483 citations · 510 across the 9 of their papers we have counts for
9 papers
GraphSeek: Next-Generation Graph Analytics with LLMs
Maciej Besta, Łukasz Jarmocik, Orest Hrycyna +7
Graphs are foundational across domains but remain hard to use without deep expertise. LLMs promise accessible natural language (NL) graph analytics, yet they fail to process indust…
Psychologically Enhanced AI Agents
Maciej Besta, Shriram Chandran, Robert Gerstenberger +9
We introduce MBTI-in-Thoughts, a framework for enhancing the effectiveness of Large Language Model (LLM) agents through psychologically grounded personality conditioning. Drawing o…
Affordable AI Assistants with Knowledge Graph of Thoughts
Maciej Besta, Lorenzo Paleari, Jia Hao Andrea Jiang +15
Large Language Models (LLMs) are revolutionizing the development of AI assistants capable of performing diverse tasks across domains. However, current state-of-the-art LLM-driven a…
Reasoning Language Models: A Blueprint
Maciej Besta, Julia Barth, Eric Schreiber +16
Reasoning language models (RLMs), also known as Large Reasoning Models (LRMs), such as OpenAI's o1 and o3, DeepSeek-R1, and Alibaba's QwQ, have redefined AI's problem-solving capab…
Multi-Head RAG: Solving Multi-Aspect Problems with LLMs
Maciej Besta, Ales Kubicek, Robert Gerstenberger +13
Retrieval-Augmented Generation (RAG) improves Large Language Models (LLMs) by retrieving supporting documents into the prompt, but existing methods do not explicitly target queries…
CheckEmbed: Effective Verification of LLM Solutions to Open-Ended Tasks
Maciej Besta, Lorenzo Paleari, Marcin Copik +9
Large Language Models (LLMs) are transforming a wide range of domains, yet verifying their outputs remains a significant challenge, especially for complex open-ended tasks such as…
Demystifying Chains, Trees, and Graphs of Thoughts
Maciej Besta, Florim Memedi, Zhenyu Zhang +13
The field of natural language processing (NLP) has witnessed significant progress in recent years, with a notable focus on improving large language models' (LLM) performance throug…
HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers
Maciej Besta, Afonso Claudino Catarino, Lukas Gianinazzi +4
Many graph representation learning (GRL) problems are dynamic, with millions of edges added or removed per second. A fundamental workload in this setting is dynamic link prediction…
Graph of Thoughts: Solving Elaborate Problems with Large Language Models
Maciej Besta, Nils Blach, Ales Kubicek +8
We introduce Graph of Thoughts (GoT): a framework that advances prompting capabilities in large language models (LLMs) beyond those offered by paradigms such as Chain-of-Thought or…