activity
20242026
collaborators

9 papers

cs.AI2026

The Reliability Gap in Benchmark Auditing: Distribution Shift and Scale as Failure Modes of Contamination Detection

Wojciech Zarzecki, Jan Dubiński, Sebastian Cygert

Benchmark contamination, where evaluation examples appear in a model's training data, threatens the validity of LLM assessment. Statistical tools for detecting training-data member…

cs.CV2026

Beyond Classification: Dynamic Adapter Routing for Continual Multimodal Retrieval

Alicja Dobrzeniecka, Filip Szatkowski, Sebastian Cygert +2

While retrieval is a core function of vision-language models, continually updating these models for retrieval tasks remains critically underexplored. Existing work often approaches…

cs.CL2026

Monitoring the Internal Monologue: Probe Trajectories Reveal Reasoning Dynamics

Maciej ChrabÄ szcz, Aleksander Szymczyk, Marcin Sendera +2

Large Reasoning Models (LRMs) introduce new opportunities for safety monitoring through their Chain of Thought (CoT) reasoning. However, CoT is not always faithful to the model's f…

cs.LG2026

Efficient Multi-Source Knowledge Transfer by Model Merging

Marcin Osial, Bartosz Wójcik, Bartosz Zieliński +1

While transfer learning is an effective strategy, it often overlooks the opportunity to leverage knowledge from numerous available models online. Addressing this multi-source trans…

cs.LG2026

Subspace Optimization for Backpropagation-Free Continual Test-Time Adaptation

Damian Sójka, Sebastian Cygert, Marc Masana

We introduce PACE, a backpropagation-free continual test-time adaptation system that directly optimizes the affine parameters of normalization layers. Existing derivative-free appr…

cs.CL2026

Annotation-Efficient Vision-Language Model Adaptation to the Polish Language Using the LLaVA Framework

Grzegorz Statkiewicz, Alicja Dobrzeniecka, Karolina Seweryn +5

Most vision-language models (VLMs) are trained on English-centric data, limiting their performance in other languages and cultural contexts. This restricts their usability for non-…