextual textual information, rema…
Transforming the Hybrid Cloud for Emerging AI Workloads
Deming Chen, Alaa Youssef, Ruchi Pendse +42
This white paper, developed through close collaboration between IBM Research and UIUC researchers within the IIDAI Institute, envisions transforming hybrid cloud systems to meet th…
AIM: Attributing, Interpreting, Mitigating Data Unfairness
Zhining Liu, Ruizhong Qiu, Zhichen Zeng +3
Data collected in the real world often encapsulates historical discrimination against disadvantaged groups and individuals. Existing fair machine learning (FairML) research has pre…