1 citations · 1 across the 9 of their papers we have counts for
10 papers
ToolHACE: A Dataset for Detecting Hallucinations in Tool-Based LLM Responses
Nikolay Ivanov, Sergey Pletenev, Elisei Rykov +8
Tool-augmented language models ground their responses in external tool outputs, improving reliability beyond parametric knowledge alone. However, even when the correct tool is call…
Enoki: Efficient Multi-Level Hallucination Detection
Elisei Rykov, Timur Ionov, Nikolay Ivanov +5
Ensuring factuality remains a critical challenge for deploying LLMs in high-stakes settings. Existing hallucination detectors usually operate at a single level: claim-level methods…
MemToC: Benchmarking Memory-Tool Conflict Resolution in Large Language Models
Arseniy Varlamov, Rishat Zinnatullin, Elisei Rykov +2
Tool-augmented LLMs must arbitrate between two fallible sources when a tool return conflicts with their parametric memory, yet existing evaluations measure source preference withou…
Learning Selective LLM Autonomy from Copilot Feedback in Enterprise Customer Support Workflows
Nikita Borovkov, Elisei Rykov, Olga Tsymboi +4
We present a deployed system that automates end-to-end customer support workflows inside an enterprise Business Process Management (BPM) platform. The approach is scalable in produ…
Multimodal Evaluation of Russian-language Architectures
Artem Chervyakov, Ulyana Isaeva, Anton Emelyanov +15
Multimodal large language models (MLLMs) are currently at the center of research attention, showing rapid progress in scale and capabilities, yet their intelligence, limitations, a…
When Models Lie, We Learn: Multilingual Span-Level Hallucination Detection with PsiloQA
Elisei Rykov, Kseniia Petrushina, Maksim Savkin +6
Hallucination detection remains a fundamental challenge for the safe and reliable deployment of large language models (LLMs), especially in applications requiring factual accuracy.…
Don't Fight Hallucinations, Use Them: Estimating Image Realism using NLI over Atomic Facts
Elisei Rykov, Kseniia Petrushina, Kseniia Titova +2
Quantifying the realism of images remains a challenging problem in the field of artificial intelligence. For example, an image of Albert Einstein holding a smartphone violates comm…
SmurfCat at PAN 2024 TextDetox: Alignment of Multilingual Transformers for Text Detoxification
Elisei Rykov, Konstantin Zaytsev, Ivan Anisimov +1
This paper presents a solution for the Multilingual Text Detoxification task in the PAN-2024 competition of the SmurfCat team. Using data augmentation through machine translation a…
S3: A Simple Strong Sample-effective Multimodal Dialog System
Elisei Rykov, Egor Malkershin, Alexander Panchenko
In this work, we present a conceptually simple yet powerful baseline for the multimodal dialog task, an S3 model, that achieves near state-of-the-art results on two compelling lead…
SmurfCat at SemEval-2024 Task 6: Leveraging Synthetic Data for Hallucination Detection
Elisei Rykov, Yana Shishkina, Kseniia Petrushina +3
In this paper, we present our novel systems developed for the SemEval-2024 hallucination detection task. Our investigation spans a range of strategies to compare model predictions…