Tootfinder

A Knowledge Graph Informing Soil Carbon Modeling
Nasim Shirvani-Mahdavi, Devin Wingfield, Juan Guajardo Gutierrez, Mai Tran, Zhengyuan Zhu, Zeyu Zhang, Haiqi Zhang, Abhishek Divakar Goudar, Chengkai Li, Virginia Jin, Timothy Propst, Dan Roberts, Catherine Stewart, Jianzhong Su, Jennifer Woodward-Greene
https://arxiv.org/abs/2508.10965

A Knowledge Graph Informing Soil Carbon Modeling
Soil organic carbon is crucial for climate change mitigation and agricultural sustainability. However, understanding its dynamics requires integrating complex, heterogeneous data from multiple sources. This paper introduces the Soil Organic Carbon Knowledge Graph (SOCKG), a semantic infrastructure designed to transform agricultural research data into a queryable knowledge representation. SOCKG features a robust ontological model of agricultural experimental data, enabling precise mapping of dat…

JustEva: A Toolkit to Evaluate LLM Fairness in Legal Knowledge Inference
Zongyue Xue, Siyuan Zheng, Shaochun Wang, Yiran Hu, Shenran Wang, Yuxin Yao, Haitao Li, Qingyao Ai, Yiqun Liu, Yun Liu, Weixing Shen
https://arxiv.org/abs/2509.12104

JustEva: A Toolkit to Evaluate LLM Fairness in Legal Knowledge Inference
The integration of Large Language Models (LLMs) into legal practice raises pressing concerns about judicial fairness, particularly due to the nature of their "black-box" processes. This study introduces JustEva, a comprehensive, open-source evaluation toolkit designed to measure LLM fairness in legal tasks. JustEva features several advantages: (1) a structured label system covering 65 extra-legal factors; (2) three core fairness metrics - inconsistency, bias, and imbalanced inaccuracy; (3) robu…

Just out! My new article, 'Reimagining Our Futures: Education and the Promise of Possibility' in Comparative Education Studies is an exercise in hope to collectively, consciously, and critically re-examine education and education systems.
We can harness education's potential of promise by questioning assumptions - which/whose knowledges are legitimised and valued; what has been counted, discounted or marginalised as evidence.

Reimagining Our Futures: Education and the Promise of Possibility    - Comparative Education Studies (CES)
Commentary Reimagining Our Futures: Education and the Promise of Possibility Prachi Srivastava | pp. 86-91 Abstract:The COVID-19 pandemic resulted in the largest global disruption of schooling in recent history, resulting in immediate and cumulative ruptures. This commentary proposes a collective, conscious, and critical re-examination of education and education systems with a view to harnessing the […]

RadarLLM: Adapting Pretrained Large Language Models for Marine Radar Target Detection with Preference-aware Loss
Qiying Hu
https://arxiv.org/abs/2509.12089 https://

RadarLLM: Adapting Pretrained Large Language Models for Marine Radar Target Detection with Preference-aware Loss
Recent advances in pre-trained large language models (LLMs) have demonstrated their capacities to capture universal knowledge, making them promising general-purpose optimization solvers for wireless signal processing. Motivated by these findings, we take the first step towards fine-tuning pre-trained LLMs for the effective analysis of radar signal features in marine target detection tasks. Nevertheless, directly fine-tuning pre-trained LLMs on marine target detection tasks tends to suffer from …

#PreciousPlastic is a global community of people working towards a solution to plastic pollution. Knowledge, tools and techniques are shared online, for free
LET'S BUILD V.5:
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We spent the last 10 years building a network of plastic recyclers around the world. Yet despite progress, only 10% of all plastic ever made has been recycled, the same as when we started

GoldMind: A Teacher-Centered Knowledge Management System for Higher Education -- Lessons from Iterative Design
Gloria Fern\'andez-Nieto, Lele Sha, Yuheng Li, Yi-Shan Tsai, Guanliang Chen, Yinwei Wei, Weiqing Wang, Jinchun Wen, Shaveen Singh, Ivan Silva, Yuanfang Li, Dragan Gas\v{e}vi\'c, Zachari Swiecki
https://arxiv.org/abs/2508.0…

GoldMind: A Teacher-Centered Knowledge Management System for Higher Education -- Lessons from Iterative Design
Designing Knowledge Management Systems (KMSs) for higher education requires addressing complex human-technology interactions, especially where staff turnover and changing roles create ongoing challenges for reusing knowledge. While advances in process mining and Generative AI enable new ways of designing features to support knowledge management, existing KMSs often overlook the realities of educators' workflows, leading to low adoption and limited impact. This paper presents findings from a two…

Geospatial Question Answering on Historical Maps Using Spatio-Temporal Knowledge Graphs and Large Language Models
Ziyi Liu, Sidi Wu, Lorenz Hurni
https://arxiv.org/abs/2508.21491

Geospatial Question Answering on Historical Maps Using Spatio-Temporal Knowledge Graphs and Large Language Models
Recent advances have enabled the extraction of vectorized features from digital historical maps. To fully leverage this information, however, the extracted features must be organized in a structured and meaningful way that supports efficient access and use. One promising approach is question answering (QA), which allows users -- especially those unfamiliar with database query languages -- to retrieve knowledge in a natural and intuitive manner. In this project, we developed a GeoQA system by in…

CRISP: Persistent Concept Unlearning via Sparse Autoencoders
Tomer Ashuach, Dana Arad, Aaron Mueller, Martin Tutek, Yonatan Belinkov
https://arxiv.org/abs/2508.13650 https://

CRISP: Persistent Concept Unlearning via Sparse Autoencoders
As large language models (LLMs) are increasingly deployed in real-world applications, the need to selectively remove unwanted knowledge while preserving model utility has become paramount. Recent work has explored sparse autoencoders (SAEs) to perform precise interventions on monosemantic features. However, most SAE-based methods operate at inference time, which does not create persistent changes in the model's parameters. Such interventions can be bypassed or reversed by malicious actors with …

Lovely to give the keynote 'On Epistemic Humility: storytelling, positionalities, and just survival in/through research', for the Higher Degree Research Forum, University of South Australia.
I draw on post-colonial, Black, and Indigenous scholarship to problematise what we know and how we know.
#HigherEducation

SentiMM: A Multimodal Multi-Agent Framework for Sentiment Analysis in Social Media
Xilai Xu, Zilin Zhao, Chengye Song, Zining Wang, Jinhe Qiang, Jiongrui Yan, Yuhuai Lin
https://arxiv.org/abs/2508.18108

SentiMM: A Multimodal Multi-Agent Framework for Sentiment Analysis in Social Media
With the increasing prevalence of multimodal content on social media, sentiment analysis faces significant challenges in effectively processing heterogeneous data and recognizing multi-label emotions. Existing methods often lack effective cross-modal fusion and external knowledge integration. We propose SentiMM, a novel multi-agent framework designed to systematically address these challenges. SentiMM processes text and visual inputs through specialized agents, fuses multimodal features, enrich…