works on

From the 1 of 17 linked papers with an AI index.

collaborators

17 papers

cs.NI2026

EvalNet: A Practical Toolchain for Generation and Analysis of Extreme-Scale Interconnects

Maciej Besta, Patrick Iff, Marcel Schneider +10

EvalNet is a practical toolchain that generates and analyzes a wide range of extreme‑scale network topologies, providing detailed metrics on shortest and non‑shortest path diversit…

cs.DB2026

Benchmarking Filtered Approximate Nearest Neighbor Search Algorithms on Transformer-based Embedding Vectors

Patrick Iff, Paul Bruegger, Marcin Chrapek +3

Advances in embedding models for text, image, audio, and video drive progress across multiple domains, including retrieval-augmented generation, recommendation systems, and others.…

cs.CL2026

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…

cs.AR2026

Network Design for Wafer-Scale Systems with Wafer-on-Wafer Hybrid Bonding

Patrick Iff, Tommaso Bonato, Maciej Besta +2

Transformer-based large language models are increasingly constrained by data movement as communication bandwidth drops sharply beyond the chip boundary. Wafer-scale integration usi…

cs.DB2026

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…

cs.CL2026

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…