activity
20172026
most citedSemEval-2019 Task 8: Fact Checking in Community Question Answering Forums

1 citations · 2 across the 12 of their papers we have counts for

collaborators

15 papers

cs.CY2026

Analyzing the Difficulty of Programming Assignments with Interpretable Knowledge Component Metrics

Tsvetomila Mihaylova, Jing Fan, Bita Akram +4

This research paper examines how Knowledge Components (KCs) - fine-grained concepts or skills required to solve programming tasks - can be used as interpretable signals for underst…

cs.HC2026

The Effects of Structured LLM-Generated Feedback on Programming Assignment Performance

Tsvetomila Mihaylova, Evanfiya Logacheva, Arto Hellas +6

When programming students encounter errors in their code, compiler messages or static analysis output often provide limited guidance, particularly for novice programmers. Personali…

cs.RO2026

Relational Scene Graphs for Object Grounding of Natural Language Commands

Julia Kuhn, Francesco Verdoja, Tsvetomila Mihaylova +1

Robots are finding wider adoption in human environments, increasing the need for natural human-robot interaction. However, understanding a natural language command requires the rob…

cs.CL2026

When Looks Do Not Lie: Discourse Structure Guided In-Context Learning for Faithful Diagram Generation

Evanfiya Logacheva, Arto Hellas, Tsvetomila Mihaylova +3

GenAI is widespread in educational applications; however, it is known to generate content with intrinsic and extrinsic hallucination. We introduce a novel method for ICL diagram ge…

cs.HC2025

Injecting Conflict Situations in Autonomous Driving Simulation using CARLA

Tsvetomila Mihaylova, Stefan Reitmann, Elin A. Topp +1

Simulation of conflict situations for autonomous driving research is crucial for understanding and managing interactions between Automated Vehicles (AVs) and human drivers. This pa…

cs.RO2024

Do Visual-Language Grid Maps Capture Latent Semantics?

Matti Pekkanen, Tsvetomila Mihaylova, Francesco Verdoja +1

Visual-language models (VLMs) have recently been introduced in robotic mapping using the latent representations, i.e., embeddings, of the VLMs to represent semantics in the map. Th…