1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.CL2025
Divide, Cache, Conquer: Dichotomic Prompting for Efficient Multi-Label LLM-Based Classification
Mikołaj Langner, Jan Eliasz, Ewa Rudnicka +1
We introduce a method for efficient multi-label text classification with large language models (LLMs), built on reformulating classification tasks as sequences of dichotomic (yes/n…
cs.AI2025★ 1 cited
AggTruth: Contextual Hallucination Detection using Aggregated Attention Scores in LLMs
Piotr Matys, Jan Eliasz, Konrad Kiełczyński +4
In real-world applications, Large Language Models (LLMs) often hallucinate, even in Retrieval-Augmented Generation (RAG) settings, which poses a significant challenge to their depl…