A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Narges Ahmadi, Yubo Jiao, Jônatas Augusto Manzolli, et al.
This paper proposes a three-agent workflow integrating conversational data collection, structured processing, and LLM-based prediction for travel behavior, achieving 71.5% accuracy with vision-based LLMs.
Zeyu Ren, Ling Yue, Ran Li, et al.
FlowEvo is a training-free framework where workflows and executable skills co-evolve at inference time, improving agent performance across benchmarks while reducing token usage.
Neura Market
81% of n8n workflow templates that call an external system declare no error handling at all — no retry, no timeout, no error branch. A structural analysis of 5,147 deduplicated automation templates, read from their own executable specifications.
Neura Market
AI went from 0% to 58% of new n8n automation templates in five years, only 1.2% of templates pause for a human, and the top 10% capture over three-quarters of all recorded adoption — from 26,822 workflow specifications across n8n and Make.
Ling Yue, K. Bhandari, Ching-Yun Ko, et al.
This survey reviews methods for designing and optimizing LLM agent workflows, treating them as agentic computation graphs and organizing literature by when workflow structure is determined.
Unknown
This paper proposes an automated workflow for discovering circuits in neural networks, aiming to reduce manual effort in mechanistic interpretability.
Sajjad Khan
This paper introduces the RESUME CONTRACT, a machine-checked conformance contract for checkpoint, interrupt, and resume semantics in workflow persistence layers, and evaluates five agent frameworks against it.
Shanghua Gao, Ada Fang, Yepeng Huang, et al.
This paper introduces AI agents that decompose complex biomedical problems into subtasks, accelerating discovery workflows and improving resource efficiency.
Unknown
This paper analyzes the security of large language model-based AI agents by studying their workflows and identifying vulnerabilities.
M. Ferrag, N. Tihanyi, Djallel Hamouda, et al.
A unified threat model for LLM-agent ecosystems covering host-to-tool and agent-to-agent attacks, with over 30 techniques and mitigation strategies.
Andrei Paleyes, Raoul-Gabriel Urma, Neil D. Lawrence
A survey of case studies on deploying machine learning, mapping challenges to workflow stages to set a research agenda.
Zongxi Li, Zijian Wang, Weiming Wang, et al.
A systematic survey of Retrieval-Augmented Generation (RAG) in education, covering workflow, retrievers, generation optimization, and applications.