Tong Xu
10 papers in the PaperMetrix corpus
Papers by this author
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Out-of-Town Recommendation with Travel Intention Modeling
2021 · Proceedings of the AAAI Conference on Artificial Intelligence
Out-of-town recommendation is designed for those users who leave their home-town areas and visit the areas they have never been to before. It is challenging to recommend Point-of-Interests (POIs) for out-of-town users since the out-of-town …
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Ontological Concept Structure Aware Knowledge Transfer for Inductive Knowledge Graph Embedding
2021
Conventional knowledge graph embedding methods mainly assume that all entities at reasoning stage are available in the original training graph. But in real-world application scenarios, newly emerged entities are always inevitable, which results in the …
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CBR: Context Bias aware Recommendation for Debiasing User Modeling and Click Prediction
2022 · Proceedings of the ACM Web Conference 2022
With the prosperity of recommender systems, the biases existing in user behaviors, which may lead to inconsistency between user preference and behavior records, have attracted wide attention. Though large efforts have been made to infer …
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Regularizing End-to-End Speech Translation with Triangular Decomposition Agreement
2021 · arXiv (Cornell University)
End-to-end speech-to-text translation (E2E-ST) is becoming increasingly popular due to the potential of its less error propagation, lower latency, and fewer parameters. Given the triplet training corpus $\langle speech, transcription, translation\rangle$, the conventional high-quality E2E-ST …
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Collaboration-Aware Hybrid Learning for Knowledge Development Prediction
2024
In recent years, the rise of online Knowledge Management Systems (KMSs) has significantly improved work efficiency in enterprises. Knowledge development prediction, as a critical application within these online platforms, enables organizations to proactively address knowledge …
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A Multi-scale Feature Learning Network with Optical Flow Correction for Micro- and Macro-expression Spotting
2024
Recently, automatic micro-expression (ME) analysis has attracted increasing attention, since ME is a spontaneous facial expression that can truly reflect the emotional state an individual tries to conceal. As a crucial step in ME analysis, …
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Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
2025
In the quest for artificial general intelligence, Multi-modal Large Language Models (MLLMs) have emerged as a focal point in recent advancements. However, the predominant focus remains on developing their capabilities in static image understanding. The …
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Disentangled Graph Collaborative Filtering
2020
Learning informative representations of users and items from the interaction data is of crucial importance to collaborative filtering (CF). Present embedding functions exploit user-item relationships to enrich the representations, evolving from a single user-item instance …
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Large language models for generative information extraction: a survey
2024 · Frontiers of Computer Science
Abstract Information Extraction (IE) aims to extract structural knowledge from plain natural language texts. Recently, generative Large Language Models (LLMs) have demonstrated remarkable capabilities in text understanding and generation. As a result, numerous works have …
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A survey on multimodal large language models
2024 · National Science Review
Recently, the multimodal large language model (MLLM) represented by GPT-4V has been a new rising research hotspot, which uses powerful large language models (LLMs) as a brain to perform multimodal tasks. The surprising emergent capabilities …