From the 6 of 186 papers with an AI index.
26 citations
- The Ohio State UniversityUS73 papers
- FZU ‒ Institute of Physics of the Academy of Sciences of the Czech RepublicCZ71 papers
- Heidelberg UniversityDE69 papers
- Jagiellonian UniversityPL68 papers
- Lawrence Berkeley National LaboratoryUS68 papers
- University of Science and Technology of ChinaCN68 papers
- Yale UniversityUS68 papers
- AGH University of KrakowPL66 papers
- University of TsukubaJP66 papers
- The University of Texas at AustinUS65 papers
- Comenius University BratislavaSK61 papers
- European Organization for Nuclear ResearchCH61 papers
6 papers · 1 filter
Reasoning-Grounded Natural Language Explanations for Language Models
Vojtech Cahlik, Rodrigo Alves, Pavel Kordik
We propose a large language model explainability technique for obtaining faithful natural language explanations by grounding the explanations in a reasoning process. When converted…
Geometric Reasoning in the Embedding Space
Jan Hůla, David MojžÃÅ¡ek, JiÅà JaneÄek +2
In this contribution, we demonstrate that Graph Neural Networks and Transformers can learn to reason about geometric constraints. We train them to predict spatial position of point…
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han +1144
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…
Reflecting in the Reflection: Integrating a Socratic Questioning Framework into Automated AI-Based Question Generation
OndÅej Holub, Essi Ryymin, Rodrigo Alves
Designing good reflection questions is pedagogically important but time-consuming and unevenly supported across teachers. This paper introduces a reflection-in-reflection framework…
Universal Embedding Function for Traffic Classification via QUIC Domain Recognition Pretraining: A Transfer Learning Success
Jan Luxemburk, Karel Hynek, Richard Plný +1
Encrypted traffic classification (TC) methods must adapt to new protocols and extensions as well as to advancements in other machine learning fields. In this paper, we adopt a tran…
REDELEX: A Framework for Relational Deep Learning Exploration
Jakub PeleÅ¡ka, Gustav Å Ãr
Relational databases (RDBs) are widely regarded as the gold standard for storing structured information. Consequently, predictive tasks leveraging this data format hold significant…