13 citations · 14 across the 4 of their papers we have counts for
5 papers
Lightweight Latent Verifiers for Efficient Meta-Generation Strategies
Bartosz Piotrowski, Witold Drzewakowski, Konrad Staniszewski +1
Verifiers are auxiliary models that assess the correctness of outputs generated by base large language models (LLMs). They play a crucial role in many strategies for solving reason…
Analysing The Impact of Sequence Composition on Language Model Pre-Training
Yu Zhao, Yuanbin Qu, Konrad Staniszewski +5
Most language model pre-training frameworks concatenate multiple documents into fixed-length sequences and use causal masking to compute the likelihood of each token given its cont…
Structured Packing in LLM Training Improves Long Context Utilization
Konrad Staniszewski, Szymon Tworkowski, Sebastian Jaszczur +4
Recent advancements in long-context large language models have attracted significant attention, yet their practical applications often suffer from suboptimal context utilization. T…
Focused Transformer: Contrastive Training for Context Scaling
Szymon Tworkowski, Konrad Staniszewski, Mikołaj Pacek +3
Large language models have an exceptional capability to incorporate new information in a contextual manner. However, the full potential of such an approach is often restrained due…
Parity Games of Bounded Tree-Depth
Konrad Staniszewski
The exact complexity of solving parity games is a major open problem. Several authors have searched for efficient algorithms over specific classes of graphs. In particular, Obdržál…