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- Simon RazniewskiSuggested from co-authorship
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Works15 from public data
- Enabling LLM Knowledge Analysis via Extensive Materialization18
This work proposes a novel methodology to comprehensively materialize an LLM's factual knowledge through recursive querying and result consolidation, for the first time providing constructive insights into the scope and structure of LLM knowledge (or beliefs).
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- Non-rigid point cloud registration for middle ear diagnostics with endoscopic optical coherence tomography10
This work proposes C2P-Net: a two-staged non-rigid registration pipeline for point clouds to support the interpretation of in vivo noisy and partial OCT images for the first time and demonstrates that C2P-Net is generalized to unseen middle ear point clouds and capable of handling realistic noise and incompleteness in synthetic and real OCT data.
- GPTKB v1.5: A Massive Knowledge Base for Exploring Factual LLM Knowledge8
This demonstration introduces GPTKB v1.5, a densely interlinked 100-million-triple knowledge base (KB) built for $14,000 from GPT-4.1, using the GPTKB methodology for massive-recursive LLM knowledge materialization.
- Flash Sculptor: Modular 3D Worlds from Objects5
This paper proposes Flash Sculptor, a simple yet effective framework for compositional 3D scene/object reconstruction from a single image, which decouples compositional scene reconstruction into a sequence of sub-tasks, including handling the appearance, rotation, scale, and translation of each individual instance.
- MMA-ASIA: A Multilingual and Multimodal Alignment Framework for Culturally-Grounded Evaluation3
This work proposes MMA-ASIA, a comprehensive framework to evaluate LLMs' cultural awareness with a focus on Asian contexts, and proposes a five-dimensional evaluation protocol that measures cultural-awareness disparities across countries, cross-lingual consistency, cross-modal consistency, cultural knowledge generalization, and grounding validity.
- Contrastive Disentanglement for Authorship Attribution3
This paper introduces ContrastDistAA, a novel framework that leverages contrastive learning and mutual information maximization to disentangle content and stylistic features in latent representations for AA, and surpasses existing state-of-the-art models in both individual and regional-level AA tasks.
- HateXScore: A Metric Suite for Evaluating Reasoning Quality in Hate Speech Explanations2
A four-component metric suite designed to evaluate the reasoning quality of model explanations that is intended as a diagnostic complement to reveal interpretability failures and annotation inconsistencies that are invisible to standard metrics like Accuracy or F1.
- Automatic ultrasound image alignment for diagnosis of pediatric distal forearm fractures1
An effective and fully automatic pipeline for aligning ultrasound images, showing potential to replace X-rays for diagnosing pediatric distal forearm fractures and leveraging a deep learning model to delineate bone boundaries.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-12. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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