most citedTimeFound: A Foundation Model for Time Series Forecasting

1 citations · 1 across the 8 of their papers we have counts for

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cs.AI2026

OmegaUse-OfficeVal: Benchmarking LLM Agents on Long-Horizon Office-Suite Tasks with Economic Grounding

Jingbo Zhou, Yusai Zhao, Qi Bao +12

Large language model (LLM) agents are increasingly expected to assist users in completing tasks. However, existing benchmarks provide limited support for evaluating whether agents…

cs.AI2026

TS-RAG: Retrieval Augmented Generation for Time Series Forecasting

Yixiong Xiao, Congxi Xiao, Jingbo Zhou

While deep learning models, particularly transformer-based architectures, have shown impressive performance in time series forecasting, the application of retrieval-augmented gener…

cs.AI2026

Temporal Bridges for Spatial Resolution: Enhancing Climate Data Super-Resolution with Bidirectional Alignment

Yichen Zhang, Yixiong Xiao, Congxi Xiao +1

High-resolution climate data is crucial for meteorological predictions and for informing decision support across diverse domains. However, the acquisition of such high-resolution c…

cs.AI2026

ChartAnchor: Chart Grounding with Structural-Semantic Fidelity

Xinhang Li, Jingbo Zhou, Pengfei Luo +2

Recent advances in multimodal large language models (MLLMs) highlight the need for benchmarks that rigorously evaluate structured chart comprehension. Chart grounding refers to the…

cs.AI2026

OmegaUse: Building a General-Purpose GUI Agent for Autonomous Task Execution

Le Zhang, Yixiong Xiao, Xinjiang Lu +12

Graphical User Interface (GUI) agents show great potential for enabling foundation models to complete real-world tasks, revolutionizing human-computer interaction and improving hum…