Tootfinder

An LLM Agent-Based Complex Semantic Table Annotation Approach
Yilin Geng, Shujing Wang, Chuan Wang, Keqing He, Yanfei Lv, Ying Wang, Zaiwen Feng, Xiaoying Bai
https://arxiv.org/abs/2508.12868

An LLM Agent-Based Complex Semantic Table Annotation Approach
The Semantic Table Annotation (STA) task, which includes Column Type Annotation (CTA) and Cell Entity Annotation (CEA), maps table contents to ontology entities and plays important roles in various semantic applications. However, complex tables often pose challenges such as semantic loss of column names or cell values, strict ontological hierarchy requirements, homonyms, spelling errors, and abbreviations, which hinder annotation accuracy. To address these issues, this paper proposes an LLM-bas…

Semantic Item Graph Enhancement for Multimodal Recommendation
Xiaoxiong Zhang, Xin Zhou, Zhiwei Zeng, Dusit Niyato, Zhiqi Shen
https://arxiv.org/abs/2508.06154 https://

Semantic Item Graph Enhancement for Multimodal Recommendation
Multimodal recommendation systems have attracted increasing attention for their improved performance by leveraging items' multimodal information. Prior methods often build modality-specific item-item semantic graphs from raw modality features and use them as supplementary structures alongside the user-item interaction graph to enhance user preference learning. However, these semantic graphs suffer from semantic deficiencies, including (1) insufficient modeling of collaborative signals among ite…

LLM-empowered Dynamic Prompt Routing for Vision-Language Models Tuning under Long-Tailed Distributions
Yongju Jia, Jiarui Ma, Xiangxian Li, Baiqiao Zhang, Xianhui Cao, Juan Liu, Yulong Bian
https://arxiv.org/abs/2508.15688

LLM-empowered Dynamic Prompt Routing for Vision-Language Models Tuning under Long-Tailed Distributions
Pre-trained vision-language models (VLMs), such as CLIP, have demonstrated impressive capability in visual tasks, but their fine-tuning often suffers from bias in class-imbalanced scene. Recent works have introduced large language models (LLMs) to enhance VLM fine-tuning with supplementing semantic information. However, they often overlook inherent class imbalance in VLMs' pre-training, which may lead to bias accumulation in downstream tasks. To address this problem, this paper proposes a Multi…

Notes on Cohomological Finite Generation for Finite Group Schemes
Juan Omar Gom\'ez, Chris J. Parker
https://arxiv.org/abs/2510.02908 https://arxiv.org…

Notes on Cohomological Finite Generation for Finite Group Schemes
These are extended notes based on lectures given by Vincent Franjou, Paul Sobaje, Peter Symonds and Antoine Touzé at the Master Class on New Developments in Finite Generation of Cohomology that took place at Bielefeld University in September 2023. Their aim to give a panoramic overview of van der Kallen's recent result on the finite generation of cohomology for finite group schemes over an arbitrary Noetherian base, bringing together the many papers that this theorem relies on, and supplying t…