collaborators

9 papers

cs.LG2026

Big Claims, Small Margins: Do Reported GraphLLM Gains Survive Simple Baselines?

Michal Podstawski

LLM-based methods for node classification on text-attributed graphs (TAGs) routinely report state-of-the-art accuracy. We ask how these results compare with inexpensive baselines r…

cs.LG2026

SLM-Conditioned Hierarchical Relation Routing for Labeled Property Graph Learning

Michal Podstawski

Labeled property graphs combine relational structure with heterogeneous textual and categorical properties attached to both nodes and relationships. Conventional graph neural netwo…

cs.LG2026

Closed-Loop Graph Algorithm Execution with Small Language Models: Step Accuracy and Rollout Reliability

Michal Podstawski

Small language models offer an efficient alternative to large-scale systems, but their ability to execute structured algorithms over multiple dependent decisions remains poorly und…

cs.LG2026

Graph Property Inference in Small Language Models: Effects of Representation and Reasoning Strategy

Michal Podstawski

Recent progress in language modeling has expanded the range of tasks that can be approached through natural language interfaces, including problems that require structured reasonin…

cs.LG2026

Generalization Boundaries of Fine-Tuned Small Language Models for Graph Structural Inference

Michal Podstawski

Small language models fine-tuned for graph property estimation have demonstrated strong in-distribution performance, yet their generalization capabilities beyond training condition…

cs.LG2025

TinyGraphEstimator: Adapting Lightweight Language Models for Graph Structure Inference

Michal Podstawski

Graphs provide a universal framework for representing complex relational systems, and inferring their structural properties is a core challenge in graph analysis and reasoning. Whi…

cs.CL2025

Applying Text Embedding Models for Efficient Analysis in Labeled Property Graphs

Michal Podstawski

Labeled property graphs often contain rich textual attributes that can enhance analytical tasks when properly leveraged. This work explores the use of pretrained text embedding mod…

cs.CV2025

Face Consistency Benchmark for GenAI Video

Michal Podstawski, Malgorzata Kudelska, Haohong Wang

Video generation driven by artificial intelligence has advanced significantly, enabling the creation of dynamic and realistic content. However, maintaining character consistency ac…

cs.HC2025

EdgeWisePersona: A Dataset for On-Device User Profiling from Natural Language Interactions

Patryk Bartkowiak, Michal Podstawski

This paper introduces a novel dataset and evaluation benchmark designed to assess and improve small language models deployable on edge devices, with a focus on user profiling from…