Zobrazeno 1 - 10
of 1 523
pro vyhledávání: '"Zhang, Weijia"'
Spatio-temporal forecasting is a critical component of various smart city applications, such as transportation optimization, energy management, and socio-economic analysis. Recently, several automated spatio-temporal forecasting methods have been pro
Externí odkaz:
http://arxiv.org/abs/2409.16586
Few-shot point cloud 3D object detection (FS3D) aims to identify and localise objects of novel classes from point clouds, using knowledge learnt from annotated base classes and novel classes with very few annotations. Thus far, this challenging task
Externí odkaz:
http://arxiv.org/abs/2408.17036
Multi-instance partial-label learning (MIPL) addresses scenarios where each training sample is represented as a multi-instance bag associated with a candidate label set containing one true label and several false positives. Existing MIPL algorithms h
Externí odkaz:
http://arxiv.org/abs/2408.14369
Autor:
Zhang, Weijia, Aliannejadi, Mohammad, Pei, Jiahuan, Yuan, Yifei, Huang, Jia-Hong, Kanoulas, Evangelos
Large language models (LLMs) often generate content with unsupported or unverifiable content, known as "hallucinations." To address this, retrieval-augmented LLMs are employed to include citations in their content, grounding the content in verifiable
Externí odkaz:
http://arxiv.org/abs/2408.12398
Autor:
Zhang, Weijia, Huang, Jia-Hong, Vakulenko, Svitlana, Xu, Yumo, Rajapakse, Thilina, Kanoulas, Evangelos
Query-focused summarization (QFS) is a fundamental task in natural language processing with broad applications, including search engines and report generation. However, traditional approaches assume the availability of relevant documents, which may n
Externí odkaz:
http://arxiv.org/abs/2408.10357
Although attention-based multi-instance learning algorithms have achieved impressive performances on slide-level whole slide image (WSI) classification tasks, they are prone to mistakenly focus on irrelevant patterns such as staining conditions and t
Externí odkaz:
http://arxiv.org/abs/2408.09449
Pre-trained Language Models (PLMs), such as ChatGPT, have significantly advanced the field of natural language processing. This progress has inspired a series of innovative studies that explore the adaptation of PLMs to time series analysis, intendin
Externí odkaz:
http://arxiv.org/abs/2408.08328
Autor:
Zhang, Weijia, Aliannejadi, Mohammad, Yuan, Yifei, Pei, Jiahuan, Huang, Jia-Hong, Kanoulas, Evangelos
Large language models (LLMs) often produce unsupported or unverifiable content, known as "hallucinations." To mitigate this, retrieval-augmented LLMs incorporate citations, grounding the content in verifiable sources. Despite such developments, manua
Externí odkaz:
http://arxiv.org/abs/2406.15264
Autor:
Dai, Gordon, Zhang, Weijia, Li, Jinhan, Yang, Siqi, lbe, Chidera Onochie, Rao, Srihas, Caetano, Arthur, Sra, Misha
The emergence of Large Language Models (LLMs) and advancements in Artificial Intelligence (AI) offer an opportunity for computational social science research at scale. Building upon prior explorations of LLM agent design, our work introduces a simula
Externí odkaz:
http://arxiv.org/abs/2406.14373
Autor:
Li, Wenyan, Zhang, Xinyu, Li, Jiaang, Peng, Qiwei, Tang, Raphael, Zhou, Li, Zhang, Weijia, Hu, Guimin, Yuan, Yifei, Søgaard, Anders, Hershcovich, Daniel, Elliott, Desmond
Food is a rich and varied dimension of cultural heritage, crucial to both individuals and social groups. To bridge the gap in the literature on the often-overlooked regional diversity in this domain, we introduce FoodieQA, a manually curated, fine-gr
Externí odkaz:
http://arxiv.org/abs/2406.11030