1 citations · 1 across the 8 of their papers we have counts for
10 papers
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…
SIRIN: A Unified Toolkit for Detecting Contextual Hallucinations in Retrieval-Augmented and Memory-Grounded LLM Systems
Julia Belikova, Rauf Parchiev, Mikhail Filimonov +3
SIRIN (Semantic Inconsistency Recognition and Inspection Nexus) is a unified toolkit and interactive web UI for detecting contextual hallucinations (fluent, plausible responses uns…
Managing Procedural Memory in LLM Agents: Control, Adaptation, and Evaluation
Julia Belikova, Rauf Parchiev, Evgeny Egorov +4
Procedural memory is increasingly used to improve LLM agents on recurring workplace tasks, yet its ability to produce reusable skills remains poorly understood. We introduce AFTER,…
Embedding-Aware Feature Discovery: Bridging Latent Representations and Interpretable Features in Event Sequences
Artem Sakhno, Ivan Sergeev, Alexey Shestov +5
Industrial financial systems operate on temporal event sequences such as transactions, user actions, and system logs. While recent research emphasizes representation learning and l…
Financial Transaction Retrieval and Contextual Evidence for Knowledge-Grounded Reasoning
Artem Sakhno, Daniil Tomilov, Yuliana Shakhvalieva +5
Nowadays, success of financial organizations heavily depends on their ability to process digital traces generated by their clients, e.g., transaction histories, gathered from vario…
Topological Metric for Unsupervised Embedding Quality Evaluation
Aleksei Shestov, Anton Klenitskiy, Daria Denisova +4
Modern representation learning increasingly relies on unsupervised and self-supervised methods trained on large-scale unlabeled data. While these approaches achieve impressive gene…