7 papers
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…
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…
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…
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…
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…
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…