AI for Research and Scalable, Efficient Systems
Springer Nature Switzerland AG (Verlag)
978-981-96-8911-8 (ISBN)
AI4Research 2025 presented 8 full papers from 35 submissions. The papers covered diverse areas such as agent debate evaluation, taxonomy expansion, hypothesis generation, AI4Research benchmarks, caption generation, drug discovery, and financial auditing.
SEAS 2025 accepted 7 full papers from 17 submissions. These papers explore the efficiency and scalability of AI models.
.- AI4Research 2025.
.- ResearchCodeAgent: An LLM Multi-Agent System for Automated Codification of Research Methodologies.
.- LLMs Tackle Meta-Analysis: Automating Scientific Hypothesis Generation with Statistical Rigor.
.- AuditBench: A Benchmark for Large Language Models in Financial Statement Auditing.
.- Clustering Time Series Data with Gaussian Mixture Embeddings in a Graph Autoencoder Framework.
.- Empowering AI as Autonomous Researchers: Evaluating LLMs in Generating Novel Research Ideas through Automated Metrics.
.- Multi-LLM Collaborative Caption Generation in Scientific Documents.
.- CypEGAT: A Deep Learning Framework Integrating Protein Language Model and Graph Attention Networks for Enhanced CYP450s Substrate Prediction.
.- Understanding How Paper Writers Use AI-Generated Captions in Figure Caption Writing.
.- SEAS 2025.
.- ssProp: Energy-Efficient Training for Convolutional Neural Networks with Scheduled Sparse Back Propagation.
.- Knowledge Distillation with Training Wheels.
.- PickLLM: Context-Aware RL-Assisted Large Language Model Routing.
.- ZNorm: Z-Score Gradient Normalization Accelerating Skip-Connected Network Training without Architectural Modification.
.- The Impact of Multilingual Model Scaling on Seen and Unseen Language Performance.
.- Information Consistent Pruning: How to Efficiently Search for Sparse Networks?.
.- Efficient Image Similarity Search with Quadtrees.
| Erscheinungsdatum | 01.07.2025 |
|---|---|
| Reihe/Serie | Communications in Computer and Information Science |
| Zusatzinfo | 49 Illustrations, color; 4 Illustrations, black and white |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Schlagworte | AI4Science • AI-assisted scientific research lifecycle • ai systems • Autonomous Scientist • Computational resources • Deep learning • Efficiency • human-in-the-loop • Large language model • Large-Scale AI • machine learning • Optimization • Scalability • Scientific Discovery • Scientific Writing |
| ISBN-10 | 981-96-8911-2 / 9819689112 |
| ISBN-13 | 978-981-96-8911-8 / 9789819689118 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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