AI
Neural-Symbolic Reasoning over Knowledge Graphs: A Survey from a Query Perspective
The paper surveys neural-symbolic reasoning over knowledge graphs from a query perspective. It revie...
AI
Practical Principles for AI Cost and Compute Accounting
Policymakers are using development cost and compute as indicators of AI capabilities and risks. Howe...
AI
Benchmarking Retrieval-Augmented Generation Strategies for Large Language Model-Based Travel Mode Choice Prediction
Researchers have developed a framework for using Large Language Models (LLMs) to predict travel mode...
AI
Beyond Benchmarks: LLM Evaluation with an Anthropomorphic and Lifecycle-oriented Roadmap
Researchers have proposed a new framework for evaluating large language models (LLMs). The framework...
AI
Beyond Benchmarking: Scenario-Based Evaluation of Large Language Models for Personalized Learning
Researchers have proposed a new framework for evaluating large language models' ...
AI
MACD: Multi-Agent Clinical Diagnosis with Self-Learned Knowledge for LLM
Researchers have developed a framework called MACD for large language models (LL...
AI
AdaR: A Framework for Equipping LLMs with Adaptive Reasoning
Researchers have proposed the AdaR framework to improve the reasoning capabiliti...
AI
Training Proactive and Personalized LLM Agents
Researchers propose a new paradigm for training language models (LLMs) to be pro...