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cs.AI2026
Query Symbolically or Retrieve Semantically? A Dataset and Method for Semi-Structured Question Answering
Mateusz Czyżnikiewicz, Ryszard Tuora, Adam Kozakiewicz +6
Retrieval-Augmented Generation (RAG) systems for question answering typically retrieve evidence by semantic similarity between the query and document chunks. While effective for un…
cs.IR2026
UnWeaving the knots of GraphRAG -- turns out VectorRAG is almost enough
Ryszard Tuora, Mateusz Galiński, Michał Godziszewski +4
One of the key problems in Retrieval-augmented generation (RAG) systems is that chunk-based retrieval pipelines represent the source chunks as atomic objects, mixing the informatio…
cs.SD2026
A Benchmark for Audio Reasoning Capabilities of Multimodal Large Language Models
Iwona Christop, Mateusz Czyżnikiewicz, Paweł Skórzewski +4
The present benchmarks for testing the audio modality of multimodal large language models concentrate on testing various audio tasks such as speaker diarization or gender identific…