9 papers
Learning the Context of Errors: Black-Box Online Adaptation of Time Series Foundation Models
Xilin Dai, Yiding Liu, Hongjie Xia +4
The rapid evolution of Time Series Foundation Models (TSFMs) has advanced zero-shot forecasting across diverse domains. Inspired by the current form of Large Language Models, futur…
MMSearch-R1: Incentivizing LMMs to Search
Jinming Wu, Zihao Deng, Wei Li +5
Robust deployment of large multimodal models (LMMs) in real-world scenarios requires access to external knowledge sources, given the complexity and dynamic nature of real-world inf…
Proactive Guidance of Multi-Turn Conversation in Industrial Search
Xiaoyu Li, Xiao Li, Li Gao +5
The evolution of Large Language Models (LLMs) has significantly advanced multi-turn conversation systems, emphasizing the need for proactive guidance to enhance users' interactions…
Variational Graph Autoencoder for Heterogeneous Information Networks with Missing and Inaccurate Attributes
Yige Zhao, Jianxiang Yu, Yao Cheng +4
Heterogeneous Information Networks (HINs), which consist of various types of nodes and edges, have recently demonstrated excellent performance in graph mining. However, most existi…
G3: An Effective and Adaptive Framework for Worldwide Geolocalization Using Large Multi-Modality Models
Pengyue Jia, Yiding Liu, Xiaopeng Li +7
Worldwide geolocalization aims to locate the precise location at the coordinate level of photos taken anywhere on the Earth. It is very challenging due to 1) the difficulty of capt…
MAIR: A Massive Benchmark for Evaluating Instructed Retrieval
Weiwei Sun, Zhengliang Shi, Jiulong Wu +6
Recent information retrieval (IR) models are pre-trained and instruction-tuned on massive datasets and tasks, enabling them to perform well on a wide range of tasks and potentially…