arXiv AI
Jun 10
A Survey on Semantic Modeling for Building Energy Management
arXiv:2404. 11716v2 Announce Type: replace Abstract: Building Energy Management (BEM) is central to reducing energy use and CO2 emissions in the building sector.
Brick-DICL: Dynamic In-Context Learning for Automated Brick Schema Classification
arXiv:2606. 17637v1 Announce Type: new Abstract: Building Management Systems (BMS) are essential for optimizing energy efficiency and operational performance in modern buildings.
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arXiv AI
Jun 19
BIM-Edit: Benchmarking Large Language Models for IFC-Based Building Information Modeling
arXiv:2606. 20146v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly applied to computer-aided design (CAD) to generate design artifacts from textual instructions.
arXiv Machine Learning
Aug 6
BIM-Native Tokenization for Constraint-Aware Room Layout Synthesis
arXiv:2512. 04832v3 Announce Type: replace-cross Abstract: We present a BIM-native tokenization for room-level layout synthesis in Building Information Modeling (BIM) scenes.
arXiv AI
Jul 28
Evo-DKD: Dual-Knowledge Decoding for Autonomous Ontology Evolution in Large Language Models
arXiv:2507. 21438v2 Announce Type: replace Abstract: Ontologies and knowledge graphs require continuous evolution to remain comprehensive and accurate, but manual curation is labor intensive.
Hugging Face Trending Papers
Jun 10
Automating Geometry-Intensive Compliance Checking in BIM: Graph-Based Semantic Reasoning Framework
Automating compliance check for geometry-intensive regulations remains a significant technical bottleneck in Building Information Modeling (BIM), primarily due to the semantic disparity between high-level regulatory logic and structured IFC data. Existing methods, often reliant on static rule templates, struggle to traverse multi-hop reasoning chains or resolve latent spatial dependencies across multiple building entities.
arXiv AI
Jun 2
MiCU: End-to-End Smart Home Command Understanding with Large Language Model
arXiv:2606. 01099v1 Announce Type: cross Abstract: Command understanding systems in smart home ecosystems can automate device control and substantially improve user experience.
arXiv AI
Jun 16
LLMs on Tabular Data with Limited Semantics: Evidence from Industrial Car Retrofit Prediction
arXiv:2606. 15314v1 Announce Type: cross Abstract: Industrial retrofit planning depends on structured operational data rather than free text: planners must estimate whether a newly registered prototype will require a retrofit, which retrofit package it will need, and how long the work will take.
arXiv AI
Jul 17
SAGA: Schema-Aware Grounding for Agentic Text-to-SPARQL Generation
arXiv:2607. 14494v1 Announce Type: new Abstract: Complex knowledge base question answering (KBQA) is commonly approached through either information retrieval over a question-specific subgraph or semantic parsing into an executable logical form.
arXiv AI
Jul 28
TRACE: Business Rule-Grounded Reasoning Curriculum for Knowledge-Preserving Parametric Tool Retrieval in Enterprise LLMs
arXiv:2607. 22639v1 Announce Type: new Abstract: Parametric retrieval enables LLMs to retrieve tools implicitly by assigning each API a unique virtual token and training the model to generate it via constrained beam search.
arXiv Machine Learning
Jul 16
Algorithmic Recourse of In-Context Learning for Tabular Data
arXiv:2605. 31272v2 Announce Type: replace Abstract: As predictive models are increasingly deployed in high-stakes settings such as credit approval, there is a growing need for post-hoc methods that provide recourse to affected individuals.
arXiv AI
Jul 21
Bridging the Information Gap: Semantic Densification and Hindsight Distillation for Cold-Start Prediction
arXiv:2607. 17070v1 Announce Type: new Abstract: New-user cold-start is a critical bottleneck for e-commerce platforms: predicting user lifetime value (LTV) and conversion rate (CVR) for users with sparse interaction history.
arXiv AI
Jun 6
Brick-Composer: Using MLLMs for Assembly with Diverse Bricks
arXiv:2606. 05445v1 Announce Type: new Abstract: We dream of AI agents that can read arbitrary designs and construct real-world objects from reusable building blocks.