31 citations · 81 across the 8 of their papers we have counts for
8 papers
Context-weighted Discrete Flow Matching
Daniil Cherniavskii, Daniel Severo, Karen Ullrich
Discrete flow matching provides a flexible framework for generative modeling on discrete structures. However, the standard factorized training objective exposes the model to target…
Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems
Antonios Tragoudaras, Chenyu Zhang, Daniil Cherniavskii +7
Recent advances in image and video generation raise hopes that these models possess world modeling capabilities-the ability to generate realistic, physically plausible videos. This…
Uncertainty Estimation of Transformers' Predictions via Topological Analysis of the Attention Matrices
Elizaveta Kostenok, Daniil Cherniavskii, Alexey Zaytsev
Transformer-based language models have set new benchmarks across a wide range of NLP tasks, yet reliably estimating the uncertainty of their predictions remains a significant chall…
Intrinsic Dimension Estimation for Robust Detection of AI-Generated Texts
Eduard Tulchinskii, Kristian Kuznetsov, Laida Kushnareva +5
Rapidly increasing quality of AI-generated content makes it difficult to distinguish between human and AI-generated texts, which may lead to undesirable consequences for society. T…
Learning Topology-Preserving Data Representations
Ilya Trofimov, Daniil Cherniavskii, Eduard Tulchinskii +3
We propose a method for learning topology-preserving data representations (dimensionality reduction). The method aims to provide topological similarity between the data manifold an…
Topological Data Analysis for Speech Processing
Eduard Tulchinskii, Kristian Kuznetsov, Laida Kushnareva +5
We apply topological data analysis (TDA) to speech classification problems and to the introspection of a pretrained speech model, HuBERT. To this end, we introduce a number of topo…
Acceptability Judgements via Examining the Topology of Attention Maps
Daniil Cherniavskii, Eduard Tulchinskii, Vladislav Mikhailov +7
The role of the attention mechanism in encoding linguistic knowledge has received special interest in NLP. However, the ability of the attention heads to judge the grammatical acce…
Artificial Text Detection via Examining the Topology of Attention Maps
Laida Kushnareva, Daniil Cherniavskii, Vladislav Mikhailov +6
The impressive capabilities of recent generative models to create texts that are challenging to distinguish from the human-written ones can be misused for generating fake news, pro…