activity
20232026
collaborators

7 papers

cs.LG2026

A Systematic Study of Small Language Models on Abstract Reasoning Tasks

Nur A Zarin Nishat, Jens Lehmann, Andrei Aioanei +1

Endpoint accuracy on abstract-reasoning benchmarks does not reveal whether a language model has acquired a transferable rule or fit distribution-specific regularities. We study thi…

cs.AI2026

Tycho: Active Abstraction with Programmatic World Models for ARC-AGI-3

Jens Lehmann, Andrei Aioanei, Sahar Vahdati

ARC-AGI-3 turns abstraction into an interactive problem of skill acquisition. A player must infer an unfamiliar game's rules, hidden state, and goal while maintaining action effici…

cs.AI2026

OntoLearner: A Modular Python Library for Ontology Learning with Large Language Models

Hamed Babaei Giglou, Jennifer D'Souza, Andrei Aioanei +2

Ontology learning (OL) aims to automatically construct structured knowledge models from text, yet progress remains fragmented across methods, domains, and evaluation practices. Des…

cs.AI2026

The ARC of Progress towards AGI: A Living Survey of Abstraction and Reasoning

Sahar Vahdati, Andrei Aioanei, Haridhra Suresh +1

The Abstraction and Reasoning Corpus (ARC-AGI) has become a key benchmark for fluid intelligence in AI. This survey presents the first cross-generation analysis of 82 approaches ac…

cs.CL2026

ARC-TGI: Human-Validated Task Generators with Reasoning Chain Templates for ARC-AGI

Jens Lehmann, Syeda Khushbakht, Nikoo Salehfard +4

The Abstraction and Reasoning Corpus (ARC-AGI) probes few-shot abstraction and rule induction on small visual grids, but progress is difficult to measure on static collections of h…

cs.AI2025

DeepResearch: A Recursive Agentic Workflow for Complex Scientific Question Answering in Ecology

Jennifer D'Souza, Endres Keno Sander, Andrei Aioanei

We introduce DeepResearch, a novel agentic LLM-based system for automated scientific synthesis that supports recursive, depth- and breadth-controlled exploration of…

cs.CV2023

Deep Aramaic: Towards a Synthetic Data Paradigm Enabling Machine Learning in Epigraphy

Andrei C. Aioanei, Regine Hunziker-Rodewald, Konstantin Klein +1

Epigraphy increasingly turns to modern artificial intelligence (AI) technologies such as machine learning (ML) for extracting insights from ancient inscriptions. However, scarce la…